{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import gc\n", "np.seterr(divide='ignore', invalid='ignore')\n", "from warnings import simplefilter\n", "simplefilter(action=\"ignore\", category=pd.errors.PerformanceWarning)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from rdkit import Chem\n", "from rdkit import DataStructs\n", "from rdkit import RDConfig\n", "from rdkit.Chem.Fingerprints import ClusterMols, DbFpSupplier, MolSimilarity, SimilarityScreener\n", "from rdkit.Chem.Fingerprints import FingerprintMols as fp\n", "from rdkit.Chem import AllChem, rdmolops, Lipinski, Descriptors\n", "from rdkit.Chem.Descriptors import ExactMolWt, HeavyAtomMolWt, MolWt \n", "from rdkit.Chem.AllChem import GetMorganFingerprintAsBitVect\n", "from rdkit.DataStructs.cDataStructs import ConvertToNumpyArray\n", "from rdkit.Avalon.pyAvalonTools import GetAvalonFP " ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "import tensorflow as tf\n", "from tensorflow import keras\n", "from tensorflow.keras import layers\n", "from tensorflow.keras.models import Sequential\n", "from tensorflow.keras.layers import Dense, Dropout, Activation\n", "from tensorflow.keras.regularizers import l2\n", "from tensorflow.keras.optimizers import Adam\n", "from tensorflow.keras import regularizers\n", "\n", "from sklearn.model_selection import train_test_split\n", "from sklearn.metrics import r2_score,mean_absolute_error,mean_squared_error" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "gpus = tf.config.experimental.list_physical_devices('GPU')\n", "if gpus:\n", " try:\n", " tf.config.experimental.set_memory_growth(gpus[0], True)\n", " except RuntimeError as e:\n", " print(e)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "data_ws = pd.read_csv('./data/ws496_logS.csv')\n", "data_ws['SMILES'] = pd.Series(data_ws['SMILES'], dtype=\"string\")\n", "smiles_ws = data_ws.iloc[:,1]\n", "y_ws = data_ws.iloc[:,2]\n", "\n", "data_delaney = pd.read_csv('./data/delaney-processed.csv')\n", "data_delaney['smiles'] = pd.Series(data_delaney['smiles'], dtype=\"string\")\n", "smiles_de = data_delaney.iloc[:,-1]\n", "y_de= data_delaney.iloc[:,1]\n", "\n", "data_lovric2020 = pd.read_csv('./data/Lovric2020_logS0.csv')\n", "data_lovric2020['isomeric_smiles'] = pd.Series(data_lovric2020['isomeric_smiles'], dtype=\"string\")\n", "smiles_lo = data_lovric2020.iloc[:,0]\n", "y_lo = data_lovric2020.iloc[:,1]\n", "\n", "data_huuskonen = pd.read_csv('./data/huusk.csv')\n", "data_huuskonen['SMILES'] = pd.Series(data_huuskonen['SMILES'], dtype=\"string\")\n", "smiles_hu = data_huuskonen.iloc[:,4]\n", "y_hu = data_huuskonen.iloc[:,-1].astype('float')\n", "\n", "y_ws_nponly = y_ws.to_numpy()\n", "y_de_nponly = y_de.to_numpy()\n", "y_lo_nponly = y_lo.to_numpy()\n", "y_hu_nponly = y_hu.to_numpy()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "def mol3d_conv(mol):\n", " for i in mol: \n", " Chem.AssignAtomChiralTagsFromStructure(i)\n", " AllChem.EmbedMolecule(i, useExpTorsionAnglePrefs=True,useBasicKnowledge=True)\n", " _ = Chem.MolToMolBlock(i,confId=-1)\n", " return mol\n", "\n", "def mol3d_conv2(mol):\n", " for i in mol:\n", " AllChem.Compute2DCoords(i)\n", " input = Chem.AddHs(i)\n", " ps = AllChem.ETKDGv2()\n", " ps.randomSeed = 0xf00d\n", " AllChem.EmbedMolecule(input,ps)\n", " return mol\n", "\n", "def conformer_idf(func, mol):\n", " arr=[]\n", " for i in mol:\n", " if i.GetNumConformers() == 1:\n", " res = np.asarray(func(i)).astype('float')\n", " arr.append(res)\n", " elif i.GetNumConformers() == 0:\n", " arr.append(0.0)\n", " else:\n", " print(f\"Every molecule must have at most 1 conformer!\")\n", " return arr" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "def fp_converter(data):\n", " LEN_OF_FF = 2048\n", " mols = [Chem.MolFromSmiles(data) for data in data]\n", " ECFP = [AllChem.GetMorganFingerprintAsBitVect(data, 2, nBits=LEN_OF_FF) for data in mols]\n", " MACCS = [Chem.rdMolDescriptors.GetMACCSKeysFingerprint(data) for data in mols]\n", " AvalonFP = [GetAvalonFP(data) for data in mols]\n", "\n", " ECFP_container = []\n", " MACCS_container = []\n", " AvalonFP_container=AvalonFP\n", " for fps in ECFP:\n", " arr = np.zeros((1,), dtype=int)\n", " DataStructs.ConvertToNumpyArray(fps, arr)\n", " ECFP_container.append(arr) \n", " \n", " for fps2 in MACCS:\n", " arr2 = np.zeros((1,), dtype=int)\n", " DataStructs.ConvertToNumpyArray(fps2, arr2)\n", " MACCS_container.append(arr2)\n", " \n", " ECFP_container = np.asarray(ECFP_container)\n", " MACCS_container = np.asarray(MACCS_container)\n", " AvalonFP_container = np.asarray(AvalonFP_container) \n", " return mols,ECFP_container, MACCS_container, AvalonFP_container" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "# mol_ws, x_ws, MACCS_ws, AvalonFP_ws = fp_converter(smiles_ws)\n", "# mol_de, x_de, MACCS_de, AvalonFP_de = fp_converter(smiles_de)\n", "# mol_lo, x_lo, MACCS_lo, AvalonFP_lo = fp_converter(smiles_lo)\n", "# mol_hu, x_hu, MACCS_hu, AvalonFP_hu = fp_converter(smiles_hu)\n", "\n", "# group_nws = np.concatenate([x_ws,MACCS_ws,AvalonFP_ws], axis=1)\n", "# group_nde = np.concatenate([x_de,MACCS_de,AvalonFP_de], axis=1)\n", "# group_nlo = np.concatenate([x_lo,MACCS_lo,AvalonFP_lo], axis=1)\n", "# group_nhu = np.concatenate([x_hu,MACCS_hu,AvalonFP_hu], axis=1)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "def search_data_origin(features,fps,mols,name): \n", " phase1 = features[0] # \"MolWeight\"\n", " phase2 = features[1] # \"Mol_MR\"\n", " phase3 = features[2] # \"Mol_TPSA\"\n", " phase4 = features[3] # \"Mol_logP\"\n", " phase5 = features[4] # \"RotatedBonds\"\n", " phase6 = features[5] # \"HeavyAtom\"\n", " phase7 = features[6] # \"numHAcceptor\"\n", " phase8 = features[7] # \"numHDoner\"\n", " phase9 = features[8] # \"numHeteroatom\"\n", " phase10 = features[9] # \"NumValenceElec\"\n", " phase11 = features[10] # \"NHOHCount\"\n", " phase12 = features[11] # \"NOCount\"\n", " phase13 = features[12] # \"Ringcount\"\n", " phase14 = features[13] # \"numAromaticR\"\n", " phase15 = features[14] # \"numSaturateR\"\n", " phase16 = features[15] # \"numAliphaticR\"\n", " phase17 = features[16] # \"LabuteASA\"\n", " phase18 = features[17] # \"BalabanJs\"\n", " phase19 = features[18] # \"BertzCTs\"\n", " phase20 = features[19] # \"ipc\"\n", " phase21 = features[20] # \"kappa_Series[1-3]\"\n", " phase22 = features[21] # \"Chi_Series[13]\"\n", " phase23 = features[22] # \"phi\"\n", " phase24 = features[23] # \"HallKierAlpha\"\n", " phase25 = features[24] # \"NumAmideBonds\"\n", " phase26 = features[25] # \"FractionCSP3\"\n", " phase27 = features[26] # \"NumSpiroAtoms\"\n", " phase28 = features[27] # \"NumBridgeheadAtoms\"\n", " phase29 = features[28] # \"PEOE_VSA_Series[1-14]\"\n", " phase30 = features[29] # \"SMR_VSA_Series[1-10]\"\n", " phase31 = features[30] # \"SlogP_VSA_Series[1-12]\"\n", " phase32 = features[31] # \"EState_VSA_Series[1-11]\"\n", " phase33 = features[32] # \"VSA_EState_Series[1-10]\"\n", " phase34 = features[33] # \"Asphericity\"\n", " phase35 = features[34] # \"PBF\"\n", " phase36 = features[35] # \"PMI_series[1-3]\"\n", " phase37 = features[36] # \"NPR_series[1-2]\"\n", " phase38 = features[37] # \"RadiusOfGyration\"\n", " phase39 = features[38] # \"InertialShapeFactor\"\n", " phase40 = features[39] # \"Eccentricity\"\n", " phase41 = features[40] # \"SpherocityIndex\"\n", " phase42 = features[41] # \"MQNs\"\n", " phase43 = features[42] # \"AUTOCORR2D\"\n", " phase44 = features[43] # \"BCUT2D\", \n", " phase45 = features[44] # \"AUTOCORR3D\"\n", " phase46 = features[45] # \"RDF\"\n", " phase47 = features[46] # \"MORSE\"\n", " phase48 = features[47] # \"WHIM\"\n", " phase49 = features[48] # \"GETAWAY\"\n", " ##############\n", " if phase1 == 1:\n", " descriptor = [ExactMolWt(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor \n", " if phase2 == 1:\n", " descriptor = [Chem.Crippen.MolMR (mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor \n", " if phase3 == 1:\n", " descriptor = [Descriptors.TPSA(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor \n", " if phase4 == 1:\n", " descriptor = [Chem.Crippen.MolLogP(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor \n", " if phase5 == 1:\n", " descriptor = [Chem.Lipinski.NumRotatableBonds(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor\n", " if phase6 == 1:\n", " descriptor = [Chem.Lipinski.HeavyAtomCount(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor\n", " if phase7 == 1:\n", " descriptor = [Chem.Lipinski.NumHAcceptors(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor \n", " if phase8 == 1:\n", " descriptor = [Chem.Lipinski.NumHDonors(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor \n", " if phase9 == 1:\n", " descriptor = [Chem.Lipinski.NumHeteroatoms(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor \n", " if phase10 == 1:\n", " descriptor = [Chem.Descriptors.NumValenceElectrons(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor\n", " if phase11 == 1:\n", " descriptor = [Chem.Lipinski.NHOHCount(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor\n", " if phase12 == 1:\n", " descriptor = [Chem.Lipinski.NOCount(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor \n", " if phase13 == 1:\n", " descriptor = [Chem.Lipinski.RingCount(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor \n", " if phase14 == 1:\n", " descriptor = [Chem.Lipinski.NumAromaticRings(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor \n", " if phase15 == 1:\n", " descriptor = [Chem.Lipinski.NumSaturatedRings(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor\n", " if phase16 == 1:\n", " descriptor = [Chem.Lipinski.NumAliphaticRings(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor\n", " if phase17 == 1:\n", " descriptor = [Chem.rdMolDescriptors.CalcLabuteASA(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor \n", " if phase18 == 1:\n", " descriptor = [Chem.GraphDescriptors.BalabanJ(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor \n", " if phase19 == 1:\n", " descriptor = [Chem.GraphDescriptors.BertzCT(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor\n", " if phase20 == 1:\n", " descriptor = [Chem.GraphDescriptors.Ipc(alpha) for alpha in mols]\n", " descriptor = conformer_idf(Chem.GraphDescriptors.Ipc, mols)\n", " descriptor = np.log1p(descriptor)\n", " descriptor = np.nan_to_num(descriptor, nan=0.0)\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor\n", " if phase21 == 1:\n", " kappa1 = [Chem.GraphDescriptors.Kappa1(mols) for mols in mols]\n", " kappa2 = [Chem.GraphDescriptors.Kappa2(mols) for mols in mols]\n", " kappa3 = [Chem.GraphDescriptors.Kappa3(mols) for mols in mols]\n", " kappa1 = np.asarray(kappa1).astype('float')\n", " kappa2 = np.asarray(kappa2).astype('float')\n", " kappa3 = np.asarray(kappa3).astype('float')\n", " fps = np.concatenate([fps,kappa1[:,None],kappa2[:,None],kappa3[:,None]], axis=1)\n", " del kappa1,kappa2,kappa3\n", " if phase22 == 1:\n", " def values_chiN(mols):\n", " list_char=[]\n", " i=0\n", " while(1):\n", " if Chem.GraphDescriptors.ChiNn_(mols,i)==0.0:\n", " break\n", " list_char.append(Chem.GraphDescriptors.ChiNn_(mols,i))\n", " i+=1\n", " res = np.array(list_char)\n", " return res\n", " def values_chiV(mols):\n", " list_char=[]\n", " i=0\n", " while(1):\n", " if Chem.GraphDescriptors.ChiNv_(mols,i)==0.0:\n", " break\n", " list_char.append(Chem.GraphDescriptors.ChiNv_(mols,i))\n", " i+=1\n", " res = np.array(list_char)\n", " return res\n", " Chi0 = [Chem.GraphDescriptors.Chi0(mols) for mols in mols]\n", " Chi0n = [Chem.GraphDescriptors.Chi0n(mols) for mols in mols]\n", " Chi0v = [Chem.GraphDescriptors.Chi0v(mols) for mols in mols]\n", " Chi1 = [Chem.GraphDescriptors.Chi1(mols) for mols in mols]\n", " Chi1n = [Chem.GraphDescriptors.Chi1n(mols) for mols in mols]\n", " Chi1v = [Chem.GraphDescriptors.Chi1v(mols) for mols in mols]\n", " Chi2n = [Chem.GraphDescriptors.Chi2n(mols) for mols in mols]\n", " Chi2v = [Chem.GraphDescriptors.Chi2v(mols) for mols in mols]\n", " Chi3n = [Chem.GraphDescriptors.Chi3n(mols) for mols in mols]\n", " Chi3v = [Chem.GraphDescriptors.Chi3v(mols) for mols in mols]\n", " Chi4n = [Chem.GraphDescriptors.Chi4n(mols) for mols in mols]\n", " Chi4v = [Chem.GraphDescriptors.Chi4v(mols) for mols in mols]\n", " max_num1 = 0\n", " max_num2 = 0\n", " ChiNn_ = [values_chiN(alpha) for alpha in mols]\n", " ChiNv_ = [values_chiV(alpha) for alpha in mols]\n", " Chi0 = np.asarray(Chi0 ).astype('float')\n", " Chi0n = np.asarray(Chi0n).astype('float')\n", " Chi0v = np.asarray(Chi0v).astype('float')\n", " Chi1 = np.asarray(Chi1 ).astype('float')\n", " Chi1n = np.asarray(Chi1n).astype('float')\n", " Chi1v = np.asarray(Chi1v).astype('float')\n", " Chi2n = np.asarray(Chi2n).astype('float')\n", " Chi2v = np.asarray(Chi2v).astype('float')\n", " Chi3n = np.asarray(Chi3n).astype('float')\n", " Chi3v = np.asarray(Chi3v).astype('float')\n", " Chi4n = np.asarray(Chi4n).astype('float')\n", " Chi4v = np.asarray(Chi4v).astype('float')\n", " ChiNn_ = [np.resize(alpha, max_num1) for alpha in ChiNn_]\n", " ChiNv_ = [np.resize(alpha, max_num2) for alpha in ChiNv_]\n", " fps = np.concatenate([fps,Chi0[:,None],\n", " Chi0n[:,None],\n", " Chi0v[:,None],\n", " Chi1[:,None],\n", " Chi1n[:,None],\n", " Chi1v[:,None],\n", " Chi2n[:,None],\n", " Chi2v[:,None],\n", " Chi3n[:,None],\n", " Chi3v[:,None],\n", " Chi4n[:,None],\n", " Chi4v[:,None],\n", " ChiNn_,\n", " ChiNv_\n", " ], axis=1)\n", " fps = np.concatenate([fps,ChiNn_], axis=1)\n", " fps = np.concatenate([fps,ChiNv_], axis=1)\n", " del Chi0,Chi0n,Chi0v,Chi1,Chi1n,Chi1v,Chi2n,Chi2v,Chi3n,Chi3v,Chi4n,Chi4v,ChiNn_,ChiNv_\n", " if phase23 == 1:\n", " descriptor = [Chem.rdMolDescriptors.CalcPhi(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor\n", " if phase24 == 1:\n", " descriptor = [Chem.GraphDescriptors.HallKierAlpha(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor \n", " if phase25 == 1:\n", " descriptor = [Chem.rdMolDescriptors.CalcNumAmideBonds(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor \n", " if phase26 == 1:\n", " descriptor = [Chem.Lipinski.FractionCSP3(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor \n", " if phase27 == 1:\n", " descriptor = [Chem.rdMolDescriptors.CalcNumSpiroAtoms(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor\n", " if phase28 == 1:\n", " descriptor = [Chem.rdMolDescriptors.CalcNumBridgeheadAtoms(mols) for mols in mols]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor\n", " ####\n", " if phase29 == 1:\n", " PEOE_VSA1 = [Chem.MolSurf.PEOE_VSA1(mols) for mols in mols]\n", " PEOE_VSA2 = [Chem.MolSurf.PEOE_VSA2(mols) for mols in mols]\n", " PEOE_VSA3 = [Chem.MolSurf.PEOE_VSA3(mols) for mols in mols]\n", " PEOE_VSA4 = [Chem.MolSurf.PEOE_VSA4(mols) for mols in mols]\n", " PEOE_VSA5 = [Chem.MolSurf.PEOE_VSA5(mols) for mols in mols]\n", " PEOE_VSA6 = [Chem.MolSurf.PEOE_VSA6(mols) for mols in mols]\n", " PEOE_VSA7 = [Chem.MolSurf.PEOE_VSA7(mols) for mols in mols]\n", " PEOE_VSA8 = [Chem.MolSurf.PEOE_VSA8(mols) for mols in mols]\n", " PEOE_VSA9 = [Chem.MolSurf.PEOE_VSA9(mols) for mols in mols]\n", " PEOE_VSA10 = [Chem.MolSurf.PEOE_VSA10(mols) for mols in mols]\n", " PEOE_VSA11 = [Chem.MolSurf.PEOE_VSA11(mols) for mols in mols]\n", " PEOE_VSA12 = [Chem.MolSurf.PEOE_VSA12(mols) for mols in mols]\n", " PEOE_VSA13 = [Chem.MolSurf.PEOE_VSA13(mols) for mols in mols]\n", " PEOE_VSA14 = [Chem.MolSurf.PEOE_VSA14(mols) for mols in mols]\n", " PEOE_VSA1 = np.asarray(PEOE_VSA1).astype('float')\n", " PEOE_VSA2 = np.asarray(PEOE_VSA2).astype('float')\n", " PEOE_VSA3 = np.asarray(PEOE_VSA3).astype('float')\n", " PEOE_VSA4 = np.asarray(PEOE_VSA4).astype('float')\n", " PEOE_VSA5 = np.asarray(PEOE_VSA5).astype('float')\n", " PEOE_VSA6 = np.asarray(PEOE_VSA6).astype('float')\n", " PEOE_VSA7 = np.asarray(PEOE_VSA7).astype('float')\n", " PEOE_VSA8 = np.asarray(PEOE_VSA8).astype('float')\n", " PEOE_VSA9 = np.asarray(PEOE_VSA9).astype('float')\n", " PEOE_VSA10 = np.asarray(PEOE_VSA10).astype('float')\n", " PEOE_VSA11 = np.asarray(PEOE_VSA11).astype('float')\n", " PEOE_VSA12 = np.asarray(PEOE_VSA12).astype('float')\n", " PEOE_VSA13 = np.asarray(PEOE_VSA13).astype('float')\n", " PEOE_VSA14 = np.asarray(PEOE_VSA14).astype('float')\n", " fps = np.concatenate([fps,PEOE_VSA1[:,None],\n", " PEOE_VSA2[:,None],\n", " PEOE_VSA3[:,None],\n", " PEOE_VSA4[:,None],\n", " PEOE_VSA5[:,None],\n", " PEOE_VSA6[:,None],\n", " PEOE_VSA7[:,None],\n", " PEOE_VSA8[:,None],\n", " PEOE_VSA9[:,None],\n", " PEOE_VSA10[:,None],\n", " PEOE_VSA11[:,None],\n", " PEOE_VSA12[:,None],\n", " PEOE_VSA13[:,None],\n", " PEOE_VSA14[:,None]], axis=1)\n", " del PEOE_VSA1,PEOE_VSA2,PEOE_VSA3,PEOE_VSA4,PEOE_VSA5,PEOE_VSA6,PEOE_VSA7,PEOE_VSA8,PEOE_VSA9,PEOE_VSA10,PEOE_VSA11,PEOE_VSA12,PEOE_VSA13,PEOE_VSA14\n", " ########\n", " if phase30 == 1:\n", " SMR_VSA1 = [Chem.MolSurf.SMR_VSA1(mols) for mols in mols]\n", " SMR_VSA2 = [Chem.MolSurf.SMR_VSA2(mols) for mols in mols]\n", " SMR_VSA3 = [Chem.MolSurf.SMR_VSA3(mols) for mols in mols]\n", " SMR_VSA4 = [Chem.MolSurf.SMR_VSA4(mols) for mols in mols]\n", " SMR_VSA5 = [Chem.MolSurf.SMR_VSA5(mols) for mols in mols]\n", " SMR_VSA6 = [Chem.MolSurf.SMR_VSA6(mols) for mols in mols]\n", " SMR_VSA7 = [Chem.MolSurf.SMR_VSA7(mols) for mols in mols]\n", " SMR_VSA8 = [Chem.MolSurf.SMR_VSA8(mols) for mols in mols]\n", " SMR_VSA9 = [Chem.MolSurf.SMR_VSA9(mols) for mols in mols]\n", " SMR_VSA10 = [Chem.MolSurf.SMR_VSA10(mols) for mols in mols]\n", " SMR_VSA1 = np.asarray(SMR_VSA1 ).astype('float')\n", " SMR_VSA2 = np.asarray(SMR_VSA2 ).astype('float')\n", " SMR_VSA3 = np.asarray(SMR_VSA3 ).astype('float')\n", " SMR_VSA4 = np.asarray(SMR_VSA4 ).astype('float')\n", " SMR_VSA5 = np.asarray(SMR_VSA5 ).astype('float')\n", " SMR_VSA6 = np.asarray(SMR_VSA6 ).astype('float')\n", " SMR_VSA7 = np.asarray(SMR_VSA7 ).astype('float')\n", " SMR_VSA8 = np.asarray(SMR_VSA8 ).astype('float')\n", " SMR_VSA9 = np.asarray(SMR_VSA9 ).astype('float')\n", " SMR_VSA10 = np.asarray(SMR_VSA10).astype('float')\n", " fps = np.concatenate([fps,SMR_VSA1[:,None],\n", " SMR_VSA2[:,None],\n", " SMR_VSA3[:,None],\n", " SMR_VSA4[:,None],\n", " SMR_VSA5[:,None],\n", " SMR_VSA6[:,None],\n", " SMR_VSA7[:,None],\n", " SMR_VSA8[:,None],\n", " SMR_VSA9[:,None],\n", " SMR_VSA10[:,None]], axis=1)\n", " del SMR_VSA1,SMR_VSA2,SMR_VSA3,SMR_VSA4,SMR_VSA5,SMR_VSA6,SMR_VSA7,SMR_VSA8,SMR_VSA9,SMR_VSA10\n", " ########\n", " if phase31 == 1:\n", " SlogP_VSA1 = [Chem.MolSurf.SlogP_VSA1(mols) for mols in mols]\n", " SlogP_VSA2 = [Chem.MolSurf.SlogP_VSA2(mols) for mols in mols]\n", " SlogP_VSA3 = [Chem.MolSurf.SlogP_VSA3(mols) for mols in mols]\n", " SlogP_VSA4 = [Chem.MolSurf.SlogP_VSA4(mols) for mols in mols]\n", " SlogP_VSA5 = [Chem.MolSurf.SlogP_VSA5(mols) for mols in mols]\n", " SlogP_VSA6 = [Chem.MolSurf.SlogP_VSA6(mols) for mols in mols]\n", " SlogP_VSA7 = [Chem.MolSurf.SlogP_VSA7(mols) for mols in mols]\n", " SlogP_VSA8 = [Chem.MolSurf.SlogP_VSA8(mols) for mols in mols]\n", " SlogP_VSA9 = [Chem.MolSurf.SlogP_VSA9(mols) for mols in mols]\n", " SlogP_VSA10 = [Chem.MolSurf.SlogP_VSA10(mols) for mols in mols]\n", " SlogP_VSA11 = [Chem.MolSurf.SlogP_VSA11(mols) for mols in mols]\n", " SlogP_VSA12 = [Chem.MolSurf.SlogP_VSA12(mols) for mols in mols]\n", " SlogP_VSA1 = np.asarray(SlogP_VSA1).astype('float')\n", " SlogP_VSA2 = np.asarray(SlogP_VSA2).astype('float')\n", " SlogP_VSA3 = np.asarray(SlogP_VSA3).astype('float')\n", " SlogP_VSA4 = np.asarray(SlogP_VSA4).astype('float')\n", " SlogP_VSA5 = np.asarray(SlogP_VSA5).astype('float')\n", " SlogP_VSA6 = np.asarray(SlogP_VSA6).astype('float')\n", " SlogP_VSA7 = np.asarray(SlogP_VSA7).astype('float')\n", " SlogP_VSA8 = np.asarray(SlogP_VSA8).astype('float')\n", " SlogP_VSA9 = np.asarray(SlogP_VSA9).astype('float')\n", " SlogP_VSA10 = np.asarray(SlogP_VSA10).astype('float')\n", " SlogP_VSA11 = np.asarray(SlogP_VSA11).astype('float')\n", " SlogP_VSA12 = np.asarray(SlogP_VSA12).astype('float')\n", " fps = np.concatenate([fps,SlogP_VSA1[:,None],\n", " SlogP_VSA2[:,None],\n", " SlogP_VSA3[:,None],\n", " SlogP_VSA4[:,None],\n", " SlogP_VSA5[:,None],\n", " SlogP_VSA6[:,None],\n", " SlogP_VSA7[:,None],\n", " SlogP_VSA8[:,None],\n", " SlogP_VSA9[:,None],\n", " SlogP_VSA10[:,None],\n", " SlogP_VSA11[:,None],\n", " SlogP_VSA12[:,None]], axis=1)\n", " del SlogP_VSA1,SlogP_VSA2,SlogP_VSA3,SlogP_VSA4,SlogP_VSA5,SlogP_VSA6,SlogP_VSA7,SlogP_VSA8,SlogP_VSA9,SlogP_VSA10,SlogP_VSA11,SlogP_VSA12\n", " ########\n", " if phase32 == 1:\n", " EState_VSA1 = [Chem.EState.EState_VSA.EState_VSA1(mols) for mols in mols]\n", " EState_VSA2 = [Chem.EState.EState_VSA.EState_VSA2(mols) for mols in mols]\n", " EState_VSA3 = [Chem.EState.EState_VSA.EState_VSA3(mols) for mols in mols]\n", " EState_VSA4 = [Chem.EState.EState_VSA.EState_VSA4(mols) for mols in mols]\n", " EState_VSA5 = [Chem.EState.EState_VSA.EState_VSA5(mols) for mols in mols]\n", " EState_VSA6 = [Chem.EState.EState_VSA.EState_VSA6(mols) for mols in mols]\n", " EState_VSA7 = [Chem.EState.EState_VSA.EState_VSA7(mols) for mols in mols]\n", " EState_VSA8 = [Chem.EState.EState_VSA.EState_VSA8(mols) for mols in mols]\n", " EState_VSA9 = [Chem.EState.EState_VSA.EState_VSA9(mols) for mols in mols]\n", " EState_VSA10 = [Chem.EState.EState_VSA.EState_VSA10(mols) for mols in mols]\n", " EState_VSA11 = [Chem.EState.EState_VSA.EState_VSA11(mols) for mols in mols]\n", " EState_VSA1 = np.asarray(EState_VSA1).astype('float')\n", " EState_VSA2 = np.asarray(EState_VSA2).astype('float')\n", " EState_VSA3 = np.asarray(EState_VSA3).astype('float')\n", " EState_VSA4 = np.asarray(EState_VSA4).astype('float')\n", " EState_VSA5 = np.asarray(EState_VSA5).astype('float')\n", " EState_VSA6 = np.asarray(EState_VSA6).astype('float')\n", " EState_VSA7 = np.asarray(EState_VSA7).astype('float')\n", " EState_VSA8 = np.asarray(EState_VSA8).astype('float')\n", " EState_VSA9 = np.asarray(EState_VSA9).astype('float')\n", " EState_VSA10 = np.asarray(EState_VSA10).astype('float')\n", " EState_VSA11 = np.asarray(EState_VSA11).astype('float')\n", " fps = np.concatenate([fps,EState_VSA1[:,None],\n", " EState_VSA2[:,None],\n", " EState_VSA3[:,None],\n", " EState_VSA4[:,None],\n", " EState_VSA5[:,None],\n", " EState_VSA6[:,None],\n", " EState_VSA7[:,None],\n", " EState_VSA8[:,None],\n", " EState_VSA9[:,None],\n", " EState_VSA10[:,None],\n", " EState_VSA11[:,None]], axis=1)\n", " del EState_VSA1,EState_VSA2,EState_VSA3,EState_VSA4,EState_VSA5,EState_VSA6,EState_VSA7,EState_VSA8,EState_VSA9,EState_VSA10,EState_VSA11\n", " ########\n", " if phase33 == 1:\n", " VSA_EState1 = [Chem.EState.EState_VSA.VSA_EState1(mols) for mols in mols]\n", " VSA_EState2 = [Chem.EState.EState_VSA.VSA_EState2(mols) for mols in mols]\n", " VSA_EState3 = [Chem.EState.EState_VSA.VSA_EState3(mols) for mols in mols]\n", " VSA_EState4 = [Chem.EState.EState_VSA.VSA_EState4(mols) for mols in mols]\n", " VSA_EState5 = [Chem.EState.EState_VSA.VSA_EState5(mols) for mols in mols]\n", " VSA_EState6 = [Chem.EState.EState_VSA.VSA_EState6(mols) for mols in mols]\n", " VSA_EState7 = [Chem.EState.EState_VSA.VSA_EState7(mols) for mols in mols]\n", " VSA_EState8 = [Chem.EState.EState_VSA.VSA_EState8(mols) for mols in mols]\n", " VSA_EState9 = [Chem.EState.EState_VSA.VSA_EState9(mols) for mols in mols]\n", " VSA_EState10 = [Chem.EState.EState_VSA.VSA_EState10(mols) for mols in mols]\n", " VSA_EState1 = np.asarray(VSA_EState1).astype('float')\n", " VSA_EState2 = np.asarray(VSA_EState2).astype('float')\n", " VSA_EState3 = np.asarray(VSA_EState3).astype('float')\n", " VSA_EState4 = np.asarray(VSA_EState4).astype('float')\n", " VSA_EState5 = np.asarray(VSA_EState5).astype('float')\n", " VSA_EState6 = np.asarray(VSA_EState6).astype('float')\n", " VSA_EState7 = np.asarray(VSA_EState7).astype('float')\n", " VSA_EState8 = np.asarray(VSA_EState8).astype('float')\n", " VSA_EState9 = np.asarray(VSA_EState9).astype('float')\n", " VSA_EState10 = np.asarray(VSA_EState10).astype('float')\n", " fps = np.concatenate([fps,VSA_EState1[:,None],\n", " VSA_EState2[:,None],\n", " VSA_EState3[:,None],\n", " VSA_EState4[:,None],\n", " VSA_EState5[:,None],\n", " VSA_EState6[:,None],\n", " VSA_EState7[:,None],\n", " VSA_EState8[:,None],\n", " VSA_EState9[:,None],\n", " VSA_EState10[:,None]], axis=1)\n", " del VSA_EState1,VSA_EState2,VSA_EState3,VSA_EState4,VSA_EState5,VSA_EState6,VSA_EState7,VSA_EState8,VSA_EState9,VSA_EState10\n", " #######################################################\n", " #######################################################\n", " # 3D Descriptors\n", " #\n", " # mol3d2=mol3d_conv(mols)\n", " mol3d=mol3d_conv2(mols)\n", " #######################################################\n", " #######################################################\n", " if phase34 == 1:\n", " descriptor = [Chem.rdMolDescriptors.CalcAsphericity(mol3d) for mol3d in mol3d]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor\n", " if phase35 == 1:\n", " descriptor = conformer_idf(Chem.rdMolDescriptors.CalcPBF,mol3d)\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor\n", " if phase36 == 1:\n", " pmi1 = [Chem.rdMolDescriptors.CalcPMI1(mol3d) for mol3d in mol3d]\n", " pmi2 = [Chem.rdMolDescriptors.CalcPMI2(mol3d) for mol3d in mol3d]\n", " pmi3 = [Chem.rdMolDescriptors.CalcPMI3(mol3d) for mol3d in mol3d]\n", " pmi1 = np.asarray(pmi1).astype('float')\n", " pmi2 = np.asarray(pmi2).astype('float')\n", " pmi3 = np.asarray(pmi3).astype('float')\n", " pmi1 = np.log1p(pmi1)\n", " pmi1 = np.nan_to_num(pmi1, nan=0.0)\n", " pmi2 = np.log1p(pmi2)\n", " pmi2 = np.nan_to_num(pmi2, nan=0.0)\n", " pmi3 = np.log1p(pmi3)\n", " pmi3 = np.nan_to_num(pmi3, nan=0.0)\n", " fps = np.concatenate([fps,pmi1[:,None],pmi2[:,None],pmi3[:,None]], axis=1)\n", " del pmi1,pmi2,pmi3\n", " if phase37 == 1:\n", " npr1 = [Chem.rdMolDescriptors.CalcNPR1(mol3d) for mol3d in mol3d]\n", " npr2 = [Chem.rdMolDescriptors.CalcNPR2(mol3d) for mol3d in mol3d]\n", " npr1 = np.asarray(npr1).astype('float')\n", " npr2 = np.asarray(npr2).astype('float')\n", " fps = np.concatenate([fps,npr1[:,None],npr2[:,None]], axis=1)\n", " del npr1,npr2 \n", " if phase38 == 1:\n", " descriptor = [Chem.rdMolDescriptors.CalcRadiusOfGyration(mol3d) for mol3d in mol3d]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor\n", " if phase39 == 1:\n", " descriptor = [Chem.rdMolDescriptors.CalcInertialShapeFactor(mol3d) for mol3d in mol3d]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor\n", " if phase40 == 1:\n", " descriptor = [Chem.rdMolDescriptors.CalcEccentricity(mol3d) for mol3d in mol3d]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor\n", " if phase41 == 1:\n", " descriptor = conformer_idf(Chem.rdMolDescriptors.CalcSpherocityIndex,mol3d)\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor[:,None]], axis=1)\n", " del descriptor\n", " if phase42 == 1:\n", " descriptor = [Chem.rdMolDescriptors.MQNs_(mols) for mols in mol3d]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor], axis=1)\n", " del descriptor\n", " if phase43 == 1:\n", " descriptor = [Chem.rdMolDescriptors.CalcAUTOCORR2D(mols) for mols in mol3d]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " descriptor = np.log1p(descriptor+0.0001)\n", " descriptor = np.nan_to_num(descriptor, nan=0)\n", " fps = np.concatenate([fps,descriptor], axis=1)\n", " del descriptor\n", " if phase44 == 1:\n", " descriptor = [Chem.rdMolDescriptors.CalcAUTOCORR3D(mols) for mols in mol3d]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " descriptor = np.log1p(descriptor+0.0001)\n", " descriptor = np.nan_to_num(descriptor, nan=0)\n", " fps = np.concatenate([fps,descriptor], axis=1)\n", " del descriptor\n", " if phase45 == 1:\n", " descriptor = [Chem.rdMolDescriptors.CalcRDF(mol3d) for mol3d in mol3d]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor], axis=1)\n", " del descriptor\n", " if phase46 == 1:\n", " try:\n", " descriptor = [Chem.rdMolDescriptors.BCUT2D(mols) for mols in mol3d]\n", " except ValueError as e:\n", " print(f\"BCUT2D is not working with {e}\")\n", " descriptor=[]\n", " for i in mol3d:\n", " try:\n", " descriptor.append(Chem.rdMolDescriptors.BCUT2D(i))\n", " except:\n", " print(f\"Error with : {Chem.MolToSmiles(i)}\")\n", " descriptor.append([0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0])\n", " descriptor = np.asarray(descriptor).astype('float')\n", " descriptor = np.log1p(descriptor+0.0001)\n", " descriptor = np.nan_to_num(descriptor, nan=0)\n", " fps = np.concatenate([fps,descriptor], axis=1)\n", " del descriptor\n", " if phase47 == 1:\n", " descriptor = [Chem.rdMolDescriptors.CalcMORSE(mol3d) for mol3d in mol3d]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " descriptor = np.log1p(descriptor+0.0001)\n", " descriptor = np.nan_to_num(descriptor, nan=0)\n", " fps = np.concatenate([fps,descriptor], axis=1)\n", " del descriptor\n", " if phase48 == 1:\n", " descriptor = [Chem.rdMolDescriptors.CalcWHIM(mol3d) for mol3d in mol3d]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " fps = np.concatenate([fps,descriptor], axis=1)\n", " del descriptor\n", " if phase49 == 1:\n", " descriptor = [Chem.rdMolDescriptors.CalcGETAWAY(mols) for mols in mol3d]\n", " descriptor = np.asarray(descriptor).astype('float')\n", " descriptor = np.log1p(descriptor+0.0001)\n", " descriptor = np.nan_to_num(descriptor, nan=0)\n", " fps = np.concatenate([fps,descriptor], axis=1)\n", " del descriptor\n", " fps = np.nan_to_num(fps, nan=0.0)\n", " return fps, _" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "ws_input_fea=[\n", " 1, #phase1 \"MolWeight\" \n", " 1, #phase2 \"Mol_MR\" \n", " 1, #phase3 \"Mol_TPSA\" \n", " 1, #phase4 \"Mol_logP\" \n", " 1, #phase5 \"RotatedBonds\" \n", " 1, #phase6 \"HeavyAtom\" \n", " 0, #phase7 \"numHAcceptor\" \n", " 0, #phase8 \"numHDoner\" \n", " 0, #phase9 \"numHeteroatom\" \n", " 1, #phase10 \"NumValenceElec\" \n", " 1, #phase11 \"NHOHCount\" \n", " 1, #phase12 \"NOCount\" \n", " 0, #phase13 \"Ringcount\" \n", " 1, #phase14 \"numAromaticR\" \n", " 0, #phase15 \"numSaturateR\" \n", " 0, #phase16 \"numAliphaticR\" \n", " 0, #phase17 \"LabuteASA\" \n", " 1, #phase18 \"BalabanJs\" \n", " 1, #phase19 \"BertzCTs\" \n", " 0, #phase20 \"ipc\", \n", " 0, #phase21 \"kappa_Series[1-3]\" \n", " 1, #phase22 \"Chi_Series[13]\" \n", " 1, #phase23 \"phi\" \n", " 0, #phase24 \"HallKierAlpha\" \n", " 0, #phase25 \"NumAmideBonds\" \n", " 1, #phase26 \"FractionCSP3\" \n", " 0, #phase27 \"NumSpiroAtoms\" \n", " 1, #phase28 \"NumBridgeheadAtoms\" \n", " 1, #phase29 \"PEOE_VSA_Series[1-14]\" \n", " 1, #phase30 \"SMR_VSA_Series[1-10]\" \n", " 0, #phase31 \"SlogP_VSA_Series[1-12]\" \n", " 1, #phase32 \"EState_VSA_Series[1-11]\" \n", " 0, #phase33 \"VSA_EState_Series[1-10]\" \n", " 0, #phase34 \"Asphericity\" \n", " 1, #phase35 \"PBF\" \n", " 1, #phase36 \"PMI_series[1-3]\" \n", " 0, #phase37 \"NPR_series[1-2]\" \n", " 0, #phase38 \"RadiusOfGyration\" \n", " 0, #phase39 \"InertialShapeFactor\" \n", " 1, #phase40 \"Eccentricity\" \n", " 0, #phase41 \"SpherocityIndex\" \n", " 0, #phase42 \"MQNs\" \n", " 0, #phase43 \"AUTOCORR2D\" \n", " 1, #phase44 \"BCUT2D\", \n", " 0, #phase45 \"AUTOCORR3D\" \n", " 1, #phase46 \"RDF\" \n", " 0, #phase47 \"MORSE\" \n", " 1, #phase48 \"WHIM\" \n", " 0, #phase49 \"GETAWAY\" \n", "]" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "de_input_fea=[\n", " 1, #phase1 \"MolWeight\"\n", " 1, #phase2 \"Mol_MR\"\n", " 1, #phase3 \"Mol_TPSA\"\n", " 1, #phase4 \"Mol_logP\"\n", " 0, #phase5 \"RotatedBonds\"\n", " 0, #phase6 \"HeavyAtom\"\n", " 1, #phase7 \"numHAcceptor\"\n", " 1, #phase8 \"numHDoner\"\n", " 0, #phase9 \"numHeteroatom\"\n", " 0, #phase10 \"NumValenceElec\"\n", " 1, #phase11 \"NHOHCount\"\n", " 0, #phase12 \"NOCount\"\n", " 0, #phase13 \"Ringcount\"\n", " 0, #phase14 \"numAromaticR\"\n", " 0, #phase15 \"numSaturateR\"\n", " 1, #phase16 \"numAliphaticR\"\n", " 1, #phase17 \"LabuteASA\"\n", " 1, #phase18 \"BalabanJs\"\n", " 1, #phase19 \"BertzCTs\"\n", " 1, #phase20 \"ipc\"\n", " 0, #phase21 \"kappa_Series[1-3]\"\n", " 0, #phase22 \"Chi_Series[13]\"\n", " 0, #phase23 \"phi\"\n", " 1, #phase24 \"HallKierAlpha\"\n", " 1, #phase25 \"NumAmideBonds\"\n", " 1, #phase26 \"FractionCSP3\"\n", " 1, #phase27 \"NumSpiroAtoms\"\n", " 0, #phase28 \"NumBridgeheadAtoms\"\n", " 1, #phase29 \"PEOE_VSA_Series[1-14]\"\n", " 1, #phase30 \"SMR_VSA_Series[1-10]\"\n", " 0, #phase31 \"SlogP_VSA_Series[1-12]\"\n", " 0, #phase32 \"EState_VSA_Series[1-11]\"\n", " 0, #phase33 \"VSA_EState_Series[1-10]\"\n", " 1, #phase34 \"Asphericity\"\n", " 0, #phase35 \"PBF\"\n", " 0, #phase36 \"PMI_series[1-3]\"\n", " 1, #phase37 \"NPR_series[1-2]\"\n", " 0, #phase38 \"RadiusOfGyration\"\n", " 0, #phase39 \"InertialShapeFactor\"\n", " 0, #phase40 \"Eccentricity\"\n", " 0, #phase41 \"SpherocityIndex\"\n", " 0, #phase42 \"MQNs\"\n", " 1, #phase43 \"AUTOCORR2D\"\n", " 1, #phase44 \"BCUT2D\"\n", " 0, #phase45 \"AUTOCORR3D\"\n", " 1, #phase46 \"RDF\"\n", " 0, #phase47 \"MORSE\"\n", " 1, #phase48 \"WHIM\"\n", " 0, #phase49 \"GETAWAY\"\n", "]" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "lo_input_fea=[\n", " 1, #phase1 \"MolWeight\"\n", " 1, #phase2 \"Mol_MR\"\n", " 1, #phase3 \"Mol_TPSA\"\n", " 1, #phase4 \"Mol_logP\"\n", " 1, #phase5 \"RotatedBonds\"\n", " 0, #phase6 \"HeavyAtom\"\n", " 0, #phase7 \"numHAcceptor\"\n", " 0, #phase8 \"numHDoner\"\n", " 1, #phase9 \"numHeteroatom\"\n", " 1, #phase10 \"NumValenceElec\"\n", " 1, #phase11 \"NHOHCount\"\n", " 1, #phase12 \"NOCount\"\n", " 0, #phase13 \"Ringcount\"\n", " 1, #phase14 \"numAromaticR\"\n", " 0, #phase15 \"numSaturateR\"\n", " 0, #phase16 \"numAliphaticR\"\n", " 0, #phase17 \"LabuteASA\"\n", " 1, #phase18 \"BalabanJs\"\n", " 0, #phase19 \"BertzCTs\"\n", " 0, #phase20 \"ipc\"\n", " 1, #phase21 \"kappa_Series[1-3]\"\n", " 0, #phase22 \"Chi_Series[13]\"\n", " 1, #phase23 \"phi\"\n", " 1, #phase24 \"HallKierAlpha\"\n", " 0, #phase25 \"NumAmideBonds\"\n", " 1, #phase26 \"FractionCSP3\"\n", " 1, #phase27 \"NumSpiroAtoms\"\n", " 0, #phase28 \"NumBridgeheadAtoms\"\n", " 1, #phase29 \"PEOE_VSA_Series[1-14]\"\n", " 1, #phase30 \"SMR_VSA_Series[1-10]\"\n", " 1, #phase31 \"SlogP_VSA_Series[1-12]\"\n", " 0, #phase32 \"EState_VSA_Series[1-11]\"\n", " 1, #phase33 \"VSA_EState_Series[1-10]\"\n", " 1, #phase34 \"Asphericity\"\n", " 0, #phase35 \"PBF\"\n", " 0, #phase36 \"PMI_series[1-3]\"\n", " 1, #phase37 \"NPR_series[1-2]\"\n", " 1, #phase38 \"RadiusOfGyration\"\n", " 0, #phase39 \"InertialShapeFactor\"\n", " 0, #phase40 \"Eccentricity\"\n", " 1, #phase41 \"SpherocityIndex\"\n", " 0, #phase42 \"MQNs\"\n", " 0, #phase43 \"AUTOCORR2D\"\n", " 0, #phase44 \"BCUT2D\"\n", " 0, #phase45 \"AUTOCORR3D\"\n", " 1, #phase46 \"RDF\"\n", " 0, #phase47 \"MORSE\"\n", " 0, #phase48 \"WHIM\"\n", " 0, #phase49 \"GETAWAY\"\n", "]" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "hu_input_fea=[\n", " 1, #phase1 \"MolWeight\"\n", " 1, #phase2 \"Mol_MR\"\n", " 1, #phase3 \"Mol_TPSA\"\n", " 1, #phase4 \"Mol_logP\"\n", " 0, #phase5 \"RotatedBonds\"\n", " 1, #phase6 \"HeavyAtom\"\n", " 0, #phase7 \"numHAcceptor\"\n", " 1, #phase8 \"numHDoner\"\n", " 1, #phase9 \"numHeteroatom\"\n", " 1, #phase10 \"NumValenceElec\"\n", " 0, #phase11 \"NHOHCount\"\n", " 1, #phase12 \"NOCount\"\n", " 1, #phase13 \"Ringcount\"\n", " 1, #phase14 \"numAromaticR\"\n", " 1, #phase15 \"numSaturateR\"\n", " 0, #phase16 \"numAliphaticR\"\n", " 0, #phase17 \"LabuteASA\"\n", " 1, #phase18 \"BalabanJs\"\n", " 1, #phase19 \"BertzCTs\"\n", " 1, #phase20 \"ipc\"\n", " 0, #phase21 \"kappa_Series[1-3]\"\n", " 1, #phase22 \"Chi_Series[13]\"\n", " 1, #phase23 \"phi\"\n", " 0, #phase24 \"HallKierAlpha\"\n", " 1, #phase25 \"NumAmideBonds\"\n", " 0, #phase26 \"FractionCSP3\"\n", " 1, #phase27 \"NumSpiroAtoms\"\n", " 0, #phase28 \"NumBridgeheadAtoms\"\n", " 1, #phase29 \"PEOE_VSA_Series[1-14]\"\n", " 1, #phase30 \"SMR_VSA_Series[1-10]\"\n", " 1, #phase31 \"SlogP_VSA_Series[1-12]\"\n", " 1, #phase32 \"EState_VSA_Series[1-11]\"\n", " 1, #phase33 \"VSA_EState_Series[1-10]\"\n", " 1, #phase34 \"Asphericity\"\n", " 1, #phase35 \"PBF\"\n", " 1, #phase36 \"PMI_series[1-3]\"\n", " 1, #phase37 \"NPR_series[1-2]\"\n", " 1, #phase38 \"RadiusOfGyration\"\n", " 1, #phase39 \"InertialShapeFactor\"\n", " 0, #phase40 \"Eccentricity\"\n", " 0, #phase41 \"SpherocityIndex\"\n", " 1, #phase42 \"MQNs\"\n", " 1, #phase43 \"AUTOCORR2D\"\n", " 1, #phase44 \"BCUT2D\"\n", " 1, #phase45 \"AUTOCORR3D\"\n", " 1, #phase46 \"RDF\"\n", " 0, #phase47 \"MORSE\"\n", " 0, #phase48 \"WHIM\"\n", " 0, #phase49 \"GETAWAY\"\n", "]" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "try:\n", " new_ws = pd.read_csv(\"new_ws_final.csv\").to_numpy()\n", " new_de = pd.read_csv(\"new_de_final.csv\").to_numpy()\n", " new_lo = pd.read_csv(\"new_lo_final.csv\").to_numpy()\n", " new_hu = pd.read_csv(\"new_hu_final.csv\").to_numpy()\n", " new_ws = np.nan_to_num(new_ws, nan=0.0)\n", " new_de = np.nan_to_num(new_de, nan=0.0)\n", " new_lo = np.nan_to_num(new_lo, nan=0.0)\n", " new_hu = np.nan_to_num(new_hu, nan=0.0)\n", "except:\n", " new_ws, pd_names_new_ws = search_data_origin(ws_input_fea, group_nws, mol_ws, 'ws')\n", " new_de, pd_names_new_de = search_data_origin(de_input_fea, group_nde, mol_de, 'de')\n", " new_lo, pd_names_new_lo = search_data_origin(lo_input_fea, group_nlo, mol_lo, 'lo')\n", " new_hu, pd_names_new_hu = search_data_origin(hu_input_fea, group_nhu, mol_hu, 'hu')\n", " pd.DataFrame(new_ws).to_csv(\"new_ws_final.csv\",index=False)\n", " pd.DataFrame(new_de).to_csv(\"new_de_final.csv\",index=False)\n", " pd.DataFrame(new_lo).to_csv(\"new_lo_final.csv\",index=False)\n", " pd.DataFrame(new_hu).to_csv(\"new_hu_final.csv\",index=False)\n", " new_ws = np.nan_to_num(new_ws, nan=0.0)\n", " new_de = np.nan_to_num(new_de, nan=0.0)\n", " new_lo = np.nan_to_num(new_lo, nan=0.0)\n", " new_hu = np.nan_to_num(new_hu, nan=0.0)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "BATCHSIZE = 16\n", "EPOCHS = 1000\n", "lr = 0.0001\n", "decay = 1e-4" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "def ws_model():\n", " decay = 1e-4\n", " model = tf.keras.Sequential()\n", " model.add(\n", " tf.keras.layers.Dense(\n", " 7897,\n", " activation=\"relu\",\n", " kernel_initializer='glorot_uniform',\n", " kernel_regularizer=tf.keras.regularizers.l2(decay),\n", " )\n", " )\n", " model.add(Dropout(rate=0.1))\n", " model.add(\n", " tf.keras.layers.Dense(\n", " 9994,\n", " activation=\"relu\",\n", " kernel_initializer='glorot_uniform',\n", " kernel_regularizer=tf.keras.regularizers.l2(decay),\n", " )\n", " )\n", " model.add(Dropout(rate=0.1))\n", " model.add(Dense(units=1))\n", " model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=lr), \n", " loss='mse', metrics=['mse', 'mae',tf.keras.metrics.RootMeanSquaredError()])\n", " return model" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "def de_model():\n", " decay = 1e-4\n", " model = tf.keras.Sequential()\n", " model.add(\n", " tf.keras.layers.Dense(\n", " 4882,\n", " activation=\"relu\",\n", " kernel_initializer='glorot_uniform',\n", " kernel_regularizer=tf.keras.regularizers.l2(decay),\n", " )\n", " )\n", " model.add(Dropout(rate=0.1))\n", " model.add(Dense(units=1))\n", " model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=lr), \n", " loss='mse', metrics=['mse', 'mae',tf.keras.metrics.RootMeanSquaredError()])\n", " return model" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "def lo_model():\n", " decay = 1e-5\n", " model = tf.keras.Sequential()\n", " model.add(\n", " tf.keras.layers.Dense(\n", " 6365,\n", " activation=\"relu\",\n", " kernel_initializer='glorot_uniform',\n", " kernel_regularizer=tf.keras.regularizers.l2(decay),\n", " )\n", " )\n", " model.add(Dropout(rate=0.1))\n", " model.add(\n", " tf.keras.layers.Dense(\n", " 9298,\n", " activation=\"relu\",\n", " kernel_initializer='glorot_uniform',\n", " kernel_regularizer=tf.keras.regularizers.l2(decay),\n", " )\n", " )\n", " model.add(Dropout(rate=0.1))\n", " model.add(Dense(units=1))\n", " model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=lr), \n", " loss='mse', metrics=['mse', 'mae',tf.keras.metrics.RootMeanSquaredError()])\n", " return model" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "def hu_model():\n", " decay1 = 1e-4\n", " model = tf.keras.Sequential()\n", " model.add(\n", " tf.keras.layers.Dense(\n", " 6325,\n", " activation=\"relu\",\n", " kernel_initializer='glorot_uniform',\n", " kernel_regularizer=tf.keras.regularizers.l2(decay1),\n", " )\n", " )\n", " model.add(Dropout(rate=0.1))\n", " model.add(Dense(units=1))\n", " model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=lr), \n", " loss='mse', metrics=['mse', 'mae',tf.keras.metrics.RootMeanSquaredError()])\n", " return model" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "xtr_fws, xte_fws, ytr_fws, yte_fws = train_test_split(new_ws, y_ws_nponly, test_size = 0.1, random_state = 42)\n", "xtr_fde, xte_fde, ytr_fde, yte_fde = train_test_split(new_de, y_de_nponly, test_size = 0.1, random_state = 42)\n", "xtr_flo, xte_flo, ytr_flo, yte_flo = train_test_split(new_lo, y_lo_nponly, test_size = 0.1, random_state = 42)\n", "xtr_fhu, xte_fhu, ytr_fhu, yte_fhu = train_test_split(new_hu, y_hu_nponly, test_size = 0.1, random_state = 42)" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "ws_url = \"./save_model/{}_model_{}batch_{}epoch_{}lr.h5\".format('ws',BATCHSIZE,EPOCHS,lr)\n", "de_url = \"./save_model/{}_model_{}batch_{}epoch_{}lr.h5\".format('de',BATCHSIZE,EPOCHS,lr)\n", "lo_url = \"./save_model/{}_model_{}batch_{}epoch_{}lr.h5\".format('lo',BATCHSIZE,EPOCHS,lr)\n", "hu_url = \"./save_model/{}_model_{}batch_{}epoch_{}lr.h5\".format('hu',BATCHSIZE,EPOCHS,lr)" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "cp_ws = tf.keras.callbacks.ModelCheckpoint(ws_url,monitor='val_loss',verbose=1, mode='auto') #,save_best_only=True)\n", "cp_de = tf.keras.callbacks.ModelCheckpoint(de_url,monitor='val_loss',verbose=1, mode='auto') #,save_best_only=True)\n", "cp_lo = tf.keras.callbacks.ModelCheckpoint(lo_url,monitor='val_loss',verbose=1, mode='auto') #,save_best_only=True)\n", "cp_hu = tf.keras.callbacks.ModelCheckpoint(hu_url,monitor='val_loss',verbose=1, mode='auto') #,save_best_only=True)" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "# cb = tf.keras.callbacks.EarlyStopping(\n", "# monitor=\"val_loss\",\n", "# patience=200,\n", "# verbose=0,\n", "# mode=\"auto\"\n", "# )" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "reading...ws\n", "ws_model : \n", "Finished...ws\n", "\n", "reading...de\n", "de_model : \n", "Finished...de\n", "\n", "reading...lo\n", "de_model : \n", "Finished...lo\n", "\n" ] } ], "source": [ "try:\n", " print(f\"reading...ws\")\n", " model_fws1 = tf.keras.models.load_model(ws_url)\n", " print(f\"ws_model : {model_fws1}\")\n", " print(f\"Finished...ws\\n\")\n", "except:\n", " print(f\"Creating...ws\")\n", " model_fws1 = hu_model()\n", " print(f\"Finished...ws\\n\")\n", "####################################################\n", "####################################################\n", "####################################################\n", "try:\n", " print(f\"reading...de\")\n", " model_fde1 = tf.keras.models.load_model(de_url)\n", " print(f\"de_model : {model_fde1}\")\n", " print(f\"Finished...de\\n\")\n", "except:\n", " print(f\"Creating...de\")\n", " model_fde1 = hu_model()\n", " print(f\"Finished...de\\n\")\n", "####################################################\n", "####################################################\n", "####################################################\n", "try:\n", " print(f\"reading...lo\")\n", " model_flo1 = tf.keras.models.load_model(lo_url)\n", " print(f\"de_model : {model_flo1}\")\n", " print(f\"Finished...lo\\n\")\n", "except:\n", " print(f\"Creating...lo\")\n", " model_flo1 = lo_model()\n", " print(f\"Finished...lo\\n\")\n", "####################################################\n", "####################################################\n", "####################################################\n", "# try:\n", "# print(f\"reading...hu\")\n", "# model_fhu1 = tf.keras.models.load_model(hu_url)\n", "# print(f\"lo_model : {model_fhu1}\")\n", "# print(f\"Finished...hu\\n\")\n", "# except:\n", "# print(f\"Creating...hu\")\n", "# model_fhu1 = hu_model()\n", "# print(f\"Finished...hu\\n\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "ws r2 score : 0.9163043268412985\n" ] }, { "data": { "text/plain": [ "650" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# tf.keras.backend.clear_session() \n", "# model_fws1 = ws_model()\n", "# model_fws1.fit(xtr_fws,ytr_fws,\n", "# batch_size=BATCHSIZE,\n", "# callbacks=[cp_ws],\n", "# validation_split=0.1,\n", "# epochs=EPOCHS,\n", "# verbose=1,\n", "# )\n", "# model_fws1.save(f'./save_model/ws_manual_save_model_{BATCHSIZE}batch_{EPOCHS}epochs_{lr}lr.h5')\n", "y_pred_search = model_fws1.predict(xte_fws, verbose=0)\n", "score = r2_score(yte_fws, y_pred_search)\n", "print(f\"ws r2 score : {score}\")\n", "gc.collect()\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "de r2 score : 0.990616653856253\n" ] }, { "data": { "text/plain": [ "655" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# tf.keras.backend.clear_session()\n", "# model_fde1.fit(xtr_fde,ytr_fde,\n", "# batch_size=BATCHSIZE,\n", "# callbacks=[cp_de],\n", "# validation_split=0.1,\n", "# epochs=EPOCHS,\n", "# verbose=1,\n", "# )\n", "# model_fde1.save(f'./save_model/de_manual_save_model_{BATCHSIZE}batch_{EPOCHS}epochs_{lr}lr.h5')\n", "y_pred_search = model_fde1.predict(xte_fde, verbose=0)\n", "y_pred_search= np.nan_to_num(y_pred_search, nan=0.0)\n", "score = r2_score(yte_fde, y_pred_search)\n", "print(f\"de r2 score : {score}\")\n", "gc.collect()" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "lo r2 score : 0.7896706466730885\n" ] }, { "data": { "text/plain": [ "650" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "y_pred_search = model_flo1.predict(xte_flo, verbose=0)\n", "score = r2_score(yte_flo, y_pred_search)\n", "print(f\"lo r2 score : {score}\")\n", "gc.collect()" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "# print(f\"reading...hu\")\n", "# model_fhu1 = tf.keras.models.load_model(hu_url)\n", "# print(f\"lo_model : {model_fhu1}\")\n", "# print(f\"Finished...hu\\n\")" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": [ "# y_pred_search = model_fhu1.predict(xte_fhu, verbose=0)\n", "# score = r2_score(yte_fhu, y_pred_search)\n", "# print(f\"hu r2 score : {score}\")\n", "# gc.collect()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# tf.keras.backend.clear_session()\n", "# model_flo1.fit(xtr_flo,ytr_flo,\n", "# batch_size=BATCHSIZE,\n", "# callbacks=[cp_lo],\n", "# validation_split=0.1,\n", "# epochs=EPOCHS,\n", "# verbose=1,\n", "# )\n", "# model_flo1.save(f'./save_model/lo_manual_save_model_{BATCHSIZE}batch_{lr}lr.h5')\n", "# y_pred_search = model_flo1.predict(xte_flo, verbose=0)\n", "# score = r2_score(yte_flo, y_pred_search)\n", "# print(f\"lo r2 score : {score}\")\n", "# gc.collect()" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": [ "EPOCHS=1000" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [], "source": [ "model_fhu1 = hu_model()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 1/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 19.5670 - mse: 19.1929 - mae: 3.0793 - root_mean_squared_error: 4.3810\n", "Epoch 1: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 38ms/step - loss: 19.5465 - mse: 19.1729 - mae: 3.0803 - root_mean_squared_error: 4.3787 - val_loss: 10.6566 - val_mse: 10.3322 - val_mae: 1.9357 - val_root_mean_squared_error: 3.2144\n", "Epoch 2/1000\n", "73/73 [==============================] - ETA: 0s - loss: 14.2646 - mse: 13.9659 - mae: 2.5667 - root_mean_squared_error: 3.7371\n", "Epoch 2: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 53ms/step - loss: 14.2646 - mse: 13.9659 - mae: 2.5667 - root_mean_squared_error: 3.7371 - val_loss: 3.4258 - val_mse: 3.1474 - val_mae: 1.2274 - val_root_mean_squared_error: 1.7741\n", "Epoch 3/1000\n", "73/73 [==============================] - ETA: 0s - loss: 12.8046 - mse: 12.5369 - mae: 2.4064 - root_mean_squared_error: 3.5408\n", "Epoch 3: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 34ms/step - loss: 12.8046 - mse: 12.5369 - mae: 2.4064 - root_mean_squared_error: 3.5408 - val_loss: 10.8817 - val_mse: 10.6223 - val_mae: 2.5679 - val_root_mean_squared_error: 3.2592\n", "Epoch 4/1000\n", "73/73 [==============================] - ETA: 0s - loss: 15.4897 - mse: 15.2345 - mae: 2.6870 - root_mean_squared_error: 3.9031\n", "Epoch 4: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 32ms/step - loss: 15.4897 - mse: 15.2345 - mae: 2.6870 - root_mean_squared_error: 3.9031 - val_loss: 9.0343 - val_mse: 8.7823 - val_mae: 1.8013 - val_root_mean_squared_error: 2.9635\n", "Epoch 5/1000\n", "73/73 [==============================] - ETA: 0s - loss: 22.6574 - mse: 22.4069 - mae: 2.9008 - root_mean_squared_error: 4.7336\n", "Epoch 5: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 22.6574 - mse: 22.4069 - mae: 2.9008 - root_mean_squared_error: 4.7336 - val_loss: 2.1114 - val_mse: 1.8622 - val_mae: 0.9561 - val_root_mean_squared_error: 1.3646\n", "Epoch 6/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 15.8459 - mse: 15.5974 - mae: 2.4468 - root_mean_squared_error: 3.9494\n", "Epoch 6: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 15.8278 - mse: 15.5793 - mae: 2.4461 - root_mean_squared_error: 3.9471 - val_loss: 2.8430 - val_mse: 2.5951 - val_mae: 1.0782 - val_root_mean_squared_error: 1.6109\n", "Epoch 7/1000\n", "73/73 [==============================] - ETA: 0s - loss: 12.7850 - mse: 12.5376 - mae: 2.2861 - root_mean_squared_error: 3.5408\n", "Epoch 7: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 12.7850 - mse: 12.5376 - mae: 2.2861 - root_mean_squared_error: 3.5408 - val_loss: 5.4713 - val_mse: 5.2243 - val_mae: 1.7011 - val_root_mean_squared_error: 2.2857\n", "Epoch 8/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 12.2220 - mse: 11.9755 - mae: 2.3434 - root_mean_squared_error: 3.4606\n", "Epoch 8: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 31ms/step - loss: 12.1527 - mse: 11.9061 - mae: 2.3351 - root_mean_squared_error: 3.4505 - val_loss: 29.9002 - val_mse: 29.6541 - val_mae: 3.4525 - val_root_mean_squared_error: 5.4456\n", "Epoch 9/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 14.6742 - mse: 14.4284 - mae: 2.5093 - root_mean_squared_error: 3.7985\n", "Epoch 9: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 32ms/step - loss: 14.6009 - mse: 14.3551 - mae: 2.5038 - root_mean_squared_error: 3.7888 - val_loss: 4.3996 - val_mse: 4.1542 - val_mae: 1.4885 - val_root_mean_squared_error: 2.0382\n", "Epoch 10/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 11.3150 - mse: 11.0700 - mae: 2.0697 - root_mean_squared_error: 3.3272\n", "Epoch 10: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 31ms/step - loss: 11.3328 - mse: 11.0877 - mae: 2.0763 - root_mean_squared_error: 3.3298 - val_loss: 9.0591 - val_mse: 8.8144 - val_mae: 1.9003 - val_root_mean_squared_error: 2.9689\n", "Epoch 11/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 9.8678 - mse: 9.6235 - mae: 2.0712 - root_mean_squared_error: 3.1022 \n", "Epoch 11: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 34ms/step - loss: 9.8517 - mse: 9.6073 - mae: 2.0726 - root_mean_squared_error: 3.0996 - val_loss: 5.2409 - val_mse: 4.9970 - val_mae: 1.6875 - val_root_mean_squared_error: 2.2354\n", "Epoch 12/1000\n", "73/73 [==============================] - ETA: 0s - loss: 10.4730 - mse: 10.2294 - mae: 2.1692 - root_mean_squared_error: 3.1983\n", "Epoch 12: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 32ms/step - loss: 10.4730 - mse: 10.2294 - mae: 2.1692 - root_mean_squared_error: 3.1983 - val_loss: 1.6288 - val_mse: 1.3856 - val_mae: 0.8909 - val_root_mean_squared_error: 1.1771\n", "Epoch 13/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 8.0089 - mse: 7.7661 - mae: 1.9368 - root_mean_squared_error: 2.7868\n", "Epoch 13: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 8.0136 - mse: 7.7708 - mae: 1.9407 - root_mean_squared_error: 2.7876 - val_loss: 1.6667 - val_mse: 1.4244 - val_mae: 0.9417 - val_root_mean_squared_error: 1.1935\n", "Epoch 14/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 6.3779 - mse: 6.1360 - mae: 1.7027 - root_mean_squared_error: 2.4771\n", "Epoch 14: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 6.4447 - mse: 6.2028 - mae: 1.7091 - root_mean_squared_error: 2.4905 - val_loss: 6.6548 - val_mse: 6.4133 - val_mae: 1.8595 - val_root_mean_squared_error: 2.5325\n", "Epoch 15/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 6.5527 - mse: 6.3116 - mae: 1.7110 - root_mean_squared_error: 2.5123\n", "Epoch 15: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 33ms/step - loss: 6.5156 - mse: 6.2745 - mae: 1.7051 - root_mean_squared_error: 2.5049 - val_loss: 1.9997 - val_mse: 1.7590 - val_mae: 0.9954 - val_root_mean_squared_error: 1.3263\n", "Epoch 16/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 8.6147 - mse: 8.3745 - mae: 1.9606 - root_mean_squared_error: 2.8939\n", "Epoch 16: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 8.6038 - mse: 8.3635 - mae: 1.9622 - root_mean_squared_error: 2.8920 - val_loss: 4.5803 - val_mse: 4.3404 - val_mae: 1.5300 - val_root_mean_squared_error: 2.0834\n", "Epoch 17/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 8.3032 - mse: 8.0637 - mae: 1.9017 - root_mean_squared_error: 2.8397\n", "Epoch 17: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 8.2153 - mse: 7.9758 - mae: 1.8924 - root_mean_squared_error: 2.8241 - val_loss: 4.0284 - val_mse: 3.7893 - val_mae: 1.4032 - val_root_mean_squared_error: 1.9466\n", "Epoch 18/1000\n", "73/73 [==============================] - ETA: 0s - loss: 8.0175 - mse: 7.7789 - mae: 1.8677 - root_mean_squared_error: 2.7891\n", "Epoch 18: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 8.0175 - mse: 7.7789 - mae: 1.8677 - root_mean_squared_error: 2.7891 - val_loss: 4.1404 - val_mse: 3.9022 - val_mae: 1.6219 - val_root_mean_squared_error: 1.9754\n", "Epoch 19/1000\n", "73/73 [==============================] - ETA: 0s - loss: 23.6595 - mse: 23.4215 - mae: 3.1193 - root_mean_squared_error: 4.8396\n", "Epoch 19: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 23.6595 - mse: 23.4215 - mae: 3.1193 - root_mean_squared_error: 4.8396 - val_loss: 2.9833 - val_mse: 2.7455 - val_mae: 1.3347 - val_root_mean_squared_error: 1.6569\n", "Epoch 20/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 12.9314 - mse: 12.6939 - mae: 2.2009 - root_mean_squared_error: 3.5628\n", "Epoch 20: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 34ms/step - loss: 12.8723 - mse: 12.6348 - mae: 2.1966 - root_mean_squared_error: 3.5545 - val_loss: 1.1906 - val_mse: 0.9535 - val_mae: 0.7198 - val_root_mean_squared_error: 0.9765\n", "Epoch 21/1000\n", "73/73 [==============================] - ETA: 0s - loss: 10.8808 - mse: 10.6442 - mae: 2.0461 - root_mean_squared_error: 3.2625\n", "Epoch 21: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 10.8808 - mse: 10.6442 - mae: 2.0461 - root_mean_squared_error: 3.2625 - val_loss: 2.9139 - val_mse: 2.6777 - val_mae: 1.1507 - val_root_mean_squared_error: 1.6364\n", "Epoch 22/1000\n", "73/73 [==============================] - ETA: 0s - loss: 9.1731 - mse: 8.9373 - mae: 1.8359 - root_mean_squared_error: 2.9895\n", "Epoch 22: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 9.1731 - mse: 8.9373 - mae: 1.8359 - root_mean_squared_error: 2.9895 - val_loss: 2.9157 - val_mse: 2.6802 - val_mae: 1.1760 - val_root_mean_squared_error: 1.6371\n", "Epoch 23/1000\n", "73/73 [==============================] - ETA: 0s - loss: 7.5726 - mse: 7.3375 - mae: 1.6591 - root_mean_squared_error: 2.7088\n", "Epoch 23: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 33ms/step - loss: 7.5726 - mse: 7.3375 - mae: 1.6591 - root_mean_squared_error: 2.7088 - val_loss: 7.4275 - val_mse: 7.1929 - val_mae: 2.2656 - val_root_mean_squared_error: 2.6820\n", "Epoch 24/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 5.5598 - mse: 5.3256 - mae: 1.5361 - root_mean_squared_error: 2.3077\n", "Epoch 24: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 61ms/step - loss: 5.5521 - mse: 5.3180 - mae: 1.5381 - root_mean_squared_error: 2.3061 - val_loss: 2.2349 - val_mse: 2.0013 - val_mae: 1.0905 - val_root_mean_squared_error: 1.4147\n", "Epoch 25/1000\n", "73/73 [==============================] - ETA: 0s - loss: 5.2782 - mse: 5.0450 - mae: 1.5128 - root_mean_squared_error: 2.2461\n", "Epoch 25: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 5.2782 - mse: 5.0450 - mae: 1.5128 - root_mean_squared_error: 2.2461 - val_loss: 2.1962 - val_mse: 1.9635 - val_mae: 0.9176 - val_root_mean_squared_error: 1.4012\n", "Epoch 26/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 5.2933 - mse: 5.0610 - mae: 1.4957 - root_mean_squared_error: 2.2497\n", "Epoch 26: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 5.2804 - mse: 5.0481 - mae: 1.4952 - root_mean_squared_error: 2.2468 - val_loss: 1.2571 - val_mse: 1.0252 - val_mae: 0.7604 - val_root_mean_squared_error: 1.0125\n", "Epoch 27/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 5.8805 - mse: 5.6491 - mae: 1.5217 - root_mean_squared_error: 2.3768\n", "Epoch 27: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 5.8658 - mse: 5.6343 - mae: 1.5191 - root_mean_squared_error: 2.3737 - val_loss: 1.9513 - val_mse: 1.7203 - val_mae: 1.0555 - val_root_mean_squared_error: 1.3116\n", "Epoch 28/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 3.6454 - mse: 3.4148 - mae: 1.2302 - root_mean_squared_error: 1.8479\n", "Epoch 28: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 3.6231 - mse: 3.3925 - mae: 1.2242 - root_mean_squared_error: 1.8419 - val_loss: 1.3612 - val_mse: 1.1311 - val_mae: 0.7986 - val_root_mean_squared_error: 1.0635\n", "Epoch 29/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 7.2311 - mse: 7.0014 - mae: 1.7745 - root_mean_squared_error: 2.6460\n", "Epoch 29: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 7.2409 - mse: 7.0112 - mae: 1.7774 - root_mean_squared_error: 2.6479 - val_loss: 1.6709 - val_mse: 1.4415 - val_mae: 0.9757 - val_root_mean_squared_error: 1.2006\n", "Epoch 30/1000\n", "73/73 [==============================] - ETA: 0s - loss: 4.2927 - mse: 4.0639 - mae: 1.3603 - root_mean_squared_error: 2.0159\n", "Epoch 30: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 4.2927 - mse: 4.0639 - mae: 1.3603 - root_mean_squared_error: 2.0159 - val_loss: 2.3099 - val_mse: 2.0815 - val_mae: 1.0327 - val_root_mean_squared_error: 1.4428\n", "Epoch 31/1000\n", "73/73 [==============================] - ETA: 0s - loss: 3.8017 - mse: 3.5737 - mae: 1.2876 - root_mean_squared_error: 1.8904\n", "Epoch 31: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 3.8017 - mse: 3.5737 - mae: 1.2876 - root_mean_squared_error: 1.8904 - val_loss: 1.4802 - val_mse: 1.2527 - val_mae: 0.8003 - val_root_mean_squared_error: 1.1192\n", "Epoch 32/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 3.9039 - mse: 3.6768 - mae: 1.3233 - root_mean_squared_error: 1.9175\n", "Epoch 32: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 3.9041 - mse: 3.6770 - mae: 1.3245 - root_mean_squared_error: 1.9176 - val_loss: 2.8675 - val_mse: 2.6409 - val_mae: 1.3399 - val_root_mean_squared_error: 1.6251\n", "Epoch 33/1000\n", "73/73 [==============================] - ETA: 0s - loss: 2.7441 - mse: 2.5179 - mae: 1.0723 - root_mean_squared_error: 1.5868\n", "Epoch 33: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 2.7441 - mse: 2.5179 - mae: 1.0723 - root_mean_squared_error: 1.5868 - val_loss: 3.4451 - val_mse: 3.2193 - val_mae: 1.4583 - val_root_mean_squared_error: 1.7943\n", "Epoch 34/1000\n", "73/73 [==============================] - ETA: 0s - loss: 2.9559 - mse: 2.7306 - mae: 1.1055 - root_mean_squared_error: 1.6525\n", "Epoch 34: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 2.9559 - mse: 2.7306 - mae: 1.1055 - root_mean_squared_error: 1.6525 - val_loss: 1.1524 - val_mse: 0.9277 - val_mae: 0.7758 - val_root_mean_squared_error: 0.9632\n", "Epoch 35/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 2.8712 - mse: 2.6468 - mae: 1.1096 - root_mean_squared_error: 1.6269\n", "Epoch 35: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 60ms/step - loss: 2.8672 - mse: 2.6429 - mae: 1.1089 - root_mean_squared_error: 1.6257 - val_loss: 4.5183 - val_mse: 4.2945 - val_mae: 1.6894 - val_root_mean_squared_error: 2.0723\n", "Epoch 36/1000\n", "73/73 [==============================] - ETA: 0s - loss: 3.4662 - mse: 3.2428 - mae: 1.2568 - root_mean_squared_error: 1.8008\n", "Epoch 36: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 3.4662 - mse: 3.2428 - mae: 1.2568 - root_mean_squared_error: 1.8008 - val_loss: 1.6763 - val_mse: 1.4534 - val_mae: 0.8899 - val_root_mean_squared_error: 1.2056\n", "Epoch 37/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 2.4659 - mse: 2.2433 - mae: 1.0270 - root_mean_squared_error: 1.4978\n", "Epoch 37: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 2.4582 - mse: 2.2357 - mae: 1.0269 - root_mean_squared_error: 1.4952 - val_loss: 1.7789 - val_mse: 1.5569 - val_mae: 0.8971 - val_root_mean_squared_error: 1.2478\n", "Epoch 38/1000\n", "73/73 [==============================] - ETA: 0s - loss: 2.8334 - mse: 2.6119 - mae: 1.1235 - root_mean_squared_error: 1.6161\n", "Epoch 38: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 2.8334 - mse: 2.6119 - mae: 1.1235 - root_mean_squared_error: 1.6161 - val_loss: 3.1576 - val_mse: 2.9365 - val_mae: 1.1195 - val_root_mean_squared_error: 1.7136\n", "Epoch 39/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 4.7138 - mse: 4.4932 - mae: 1.3916 - root_mean_squared_error: 2.1197\n", "Epoch 39: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 4.7126 - mse: 4.4920 - mae: 1.3947 - root_mean_squared_error: 2.1194 - val_loss: 1.2591 - val_mse: 1.0390 - val_mae: 0.8087 - val_root_mean_squared_error: 1.0193\n", "Epoch 40/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 3.6973 - mse: 3.4776 - mae: 1.1124 - root_mean_squared_error: 1.8648\n", "Epoch 40: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 3.7689 - mse: 3.5492 - mae: 1.1259 - root_mean_squared_error: 1.8839 - val_loss: 18.2145 - val_mse: 17.9952 - val_mae: 3.3777 - val_root_mean_squared_error: 4.2421\n", "Epoch 41/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 8.1234 - mse: 7.9045 - mae: 1.7329 - root_mean_squared_error: 2.8115\n", "Epoch 41: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 60ms/step - loss: 8.0741 - mse: 7.8552 - mae: 1.7279 - root_mean_squared_error: 2.8027 - val_loss: 3.9510 - val_mse: 3.7325 - val_mae: 1.4589 - val_root_mean_squared_error: 1.9320\n", "Epoch 42/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 4.7139 - mse: 4.4958 - mae: 1.2875 - root_mean_squared_error: 2.1203\n", "Epoch 42: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 4.6868 - mse: 4.4687 - mae: 1.2836 - root_mean_squared_error: 2.1139 - val_loss: 1.7301 - val_mse: 1.5125 - val_mae: 0.8059 - val_root_mean_squared_error: 1.2298\n", "Epoch 43/1000\n", "73/73 [==============================] - ETA: 0s - loss: 3.3533 - mse: 3.1360 - mae: 1.0472 - root_mean_squared_error: 1.7709\n", "Epoch 43: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 3.3533 - mse: 3.1360 - mae: 1.0472 - root_mean_squared_error: 1.7709 - val_loss: 8.0395 - val_mse: 7.8227 - val_mae: 2.3360 - val_root_mean_squared_error: 2.7969\n", "Epoch 44/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 6.3787 - mse: 6.1623 - mae: 1.5169 - root_mean_squared_error: 2.4824\n", "Epoch 44: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 6.3375 - mse: 6.1212 - mae: 1.5099 - root_mean_squared_error: 2.4741 - val_loss: 1.0049 - val_mse: 0.7890 - val_mae: 0.6973 - val_root_mean_squared_error: 0.8882\n", "Epoch 45/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 3.6902 - mse: 3.4747 - mae: 1.1316 - root_mean_squared_error: 1.8641\n", "Epoch 45: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 3.6747 - mse: 3.4592 - mae: 1.1314 - root_mean_squared_error: 1.8599 - val_loss: 2.6766 - val_mse: 2.4616 - val_mae: 1.1398 - val_root_mean_squared_error: 1.5689\n", "Epoch 46/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 1.9248 - mse: 1.7103 - mae: 0.8651 - root_mean_squared_error: 1.3078\n", "Epoch 46: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 1.9295 - mse: 1.7150 - mae: 0.8655 - root_mean_squared_error: 1.3096 - val_loss: 1.2184 - val_mse: 1.0044 - val_mae: 0.6900 - val_root_mean_squared_error: 1.0022\n", "Epoch 47/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 1.5276 - mse: 1.3141 - mae: 0.7963 - root_mean_squared_error: 1.1463\n", "Epoch 47: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 5s 64ms/step - loss: 1.5252 - mse: 1.3117 - mae: 0.7966 - root_mean_squared_error: 1.1453 - val_loss: 0.7230 - val_mse: 0.5101 - val_mae: 0.5423 - val_root_mean_squared_error: 0.7142\n", "Epoch 48/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 1.7922 - mse: 1.5797 - mae: 0.8271 - root_mean_squared_error: 1.2569\n", "Epoch 48: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 1.8019 - mse: 1.5895 - mae: 0.8303 - root_mean_squared_error: 1.2607 - val_loss: 1.0458 - val_mse: 0.8339 - val_mae: 0.6479 - val_root_mean_squared_error: 0.9132\n", "Epoch 49/1000\n", "73/73 [==============================] - ETA: 0s - loss: 2.1860 - mse: 1.9745 - mae: 0.9224 - root_mean_squared_error: 1.4052\n", "Epoch 49: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 2.1860 - mse: 1.9745 - mae: 0.9224 - root_mean_squared_error: 1.4052 - val_loss: 1.3320 - val_mse: 1.1211 - val_mae: 0.8235 - val_root_mean_squared_error: 1.0588\n", "Epoch 50/1000\n", "73/73 [==============================] - ETA: 0s - loss: 1.5814 - mse: 1.3709 - mae: 0.8036 - root_mean_squared_error: 1.1709\n", "Epoch 50: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 1.5814 - mse: 1.3709 - mae: 0.8036 - root_mean_squared_error: 1.1709 - val_loss: 0.6982 - val_mse: 0.4882 - val_mae: 0.5330 - val_root_mean_squared_error: 0.6987\n", "Epoch 51/1000\n", "73/73 [==============================] - ETA: 0s - loss: 1.3200 - mse: 1.1106 - mae: 0.7296 - root_mean_squared_error: 1.0538\n", "Epoch 51: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 1.3200 - mse: 1.1106 - mae: 0.7296 - root_mean_squared_error: 1.0538 - val_loss: 0.9118 - val_mse: 0.7029 - val_mae: 0.6309 - val_root_mean_squared_error: 0.8384\n", "Epoch 52/1000\n", "73/73 [==============================] - ETA: 0s - loss: 1.4406 - mse: 1.2322 - mae: 0.7512 - root_mean_squared_error: 1.1101\n", "Epoch 52: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 1.4406 - mse: 1.2322 - mae: 0.7512 - root_mean_squared_error: 1.1101 - val_loss: 1.1743 - val_mse: 0.9664 - val_mae: 0.7088 - val_root_mean_squared_error: 0.9831\n", "Epoch 53/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 1.7029 - mse: 1.4955 - mae: 0.8104 - root_mean_squared_error: 1.2229\n", "Epoch 53: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 1.6978 - mse: 1.4904 - mae: 0.8095 - root_mean_squared_error: 1.2208 - val_loss: 1.0533 - val_mse: 0.8464 - val_mae: 0.6816 - val_root_mean_squared_error: 0.9200\n", "Epoch 54/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 1.0668 - mse: 0.8604 - mae: 0.6583 - root_mean_squared_error: 0.9276\n", "Epoch 54: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 1.0711 - mse: 0.8648 - mae: 0.6587 - root_mean_squared_error: 0.9300 - val_loss: 0.7180 - val_mse: 0.5122 - val_mae: 0.5674 - val_root_mean_squared_error: 0.7157\n", "Epoch 55/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 1.2678 - mse: 1.0625 - mae: 0.7080 - root_mean_squared_error: 1.0308\n", "Epoch 55: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 1.2764 - mse: 1.0711 - mae: 0.7099 - root_mean_squared_error: 1.0350 - val_loss: 0.7195 - val_mse: 0.5148 - val_mae: 0.5739 - val_root_mean_squared_error: 0.7175\n", "Epoch 56/1000\n", "73/73 [==============================] - ETA: 0s - loss: 1.4966 - mse: 1.2924 - mae: 0.7477 - root_mean_squared_error: 1.1368\n", "Epoch 56: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 1.4966 - mse: 1.2924 - mae: 0.7477 - root_mean_squared_error: 1.1368 - val_loss: 1.0844 - val_mse: 0.8808 - val_mae: 0.7234 - val_root_mean_squared_error: 0.9385\n", "Epoch 57/1000\n", "73/73 [==============================] - ETA: 0s - loss: 1.6091 - mse: 1.4060 - mae: 0.7804 - root_mean_squared_error: 1.1857\n", "Epoch 57: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 1.6091 - mse: 1.4060 - mae: 0.7804 - root_mean_squared_error: 1.1857 - val_loss: 0.9262 - val_mse: 0.7236 - val_mae: 0.6236 - val_root_mean_squared_error: 0.8506\n", "Epoch 58/1000\n", "73/73 [==============================] - ETA: 0s - loss: 1.2912 - mse: 1.0891 - mae: 0.6802 - root_mean_squared_error: 1.0436\n", "Epoch 58: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 1.2912 - mse: 1.0891 - mae: 0.6802 - root_mean_squared_error: 1.0436 - val_loss: 0.8723 - val_mse: 0.6708 - val_mae: 0.5958 - val_root_mean_squared_error: 0.8190\n", "Epoch 59/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 2.4222 - mse: 2.2212 - mae: 0.9181 - root_mean_squared_error: 1.4904\n", "Epoch 59: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 2.4138 - mse: 2.2128 - mae: 0.9179 - root_mean_squared_error: 1.4876 - val_loss: 1.3476 - val_mse: 1.1471 - val_mae: 0.7319 - val_root_mean_squared_error: 1.0710\n", "Epoch 60/1000\n", "73/73 [==============================] - ETA: 0s - loss: 2.4484 - mse: 2.2484 - mae: 0.8748 - root_mean_squared_error: 1.4995\n", "Epoch 60: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 2.4484 - mse: 2.2484 - mae: 0.8748 - root_mean_squared_error: 1.4995 - val_loss: 3.0356 - val_mse: 2.8362 - val_mae: 1.2288 - val_root_mean_squared_error: 1.6841\n", "Epoch 61/1000\n", "73/73 [==============================] - ETA: 0s - loss: 2.7909 - mse: 2.5920 - mae: 0.8964 - root_mean_squared_error: 1.6100\n", "Epoch 61: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 34ms/step - loss: 2.7909 - mse: 2.5920 - mae: 0.8964 - root_mean_squared_error: 1.6100 - val_loss: 0.7648 - val_mse: 0.5664 - val_mae: 0.5856 - val_root_mean_squared_error: 0.7526\n", "Epoch 62/1000\n", "73/73 [==============================] - ETA: 0s - loss: 3.7784 - mse: 3.5804 - mae: 0.9998 - root_mean_squared_error: 1.8922\n", "Epoch 62: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 3.7784 - mse: 3.5804 - mae: 0.9998 - root_mean_squared_error: 1.8922 - val_loss: 0.9213 - val_mse: 0.7238 - val_mae: 0.6266 - val_root_mean_squared_error: 0.8508\n", "Epoch 63/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 1.5139 - mse: 1.3170 - mae: 0.6098 - root_mean_squared_error: 1.1476\n", "Epoch 63: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 1.5351 - mse: 1.3381 - mae: 0.6156 - root_mean_squared_error: 1.1568 - val_loss: 3.6908 - val_mse: 3.4944 - val_mae: 1.4008 - val_root_mean_squared_error: 1.8693\n", "Epoch 64/1000\n", "73/73 [==============================] - ETA: 0s - loss: 1.9277 - mse: 1.7317 - mae: 0.8186 - root_mean_squared_error: 1.3159\n", "Epoch 64: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 1.9277 - mse: 1.7317 - mae: 0.8186 - root_mean_squared_error: 1.3159 - val_loss: 0.9588 - val_mse: 0.7633 - val_mae: 0.6434 - val_root_mean_squared_error: 0.8737\n", "Epoch 65/1000\n", "73/73 [==============================] - ETA: 0s - loss: 1.2721 - mse: 1.0772 - mae: 0.6427 - root_mean_squared_error: 1.0379\n", "Epoch 65: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 1.2721 - mse: 1.0772 - mae: 0.6427 - root_mean_squared_error: 1.0379 - val_loss: 0.7779 - val_mse: 0.5835 - val_mae: 0.6215 - val_root_mean_squared_error: 0.7639\n", "Epoch 66/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.9585 - mse: 0.7647 - mae: 0.5805 - root_mean_squared_error: 0.8745\n", "Epoch 66: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.9601 - mse: 0.7663 - mae: 0.5812 - root_mean_squared_error: 0.8754 - val_loss: 0.7438 - val_mse: 0.5506 - val_mae: 0.5405 - val_root_mean_squared_error: 0.7420\n", "Epoch 67/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.7743 - mse: 0.5816 - mae: 0.5281 - root_mean_squared_error: 0.7626\n", "Epoch 67: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.7743 - mse: 0.5816 - mae: 0.5281 - root_mean_squared_error: 0.7626 - val_loss: 0.6553 - val_mse: 0.4632 - val_mae: 0.5424 - val_root_mean_squared_error: 0.6806\n", "Epoch 68/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.7364 - mse: 0.5448 - mae: 0.5111 - root_mean_squared_error: 0.7381\n", "Epoch 68: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.7364 - mse: 0.5448 - mae: 0.5111 - root_mean_squared_error: 0.7381 - val_loss: 0.7062 - val_mse: 0.5152 - val_mae: 0.5405 - val_root_mean_squared_error: 0.7178\n", "Epoch 69/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.7825 - mse: 0.5920 - mae: 0.4993 - root_mean_squared_error: 0.7694\n", "Epoch 69: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 34ms/step - loss: 0.7814 - mse: 0.5909 - mae: 0.4997 - root_mean_squared_error: 0.7687 - val_loss: 0.7817 - val_mse: 0.5918 - val_mae: 0.5736 - val_root_mean_squared_error: 0.7693\n", "Epoch 70/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.9786 - mse: 0.7893 - mae: 0.5822 - root_mean_squared_error: 0.8884\n", "Epoch 70: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.9786 - mse: 0.7893 - mae: 0.5822 - root_mean_squared_error: 0.8884 - val_loss: 0.7109 - val_mse: 0.5221 - val_mae: 0.5484 - val_root_mean_squared_error: 0.7226\n", "Epoch 71/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.7762 - mse: 0.5880 - mae: 0.5149 - root_mean_squared_error: 0.7668\n", "Epoch 71: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.7762 - mse: 0.5880 - mae: 0.5149 - root_mean_squared_error: 0.7668 - val_loss: 0.7707 - val_mse: 0.5830 - val_mae: 0.5796 - val_root_mean_squared_error: 0.7636\n", "Epoch 72/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.7580 - mse: 0.5709 - mae: 0.5018 - root_mean_squared_error: 0.7556\n", "Epoch 72: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 53ms/step - loss: 0.7565 - mse: 0.5694 - mae: 0.5013 - root_mean_squared_error: 0.7546 - val_loss: 0.7034 - val_mse: 0.5169 - val_mae: 0.5565 - val_root_mean_squared_error: 0.7190\n", "Epoch 73/1000\n", "73/73 [==============================] - ETA: 0s - loss: 1.1190 - mse: 0.9331 - mae: 0.6078 - root_mean_squared_error: 0.9660\n", "Epoch 73: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 1.1190 - mse: 0.9331 - mae: 0.6078 - root_mean_squared_error: 0.9660 - val_loss: 0.8189 - val_mse: 0.6335 - val_mae: 0.6082 - val_root_mean_squared_error: 0.7960\n", "Epoch 74/1000\n", "73/73 [==============================] - ETA: 0s - loss: 1.0513 - mse: 0.8665 - mae: 0.5910 - root_mean_squared_error: 0.9308\n", "Epoch 74: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 1.0513 - mse: 0.8665 - mae: 0.5910 - root_mean_squared_error: 0.9308 - val_loss: 1.1930 - val_mse: 1.0087 - val_mae: 0.7055 - val_root_mean_squared_error: 1.0044\n", "Epoch 75/1000\n", "73/73 [==============================] - ETA: 0s - loss: 1.1328 - mse: 0.9491 - mae: 0.5572 - root_mean_squared_error: 0.9742\n", "Epoch 75: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 1.1328 - mse: 0.9491 - mae: 0.5572 - root_mean_squared_error: 0.9742 - val_loss: 0.8584 - val_mse: 0.6752 - val_mae: 0.6091 - val_root_mean_squared_error: 0.8217\n", "Epoch 76/1000\n", "73/73 [==============================] - ETA: 0s - loss: 1.0938 - mse: 0.9112 - mae: 0.5651 - root_mean_squared_error: 0.9546\n", "Epoch 76: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 1.0938 - mse: 0.9112 - mae: 0.5651 - root_mean_squared_error: 0.9546 - val_loss: 0.8963 - val_mse: 0.7142 - val_mae: 0.6080 - val_root_mean_squared_error: 0.8451\n", "Epoch 77/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 1.3804 - mse: 1.1989 - mae: 0.6186 - root_mean_squared_error: 1.0949\n", "Epoch 77: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 1.3636 - mse: 1.1820 - mae: 0.6147 - root_mean_squared_error: 1.0872 - val_loss: 0.6624 - val_mse: 0.4814 - val_mae: 0.5259 - val_root_mean_squared_error: 0.6938\n", "Epoch 78/1000\n", "73/73 [==============================] - ETA: 0s - loss: 1.0143 - mse: 0.8339 - mae: 0.5331 - root_mean_squared_error: 0.9132\n", "Epoch 78: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 1.0143 - mse: 0.8339 - mae: 0.5331 - root_mean_squared_error: 0.9132 - val_loss: 0.7414 - val_mse: 0.5615 - val_mae: 0.5431 - val_root_mean_squared_error: 0.7493\n", "Epoch 79/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.6259 - mse: 0.4466 - mae: 0.4396 - root_mean_squared_error: 0.6683\n", "Epoch 79: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.6252 - mse: 0.4459 - mae: 0.4398 - root_mean_squared_error: 0.6678 - val_loss: 0.5992 - val_mse: 0.4205 - val_mae: 0.4933 - val_root_mean_squared_error: 0.6484\n", "Epoch 80/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.5388 - mse: 0.3607 - mae: 0.4129 - root_mean_squared_error: 0.6006\n", "Epoch 80: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.5369 - mse: 0.3588 - mae: 0.4119 - root_mean_squared_error: 0.5990 - val_loss: 0.8311 - val_mse: 0.6536 - val_mae: 0.6031 - val_root_mean_squared_error: 0.8085\n", "Epoch 81/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.4957 - mse: 0.3188 - mae: 0.3833 - root_mean_squared_error: 0.5646\n", "Epoch 81: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.4942 - mse: 0.3173 - mae: 0.3821 - root_mean_squared_error: 0.5633 - val_loss: 0.6455 - val_mse: 0.4692 - val_mae: 0.5369 - val_root_mean_squared_error: 0.6850\n", "Epoch 82/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.4999 - mse: 0.3242 - mae: 0.3977 - root_mean_squared_error: 0.5694\n", "Epoch 82: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.5028 - mse: 0.3271 - mae: 0.3994 - root_mean_squared_error: 0.5720 - val_loss: 0.6612 - val_mse: 0.4861 - val_mae: 0.5304 - val_root_mean_squared_error: 0.6972\n", "Epoch 83/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.6530 - mse: 0.4785 - mae: 0.4589 - root_mean_squared_error: 0.6917\n", "Epoch 83: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.6552 - mse: 0.4807 - mae: 0.4602 - root_mean_squared_error: 0.6933 - val_loss: 0.8424 - val_mse: 0.6684 - val_mae: 0.6007 - val_root_mean_squared_error: 0.8176\n", "Epoch 84/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.7413 - mse: 0.5680 - mae: 0.4828 - root_mean_squared_error: 0.7537\n", "Epoch 84: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 33ms/step - loss: 0.7413 - mse: 0.5680 - mae: 0.4828 - root_mean_squared_error: 0.7537 - val_loss: 0.8627 - val_mse: 0.6900 - val_mae: 0.5961 - val_root_mean_squared_error: 0.8307\n", "Epoch 85/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.6304 - mse: 0.4582 - mae: 0.4391 - root_mean_squared_error: 0.6769\n", "Epoch 85: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.6304 - mse: 0.4582 - mae: 0.4391 - root_mean_squared_error: 0.6769 - val_loss: 0.6608 - val_mse: 0.4892 - val_mae: 0.5314 - val_root_mean_squared_error: 0.6994\n", "Epoch 86/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.4818 - mse: 0.3108 - mae: 0.3645 - root_mean_squared_error: 0.5575\n", "Epoch 86: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.4856 - mse: 0.3146 - mae: 0.3669 - root_mean_squared_error: 0.5609 - val_loss: 0.7340 - val_mse: 0.5636 - val_mae: 0.5437 - val_root_mean_squared_error: 0.7507\n", "Epoch 87/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.5090 - mse: 0.3392 - mae: 0.3639 - root_mean_squared_error: 0.5824\n", "Epoch 87: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.5071 - mse: 0.3373 - mae: 0.3641 - root_mean_squared_error: 0.5808 - val_loss: 0.6138 - val_mse: 0.4446 - val_mae: 0.5060 - val_root_mean_squared_error: 0.6668\n", "Epoch 88/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.5053 - mse: 0.3367 - mae: 0.3826 - root_mean_squared_error: 0.5803\n", "Epoch 88: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.5046 - mse: 0.3360 - mae: 0.3828 - root_mean_squared_error: 0.5797 - val_loss: 0.7781 - val_mse: 0.6101 - val_mae: 0.6029 - val_root_mean_squared_error: 0.7811\n", "Epoch 89/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.6824 - mse: 0.5151 - mae: 0.4694 - root_mean_squared_error: 0.7177\n", "Epoch 89: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.6824 - mse: 0.5151 - mae: 0.4694 - root_mean_squared_error: 0.7177 - val_loss: 0.7985 - val_mse: 0.6317 - val_mae: 0.6043 - val_root_mean_squared_error: 0.7948\n", "Epoch 90/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.5606 - mse: 0.3944 - mae: 0.4251 - root_mean_squared_error: 0.6280\n", "Epoch 90: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.5606 - mse: 0.3944 - mae: 0.4251 - root_mean_squared_error: 0.6280 - val_loss: 0.6586 - val_mse: 0.4930 - val_mae: 0.5189 - val_root_mean_squared_error: 0.7022\n", "Epoch 91/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.4598 - mse: 0.2948 - mae: 0.3691 - root_mean_squared_error: 0.5430\n", "Epoch 91: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.4587 - mse: 0.2937 - mae: 0.3686 - root_mean_squared_error: 0.5419 - val_loss: 0.5848 - val_mse: 0.4204 - val_mae: 0.4880 - val_root_mean_squared_error: 0.6484\n", "Epoch 92/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.3565 - mse: 0.1927 - mae: 0.3086 - root_mean_squared_error: 0.4390\n", "Epoch 92: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.3565 - mse: 0.1927 - mae: 0.3086 - root_mean_squared_error: 0.4390 - val_loss: 0.7652 - val_mse: 0.6020 - val_mae: 0.6049 - val_root_mean_squared_error: 0.7759\n", "Epoch 93/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.4381 - mse: 0.2755 - mae: 0.3572 - root_mean_squared_error: 0.5249\n", "Epoch 93: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 50ms/step - loss: 0.4381 - mse: 0.2755 - mae: 0.3572 - root_mean_squared_error: 0.5249 - val_loss: 0.6355 - val_mse: 0.4736 - val_mae: 0.5214 - val_root_mean_squared_error: 0.6882\n", "Epoch 94/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.3938 - mse: 0.2324 - mae: 0.3178 - root_mean_squared_error: 0.4821\n", "Epoch 94: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.3943 - mse: 0.2330 - mae: 0.3190 - root_mean_squared_error: 0.4827 - val_loss: 0.8852 - val_mse: 0.7245 - val_mae: 0.6219 - val_root_mean_squared_error: 0.8512\n", "Epoch 95/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.8038 - mse: 0.6437 - mae: 0.4998 - root_mean_squared_error: 0.8023\n", "Epoch 95: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.8038 - mse: 0.6437 - mae: 0.4998 - root_mean_squared_error: 0.8023 - val_loss: 0.7974 - val_mse: 0.6378 - val_mae: 0.6106 - val_root_mean_squared_error: 0.7986\n", "Epoch 96/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.7054 - mse: 0.5464 - mae: 0.3969 - root_mean_squared_error: 0.7392\n", "Epoch 96: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.7054 - mse: 0.5464 - mae: 0.3969 - root_mean_squared_error: 0.7392 - val_loss: 1.0851 - val_mse: 0.9267 - val_mae: 0.6663 - val_root_mean_squared_error: 0.9626\n", "Epoch 97/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.9202 - mse: 0.7623 - mae: 0.4659 - root_mean_squared_error: 0.8731\n", "Epoch 97: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.9202 - mse: 0.7623 - mae: 0.4659 - root_mean_squared_error: 0.8731 - val_loss: 0.6914 - val_mse: 0.5340 - val_mae: 0.5790 - val_root_mean_squared_error: 0.7308\n", "Epoch 98/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.9232 - mse: 0.7664 - mae: 0.4666 - root_mean_squared_error: 0.8755\n", "Epoch 98: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 0.9232 - mse: 0.7664 - mae: 0.4666 - root_mean_squared_error: 0.8755 - val_loss: 1.0743 - val_mse: 0.9181 - val_mae: 0.7436 - val_root_mean_squared_error: 0.9582\n", "Epoch 99/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.9782 - mse: 0.8225 - mae: 0.5248 - root_mean_squared_error: 0.9069\n", "Epoch 99: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.9782 - mse: 0.8225 - mae: 0.5248 - root_mean_squared_error: 0.9069 - val_loss: 0.7742 - val_mse: 0.6190 - val_mae: 0.5989 - val_root_mean_squared_error: 0.7868\n", "Epoch 100/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.6323 - mse: 0.4777 - mae: 0.4063 - root_mean_squared_error: 0.6911\n", "Epoch 100: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 34ms/step - loss: 0.6323 - mse: 0.4777 - mae: 0.4063 - root_mean_squared_error: 0.6911 - val_loss: 0.6299 - val_mse: 0.4758 - val_mae: 0.5201 - val_root_mean_squared_error: 0.6898\n", "Epoch 101/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.4818 - mse: 0.3283 - mae: 0.3507 - root_mean_squared_error: 0.5730\n", "Epoch 101: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.4818 - mse: 0.3283 - mae: 0.3507 - root_mean_squared_error: 0.5730 - val_loss: 0.6179 - val_mse: 0.4650 - val_mae: 0.5092 - val_root_mean_squared_error: 0.6819\n", "Epoch 102/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.3840 - mse: 0.2317 - mae: 0.3050 - root_mean_squared_error: 0.4813\n", "Epoch 102: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.3840 - mse: 0.2317 - mae: 0.3050 - root_mean_squared_error: 0.4813 - val_loss: 0.6547 - val_mse: 0.5030 - val_mae: 0.5353 - val_root_mean_squared_error: 0.7092\n", "Epoch 103/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.3392 - mse: 0.1880 - mae: 0.2979 - root_mean_squared_error: 0.4336\n", "Epoch 103: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.3392 - mse: 0.1880 - mae: 0.2979 - root_mean_squared_error: 0.4336 - val_loss: 0.6426 - val_mse: 0.4920 - val_mae: 0.5565 - val_root_mean_squared_error: 0.7015\n", "Epoch 104/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.3244 - mse: 0.1745 - mae: 0.2842 - root_mean_squared_error: 0.4177\n", "Epoch 104: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.3244 - mse: 0.1745 - mae: 0.2842 - root_mean_squared_error: 0.4177 - val_loss: 0.5490 - val_mse: 0.3997 - val_mae: 0.4743 - val_root_mean_squared_error: 0.6322\n", "Epoch 105/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2942 - mse: 0.1455 - mae: 0.2706 - root_mean_squared_error: 0.3814\n", "Epoch 105: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.2948 - mse: 0.1461 - mae: 0.2714 - root_mean_squared_error: 0.3823 - val_loss: 0.5373 - val_mse: 0.3893 - val_mae: 0.4780 - val_root_mean_squared_error: 0.6239\n", "Epoch 106/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2966 - mse: 0.1493 - mae: 0.2698 - root_mean_squared_error: 0.3864\n", "Epoch 106: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.2966 - mse: 0.1492 - mae: 0.2699 - root_mean_squared_error: 0.3863 - val_loss: 0.5424 - val_mse: 0.3957 - val_mae: 0.4764 - val_root_mean_squared_error: 0.6290\n", "Epoch 107/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2749 - mse: 0.1288 - mae: 0.2558 - root_mean_squared_error: 0.3589\n", "Epoch 107: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.2744 - mse: 0.1283 - mae: 0.2554 - root_mean_squared_error: 0.3582 - val_loss: 0.5556 - val_mse: 0.4101 - val_mae: 0.4898 - val_root_mean_squared_error: 0.6404\n", "Epoch 108/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.3215 - mse: 0.1766 - mae: 0.2803 - root_mean_squared_error: 0.4203\n", "Epoch 108: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.3215 - mse: 0.1766 - mae: 0.2803 - root_mean_squared_error: 0.4203 - val_loss: 0.5459 - val_mse: 0.4017 - val_mae: 0.4947 - val_root_mean_squared_error: 0.6338\n", "Epoch 109/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.3875 - mse: 0.2440 - mae: 0.3141 - root_mean_squared_error: 0.4939\n", "Epoch 109: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.3878 - mse: 0.2442 - mae: 0.3144 - root_mean_squared_error: 0.4942 - val_loss: 0.6253 - val_mse: 0.4823 - val_mae: 0.5241 - val_root_mean_squared_error: 0.6945\n", "Epoch 110/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.3845 - mse: 0.2421 - mae: 0.3083 - root_mean_squared_error: 0.4920\n", "Epoch 110: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.3845 - mse: 0.2421 - mae: 0.3083 - root_mean_squared_error: 0.4920 - val_loss: 0.5850 - val_mse: 0.4433 - val_mae: 0.5196 - val_root_mean_squared_error: 0.6658\n", "Epoch 111/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.3620 - mse: 0.2208 - mae: 0.2967 - root_mean_squared_error: 0.4699\n", "Epoch 111: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.3606 - mse: 0.2195 - mae: 0.2957 - root_mean_squared_error: 0.4685 - val_loss: 0.5768 - val_mse: 0.4363 - val_mae: 0.5080 - val_root_mean_squared_error: 0.6606\n", "Epoch 112/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.3644 - mse: 0.2245 - mae: 0.2819 - root_mean_squared_error: 0.4738\n", "Epoch 112: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.3644 - mse: 0.2245 - mae: 0.2819 - root_mean_squared_error: 0.4738 - val_loss: 0.6648 - val_mse: 0.5255 - val_mae: 0.5428 - val_root_mean_squared_error: 0.7249\n", "Epoch 113/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.4542 - mse: 0.3155 - mae: 0.3398 - root_mean_squared_error: 0.5617\n", "Epoch 113: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.4550 - mse: 0.3163 - mae: 0.3397 - root_mean_squared_error: 0.5624 - val_loss: 0.6926 - val_mse: 0.5546 - val_mae: 0.5461 - val_root_mean_squared_error: 0.7447\n", "Epoch 114/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.4777 - mse: 0.3402 - mae: 0.3385 - root_mean_squared_error: 0.5833\n", "Epoch 114: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.4777 - mse: 0.3402 - mae: 0.3385 - root_mean_squared_error: 0.5833 - val_loss: 0.5860 - val_mse: 0.4490 - val_mae: 0.5235 - val_root_mean_squared_error: 0.6701\n", "Epoch 115/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.3479 - mse: 0.2115 - mae: 0.2806 - root_mean_squared_error: 0.4599\n", "Epoch 115: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 53ms/step - loss: 0.3479 - mse: 0.2115 - mae: 0.2806 - root_mean_squared_error: 0.4599 - val_loss: 0.7133 - val_mse: 0.5776 - val_mae: 0.5736 - val_root_mean_squared_error: 0.7600\n", "Epoch 116/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.4181 - mse: 0.2829 - mae: 0.3430 - root_mean_squared_error: 0.5319\n", "Epoch 116: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 61ms/step - loss: 0.4181 - mse: 0.2829 - mae: 0.3430 - root_mean_squared_error: 0.5319 - val_loss: 0.5443 - val_mse: 0.4096 - val_mae: 0.4923 - val_root_mean_squared_error: 0.6400\n", "Epoch 117/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.3664 - mse: 0.2323 - mae: 0.3141 - root_mean_squared_error: 0.4820\n", "Epoch 117: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.3665 - mse: 0.2324 - mae: 0.3151 - root_mean_squared_error: 0.4821 - val_loss: 0.5946 - val_mse: 0.4611 - val_mae: 0.5154 - val_root_mean_squared_error: 0.6790\n", "Epoch 118/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2830 - mse: 0.1501 - mae: 0.2580 - root_mean_squared_error: 0.3874\n", "Epoch 118: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 52ms/step - loss: 0.2825 - mse: 0.1496 - mae: 0.2579 - root_mean_squared_error: 0.3868 - val_loss: 0.6334 - val_mse: 0.5011 - val_mae: 0.5386 - val_root_mean_squared_error: 0.7079\n", "Epoch 119/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.2385 - mse: 0.1069 - mae: 0.2294 - root_mean_squared_error: 0.3269\n", "Epoch 119: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 54ms/step - loss: 0.2385 - mse: 0.1069 - mae: 0.2294 - root_mean_squared_error: 0.3269 - val_loss: 0.5537 - val_mse: 0.4226 - val_mae: 0.4898 - val_root_mean_squared_error: 0.6501\n", "Epoch 120/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.2446 - mse: 0.1142 - mae: 0.2354 - root_mean_squared_error: 0.3380\n", "Epoch 120: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 51ms/step - loss: 0.2446 - mse: 0.1142 - mae: 0.2354 - root_mean_squared_error: 0.3380 - val_loss: 0.5336 - val_mse: 0.4039 - val_mae: 0.4843 - val_root_mean_squared_error: 0.6355\n", "Epoch 121/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.2536 - mse: 0.1245 - mae: 0.2388 - root_mean_squared_error: 0.3528\n", "Epoch 121: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.2536 - mse: 0.1245 - mae: 0.2388 - root_mean_squared_error: 0.3528 - val_loss: 0.5751 - val_mse: 0.4466 - val_mae: 0.4992 - val_root_mean_squared_error: 0.6683\n", "Epoch 122/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.2282 - mse: 0.1003 - mae: 0.2116 - root_mean_squared_error: 0.3167\n", "Epoch 122: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.2282 - mse: 0.1003 - mae: 0.2116 - root_mean_squared_error: 0.3167 - val_loss: 0.5484 - val_mse: 0.4212 - val_mae: 0.4934 - val_root_mean_squared_error: 0.6490\n", "Epoch 123/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.2265 - mse: 0.1000 - mae: 0.2156 - root_mean_squared_error: 0.3162\n", "Epoch 123: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.2268 - mse: 0.1003 - mae: 0.2158 - root_mean_squared_error: 0.3166 - val_loss: 0.5387 - val_mse: 0.4129 - val_mae: 0.4842 - val_root_mean_squared_error: 0.6426\n", "Epoch 124/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2101 - mse: 0.0849 - mae: 0.2007 - root_mean_squared_error: 0.2914\n", "Epoch 124: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.2101 - mse: 0.0849 - mae: 0.2009 - root_mean_squared_error: 0.2913 - val_loss: 0.5295 - val_mse: 0.4049 - val_mae: 0.4775 - val_root_mean_squared_error: 0.6363\n", "Epoch 125/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.2277 - mse: 0.1038 - mae: 0.2243 - root_mean_squared_error: 0.3221\n", "Epoch 125: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.2277 - mse: 0.1038 - mae: 0.2243 - root_mean_squared_error: 0.3221 - val_loss: 0.6404 - val_mse: 0.5171 - val_mae: 0.5389 - val_root_mean_squared_error: 0.7191\n", "Epoch 126/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.2978 - mse: 0.1751 - mae: 0.2949 - root_mean_squared_error: 0.4184\n", "Epoch 126: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 51ms/step - loss: 0.2978 - mse: 0.1751 - mae: 0.2949 - root_mean_squared_error: 0.4184 - val_loss: 0.5351 - val_mse: 0.4131 - val_mae: 0.4976 - val_root_mean_squared_error: 0.6427\n", "Epoch 127/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.2430 - mse: 0.1216 - mae: 0.2350 - root_mean_squared_error: 0.3487\n", "Epoch 127: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.2430 - mse: 0.1216 - mae: 0.2350 - root_mean_squared_error: 0.3487 - val_loss: 0.5443 - val_mse: 0.4235 - val_mae: 0.4925 - val_root_mean_squared_error: 0.6508\n", "Epoch 128/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2360 - mse: 0.1157 - mae: 0.2320 - root_mean_squared_error: 0.3402\n", "Epoch 128: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 34ms/step - loss: 0.2353 - mse: 0.1151 - mae: 0.2314 - root_mean_squared_error: 0.3393 - val_loss: 0.5191 - val_mse: 0.3995 - val_mae: 0.4701 - val_root_mean_squared_error: 0.6321\n", "Epoch 129/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2117 - mse: 0.0927 - mae: 0.2161 - root_mean_squared_error: 0.3044\n", "Epoch 129: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.2116 - mse: 0.0926 - mae: 0.2163 - root_mean_squared_error: 0.3043 - val_loss: 0.5407 - val_mse: 0.4223 - val_mae: 0.4906 - val_root_mean_squared_error: 0.6499\n", "Epoch 130/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.2239 - mse: 0.1061 - mae: 0.2183 - root_mean_squared_error: 0.3257\n", "Epoch 130: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.2233 - mse: 0.1055 - mae: 0.2176 - root_mean_squared_error: 0.3248 - val_loss: 0.5019 - val_mse: 0.3847 - val_mae: 0.4708 - val_root_mean_squared_error: 0.6203\n", "Epoch 131/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.3470 - mse: 0.2303 - mae: 0.2940 - root_mean_squared_error: 0.4799\n", "Epoch 131: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.3470 - mse: 0.2303 - mae: 0.2940 - root_mean_squared_error: 0.4799 - val_loss: 0.6857 - val_mse: 0.5695 - val_mae: 0.5703 - val_root_mean_squared_error: 0.7547\n", "Epoch 132/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.3098 - mse: 0.1943 - mae: 0.2559 - root_mean_squared_error: 0.4408\n", "Epoch 132: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 34ms/step - loss: 0.3105 - mse: 0.1950 - mae: 0.2568 - root_mean_squared_error: 0.4415 - val_loss: 0.7237 - val_mse: 0.6088 - val_mae: 0.6109 - val_root_mean_squared_error: 0.7802\n", "Epoch 133/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.3865 - mse: 0.2721 - mae: 0.3167 - root_mean_squared_error: 0.5216\n", "Epoch 133: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.3858 - mse: 0.2713 - mae: 0.3169 - root_mean_squared_error: 0.5209 - val_loss: 0.6510 - val_mse: 0.5370 - val_mae: 0.5411 - val_root_mean_squared_error: 0.7328\n", "Epoch 134/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.4085 - mse: 0.2950 - mae: 0.3168 - root_mean_squared_error: 0.5431\n", "Epoch 134: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.4085 - mse: 0.2950 - mae: 0.3168 - root_mean_squared_error: 0.5431 - val_loss: 0.5648 - val_mse: 0.4518 - val_mae: 0.5096 - val_root_mean_squared_error: 0.6722\n", "Epoch 135/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.3842 - mse: 0.2718 - mae: 0.2921 - root_mean_squared_error: 0.5214\n", "Epoch 135: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.3842 - mse: 0.2718 - mae: 0.2921 - root_mean_squared_error: 0.5214 - val_loss: 1.1816 - val_mse: 1.0697 - val_mae: 0.7832 - val_root_mean_squared_error: 1.0343\n", "Epoch 136/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.4016 - mse: 0.2901 - mae: 0.3084 - root_mean_squared_error: 0.5386\n", "Epoch 136: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.4026 - mse: 0.2911 - mae: 0.3091 - root_mean_squared_error: 0.5395 - val_loss: 0.4891 - val_mse: 0.3781 - val_mae: 0.4690 - val_root_mean_squared_error: 0.6149\n", "Epoch 137/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2803 - mse: 0.1699 - mae: 0.2580 - root_mean_squared_error: 0.4121\n", "Epoch 137: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 59ms/step - loss: 0.2808 - mse: 0.1704 - mae: 0.2589 - root_mean_squared_error: 0.4128 - val_loss: 0.6201 - val_mse: 0.5102 - val_mae: 0.5351 - val_root_mean_squared_error: 0.7143\n", "Epoch 138/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2444 - mse: 0.1351 - mae: 0.2526 - root_mean_squared_error: 0.3676\n", "Epoch 138: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.2438 - mse: 0.1345 - mae: 0.2521 - root_mean_squared_error: 0.3667 - val_loss: 0.5163 - val_mse: 0.4076 - val_mae: 0.4815 - val_root_mean_squared_error: 0.6384\n", "Epoch 139/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2132 - mse: 0.1051 - mae: 0.2262 - root_mean_squared_error: 0.3241\n", "Epoch 139: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.2130 - mse: 0.1048 - mae: 0.2261 - root_mean_squared_error: 0.3237 - val_loss: 0.5362 - val_mse: 0.4286 - val_mae: 0.4884 - val_root_mean_squared_error: 0.6546\n", "Epoch 140/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.2063 - mse: 0.0993 - mae: 0.2084 - root_mean_squared_error: 0.3151\n", "Epoch 140: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.2063 - mse: 0.0993 - mae: 0.2084 - root_mean_squared_error: 0.3151 - val_loss: 0.5003 - val_mse: 0.3939 - val_mae: 0.4837 - val_root_mean_squared_error: 0.6276\n", "Epoch 141/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2292 - mse: 0.1233 - mae: 0.2348 - root_mean_squared_error: 0.3512\n", "Epoch 141: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.2291 - mse: 0.1232 - mae: 0.2352 - root_mean_squared_error: 0.3510 - val_loss: 0.5518 - val_mse: 0.4466 - val_mae: 0.4942 - val_root_mean_squared_error: 0.6683\n", "Epoch 142/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2125 - mse: 0.1077 - mae: 0.2306 - root_mean_squared_error: 0.3282\n", "Epoch 142: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.2123 - mse: 0.1076 - mae: 0.2304 - root_mean_squared_error: 0.3281 - val_loss: 0.4907 - val_mse: 0.3866 - val_mae: 0.4748 - val_root_mean_squared_error: 0.6218\n", "Epoch 143/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2066 - mse: 0.1030 - mae: 0.2245 - root_mean_squared_error: 0.3209\n", "Epoch 143: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.2065 - mse: 0.1029 - mae: 0.2249 - root_mean_squared_error: 0.3208 - val_loss: 0.5198 - val_mse: 0.4168 - val_mae: 0.4948 - val_root_mean_squared_error: 0.6456\n", "Epoch 144/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1827 - mse: 0.0802 - mae: 0.1942 - root_mean_squared_error: 0.2832\n", "Epoch 144: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 53ms/step - loss: 0.1843 - mse: 0.0819 - mae: 0.1956 - root_mean_squared_error: 0.2862 - val_loss: 0.5422 - val_mse: 0.4403 - val_mae: 0.5103 - val_root_mean_squared_error: 0.6636\n", "Epoch 145/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2028 - mse: 0.1015 - mae: 0.2246 - root_mean_squared_error: 0.3186\n", "Epoch 145: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.2025 - mse: 0.1012 - mae: 0.2245 - root_mean_squared_error: 0.3181 - val_loss: 0.5717 - val_mse: 0.4711 - val_mae: 0.5485 - val_root_mean_squared_error: 0.6863\n", "Epoch 146/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.2390 - mse: 0.1388 - mae: 0.2567 - root_mean_squared_error: 0.3725\n", "Epoch 146: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 50ms/step - loss: 0.2390 - mse: 0.1388 - mae: 0.2567 - root_mean_squared_error: 0.3725 - val_loss: 0.4974 - val_mse: 0.3977 - val_mae: 0.4811 - val_root_mean_squared_error: 0.6306\n", "Epoch 147/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1781 - mse: 0.0790 - mae: 0.1977 - root_mean_squared_error: 0.2811\n", "Epoch 147: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.1781 - mse: 0.0790 - mae: 0.1977 - root_mean_squared_error: 0.2811 - val_loss: 0.5060 - val_mse: 0.4075 - val_mae: 0.5019 - val_root_mean_squared_error: 0.6384\n", "Epoch 148/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1860 - mse: 0.0880 - mae: 0.2061 - root_mean_squared_error: 0.2967\n", "Epoch 148: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.1867 - mse: 0.0887 - mae: 0.2071 - root_mean_squared_error: 0.2978 - val_loss: 0.5002 - val_mse: 0.4028 - val_mae: 0.4798 - val_root_mean_squared_error: 0.6347\n", "Epoch 149/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2057 - mse: 0.1089 - mae: 0.2195 - root_mean_squared_error: 0.3300\n", "Epoch 149: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.2057 - mse: 0.1089 - mae: 0.2194 - root_mean_squared_error: 0.3300 - val_loss: 0.5131 - val_mse: 0.4169 - val_mae: 0.5008 - val_root_mean_squared_error: 0.6456\n", "Epoch 150/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.2153 - mse: 0.1195 - mae: 0.2200 - root_mean_squared_error: 0.3457\n", "Epoch 150: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.2142 - mse: 0.1185 - mae: 0.2198 - root_mean_squared_error: 0.3442 - val_loss: 0.4953 - val_mse: 0.4001 - val_mae: 0.4902 - val_root_mean_squared_error: 0.6325\n", "Epoch 151/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2076 - mse: 0.1128 - mae: 0.2144 - root_mean_squared_error: 0.3359\n", "Epoch 151: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.2085 - mse: 0.1138 - mae: 0.2153 - root_mean_squared_error: 0.3373 - val_loss: 0.6039 - val_mse: 0.5097 - val_mae: 0.5535 - val_root_mean_squared_error: 0.7139\n", "Epoch 152/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.2948 - mse: 0.2010 - mae: 0.3001 - root_mean_squared_error: 0.4484\n", "Epoch 152: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.2948 - mse: 0.2010 - mae: 0.3001 - root_mean_squared_error: 0.4484 - val_loss: 0.5162 - val_mse: 0.4230 - val_mae: 0.4954 - val_root_mean_squared_error: 0.6503\n", "Epoch 153/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2363 - mse: 0.1434 - mae: 0.2393 - root_mean_squared_error: 0.3787\n", "Epoch 153: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.2359 - mse: 0.1431 - mae: 0.2397 - root_mean_squared_error: 0.3783 - val_loss: 0.5788 - val_mse: 0.4864 - val_mae: 0.5443 - val_root_mean_squared_error: 0.6975\n", "Epoch 154/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2880 - mse: 0.1961 - mae: 0.2686 - root_mean_squared_error: 0.4429\n", "Epoch 154: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.2869 - mse: 0.1950 - mae: 0.2679 - root_mean_squared_error: 0.4416 - val_loss: 0.5064 - val_mse: 0.4149 - val_mae: 0.4673 - val_root_mean_squared_error: 0.6441\n", "Epoch 155/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.2691 - mse: 0.1781 - mae: 0.2321 - root_mean_squared_error: 0.4220\n", "Epoch 155: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.2689 - mse: 0.1779 - mae: 0.2325 - root_mean_squared_error: 0.4218 - val_loss: 0.5107 - val_mse: 0.4203 - val_mae: 0.4902 - val_root_mean_squared_error: 0.6483\n", "Epoch 156/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.2387 - mse: 0.1487 - mae: 0.2417 - root_mean_squared_error: 0.3856\n", "Epoch 156: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.2387 - mse: 0.1487 - mae: 0.2417 - root_mean_squared_error: 0.3856 - val_loss: 0.5934 - val_mse: 0.5039 - val_mae: 0.5418 - val_root_mean_squared_error: 0.7098\n", "Epoch 157/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.2052 - mse: 0.1161 - mae: 0.2255 - root_mean_squared_error: 0.3407\n", "Epoch 157: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.2052 - mse: 0.1161 - mae: 0.2255 - root_mean_squared_error: 0.3407 - val_loss: 0.4698 - val_mse: 0.3812 - val_mae: 0.4616 - val_root_mean_squared_error: 0.6174\n", "Epoch 158/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1818 - mse: 0.0937 - mae: 0.2211 - root_mean_squared_error: 0.3061\n", "Epoch 158: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 56ms/step - loss: 0.1814 - mse: 0.0933 - mae: 0.2206 - root_mean_squared_error: 0.3054 - val_loss: 0.5491 - val_mse: 0.4615 - val_mae: 0.5188 - val_root_mean_squared_error: 0.6794\n", "Epoch 159/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1566 - mse: 0.0695 - mae: 0.1907 - root_mean_squared_error: 0.2636\n", "Epoch 159: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 5s 64ms/step - loss: 0.1580 - mse: 0.0709 - mae: 0.1914 - root_mean_squared_error: 0.2662 - val_loss: 0.4932 - val_mse: 0.4066 - val_mae: 0.4817 - val_root_mean_squared_error: 0.6377\n", "Epoch 160/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1620 - mse: 0.0759 - mae: 0.1904 - root_mean_squared_error: 0.2755\n", "Epoch 160: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.1639 - mse: 0.0779 - mae: 0.1918 - root_mean_squared_error: 0.2790 - val_loss: 0.4860 - val_mse: 0.4005 - val_mae: 0.4786 - val_root_mean_squared_error: 0.6328\n", "Epoch 161/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1769 - mse: 0.0918 - mae: 0.1963 - root_mean_squared_error: 0.3031\n", "Epoch 161: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.1768 - mse: 0.0917 - mae: 0.1964 - root_mean_squared_error: 0.3028 - val_loss: 0.4712 - val_mse: 0.3866 - val_mae: 0.4679 - val_root_mean_squared_error: 0.6218\n", "Epoch 162/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1808 - mse: 0.0968 - mae: 0.2099 - root_mean_squared_error: 0.3111\n", "Epoch 162: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 52ms/step - loss: 0.1808 - mse: 0.0968 - mae: 0.2099 - root_mean_squared_error: 0.3111 - val_loss: 0.4610 - val_mse: 0.3774 - val_mae: 0.4581 - val_root_mean_squared_error: 0.6144\n", "Epoch 163/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1853 - mse: 0.1022 - mae: 0.2118 - root_mean_squared_error: 0.3197\n", "Epoch 163: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.1853 - mse: 0.1022 - mae: 0.2118 - root_mean_squared_error: 0.3197 - val_loss: 0.4553 - val_mse: 0.3726 - val_mae: 0.4747 - val_root_mean_squared_error: 0.6104\n", "Epoch 164/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1826 - mse: 0.1004 - mae: 0.2028 - root_mean_squared_error: 0.3169\n", "Epoch 164: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.1823 - mse: 0.1002 - mae: 0.2028 - root_mean_squared_error: 0.3165 - val_loss: 0.5136 - val_mse: 0.4319 - val_mae: 0.5018 - val_root_mean_squared_error: 0.6572\n", "Epoch 165/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.2094 - mse: 0.1280 - mae: 0.2487 - root_mean_squared_error: 0.3578\n", "Epoch 165: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.2094 - mse: 0.1280 - mae: 0.2487 - root_mean_squared_error: 0.3578 - val_loss: 0.4626 - val_mse: 0.3817 - val_mae: 0.4658 - val_root_mean_squared_error: 0.6178\n", "Epoch 166/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1903 - mse: 0.1098 - mae: 0.2268 - root_mean_squared_error: 0.3314\n", "Epoch 166: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.1900 - mse: 0.1095 - mae: 0.2266 - root_mean_squared_error: 0.3309 - val_loss: 0.5464 - val_mse: 0.4663 - val_mae: 0.5028 - val_root_mean_squared_error: 0.6829\n", "Epoch 167/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1828 - mse: 0.1031 - mae: 0.2302 - root_mean_squared_error: 0.3211\n", "Epoch 167: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 0.1824 - mse: 0.1027 - mae: 0.2298 - root_mean_squared_error: 0.3205 - val_loss: 0.4760 - val_mse: 0.3968 - val_mae: 0.4774 - val_root_mean_squared_error: 0.6299\n", "Epoch 168/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1757 - mse: 0.0969 - mae: 0.2066 - root_mean_squared_error: 0.3113\n", "Epoch 168: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.1753 - mse: 0.0965 - mae: 0.2062 - root_mean_squared_error: 0.3106 - val_loss: 0.4938 - val_mse: 0.4155 - val_mae: 0.4878 - val_root_mean_squared_error: 0.6446\n", "Epoch 169/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.2224 - mse: 0.1444 - mae: 0.2645 - root_mean_squared_error: 0.3800\n", "Epoch 169: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.2224 - mse: 0.1444 - mae: 0.2645 - root_mean_squared_error: 0.3800 - val_loss: 0.5438 - val_mse: 0.4662 - val_mae: 0.5247 - val_root_mean_squared_error: 0.6828\n", "Epoch 170/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1984 - mse: 0.1212 - mae: 0.2347 - root_mean_squared_error: 0.3482\n", "Epoch 170: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 52ms/step - loss: 0.1984 - mse: 0.1212 - mae: 0.2347 - root_mean_squared_error: 0.3482 - val_loss: 0.5550 - val_mse: 0.4782 - val_mae: 0.5123 - val_root_mean_squared_error: 0.6915\n", "Epoch 171/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.2053 - mse: 0.1289 - mae: 0.2463 - root_mean_squared_error: 0.3590\n", "Epoch 171: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.2053 - mse: 0.1289 - mae: 0.2463 - root_mean_squared_error: 0.3590 - val_loss: 0.4936 - val_mse: 0.4176 - val_mae: 0.4915 - val_root_mean_squared_error: 0.6462\n", "Epoch 172/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1790 - mse: 0.1033 - mae: 0.2208 - root_mean_squared_error: 0.3215\n", "Epoch 172: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.1786 - mse: 0.1029 - mae: 0.2202 - root_mean_squared_error: 0.3208 - val_loss: 0.4836 - val_mse: 0.4084 - val_mae: 0.4797 - val_root_mean_squared_error: 0.6391\n", "Epoch 173/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1617 - mse: 0.0869 - mae: 0.2060 - root_mean_squared_error: 0.2948\n", "Epoch 173: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 56ms/step - loss: 0.1617 - mse: 0.0869 - mae: 0.2060 - root_mean_squared_error: 0.2948 - val_loss: 0.4806 - val_mse: 0.4063 - val_mae: 0.4864 - val_root_mean_squared_error: 0.6374\n", "Epoch 174/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.1358 - mse: 0.0618 - mae: 0.1811 - root_mean_squared_error: 0.2487\n", "Epoch 174: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.1357 - mse: 0.0618 - mae: 0.1814 - root_mean_squared_error: 0.2486 - val_loss: 0.4668 - val_mse: 0.3934 - val_mae: 0.4690 - val_root_mean_squared_error: 0.6272\n", "Epoch 175/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.1332 - mse: 0.0602 - mae: 0.1782 - root_mean_squared_error: 0.2454\n", "Epoch 175: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.1332 - mse: 0.0602 - mae: 0.1786 - root_mean_squared_error: 0.2454 - val_loss: 0.4601 - val_mse: 0.3876 - val_mae: 0.4629 - val_root_mean_squared_error: 0.6226\n", "Epoch 176/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1452 - mse: 0.0731 - mae: 0.1842 - root_mean_squared_error: 0.2704\n", "Epoch 176: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.1449 - mse: 0.0728 - mae: 0.1840 - root_mean_squared_error: 0.2699 - val_loss: 0.5031 - val_mse: 0.4314 - val_mae: 0.4992 - val_root_mean_squared_error: 0.6568\n", "Epoch 177/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1592 - mse: 0.0880 - mae: 0.2024 - root_mean_squared_error: 0.2966\n", "Epoch 177: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.1590 - mse: 0.0878 - mae: 0.2025 - root_mean_squared_error: 0.2963 - val_loss: 0.4771 - val_mse: 0.4063 - val_mae: 0.4766 - val_root_mean_squared_error: 0.6374\n", "Epoch 178/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1570 - mse: 0.0866 - mae: 0.2110 - root_mean_squared_error: 0.2943\n", "Epoch 178: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.1566 - mse: 0.0862 - mae: 0.2104 - root_mean_squared_error: 0.2936 - val_loss: 0.4822 - val_mse: 0.4122 - val_mae: 0.4924 - val_root_mean_squared_error: 0.6420\n", "Epoch 179/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.1301 - mse: 0.0605 - mae: 0.1739 - root_mean_squared_error: 0.2460\n", "Epoch 179: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.1302 - mse: 0.0606 - mae: 0.1741 - root_mean_squared_error: 0.2462 - val_loss: 0.5117 - val_mse: 0.4426 - val_mae: 0.5204 - val_root_mean_squared_error: 0.6653\n", "Epoch 180/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1416 - mse: 0.0728 - mae: 0.1951 - root_mean_squared_error: 0.2698\n", "Epoch 180: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.1412 - mse: 0.0724 - mae: 0.1946 - root_mean_squared_error: 0.2691 - val_loss: 0.4855 - val_mse: 0.4171 - val_mae: 0.4869 - val_root_mean_squared_error: 0.6458\n", "Epoch 181/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1190 - mse: 0.0510 - mae: 0.1633 - root_mean_squared_error: 0.2258\n", "Epoch 181: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.1189 - mse: 0.0509 - mae: 0.1635 - root_mean_squared_error: 0.2257 - val_loss: 0.4744 - val_mse: 0.4069 - val_mae: 0.4894 - val_root_mean_squared_error: 0.6379\n", "Epoch 182/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1117 - mse: 0.0446 - mae: 0.1539 - root_mean_squared_error: 0.2112\n", "Epoch 182: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 5s 66ms/step - loss: 0.1117 - mse: 0.0446 - mae: 0.1539 - root_mean_squared_error: 0.2112 - val_loss: 0.4999 - val_mse: 0.4333 - val_mae: 0.5100 - val_root_mean_squared_error: 0.6582\n", "Epoch 183/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1169 - mse: 0.0507 - mae: 0.1592 - root_mean_squared_error: 0.2251\n", "Epoch 183: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.1167 - mse: 0.0504 - mae: 0.1587 - root_mean_squared_error: 0.2246 - val_loss: 0.4578 - val_mse: 0.3920 - val_mae: 0.4785 - val_root_mean_squared_error: 0.6261\n", "Epoch 184/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1147 - mse: 0.0494 - mae: 0.1616 - root_mean_squared_error: 0.2223\n", "Epoch 184: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.1145 - mse: 0.0491 - mae: 0.1611 - root_mean_squared_error: 0.2217 - val_loss: 0.4538 - val_mse: 0.3889 - val_mae: 0.4750 - val_root_mean_squared_error: 0.6236\n", "Epoch 185/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1243 - mse: 0.0598 - mae: 0.1790 - root_mean_squared_error: 0.2445\n", "Epoch 185: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.1240 - mse: 0.0595 - mae: 0.1786 - root_mean_squared_error: 0.2438 - val_loss: 0.4421 - val_mse: 0.3780 - val_mae: 0.4674 - val_root_mean_squared_error: 0.6148\n", "Epoch 186/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1240 - mse: 0.0603 - mae: 0.1787 - root_mean_squared_error: 0.2456\n", "Epoch 186: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.1240 - mse: 0.0603 - mae: 0.1787 - root_mean_squared_error: 0.2456 - val_loss: 0.4510 - val_mse: 0.3876 - val_mae: 0.4716 - val_root_mean_squared_error: 0.6226\n", "Epoch 187/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1468 - mse: 0.0838 - mae: 0.2057 - root_mean_squared_error: 0.2895\n", "Epoch 187: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.1468 - mse: 0.0838 - mae: 0.2057 - root_mean_squared_error: 0.2895 - val_loss: 0.4514 - val_mse: 0.3888 - val_mae: 0.4849 - val_root_mean_squared_error: 0.6235\n", "Epoch 188/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1833 - mse: 0.1209 - mae: 0.2357 - root_mean_squared_error: 0.3477\n", "Epoch 188: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.1833 - mse: 0.1209 - mae: 0.2357 - root_mean_squared_error: 0.3477 - val_loss: 0.5211 - val_mse: 0.4590 - val_mae: 0.4986 - val_root_mean_squared_error: 0.6775\n", "Epoch 189/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1754 - mse: 0.1135 - mae: 0.2210 - root_mean_squared_error: 0.3369\n", "Epoch 189: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.1754 - mse: 0.1135 - mae: 0.2210 - root_mean_squared_error: 0.3369 - val_loss: 0.4728 - val_mse: 0.4112 - val_mae: 0.4876 - val_root_mean_squared_error: 0.6413\n", "Epoch 190/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.2129 - mse: 0.1516 - mae: 0.2534 - root_mean_squared_error: 0.3893\n", "Epoch 190: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.2115 - mse: 0.1501 - mae: 0.2529 - root_mean_squared_error: 0.3874 - val_loss: 0.4525 - val_mse: 0.3913 - val_mae: 0.4811 - val_root_mean_squared_error: 0.6255\n", "Epoch 191/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1964 - mse: 0.1355 - mae: 0.2590 - root_mean_squared_error: 0.3681\n", "Epoch 191: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.1965 - mse: 0.1356 - mae: 0.2594 - root_mean_squared_error: 0.3682 - val_loss: 0.4807 - val_mse: 0.4200 - val_mae: 0.4844 - val_root_mean_squared_error: 0.6481\n", "Epoch 192/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1448 - mse: 0.0844 - mae: 0.2057 - root_mean_squared_error: 0.2905\n", "Epoch 192: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.1446 - mse: 0.0842 - mae: 0.2058 - root_mean_squared_error: 0.2902 - val_loss: 0.5190 - val_mse: 0.4589 - val_mae: 0.5085 - val_root_mean_squared_error: 0.6774\n", "Epoch 193/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1198 - mse: 0.0601 - mae: 0.1721 - root_mean_squared_error: 0.2452\n", "Epoch 193: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 0.1198 - mse: 0.0601 - mae: 0.1721 - root_mean_squared_error: 0.2452 - val_loss: 0.4281 - val_mse: 0.3688 - val_mae: 0.4646 - val_root_mean_squared_error: 0.6073\n", "Epoch 194/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1189 - mse: 0.0600 - mae: 0.1732 - root_mean_squared_error: 0.2449\n", "Epoch 194: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 50ms/step - loss: 0.1189 - mse: 0.0600 - mae: 0.1732 - root_mean_squared_error: 0.2449 - val_loss: 0.4611 - val_mse: 0.4025 - val_mae: 0.4803 - val_root_mean_squared_error: 0.6344\n", "Epoch 195/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1266 - mse: 0.0684 - mae: 0.1902 - root_mean_squared_error: 0.2615\n", "Epoch 195: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 57ms/step - loss: 0.1266 - mse: 0.0684 - mae: 0.1902 - root_mean_squared_error: 0.2615 - val_loss: 0.5276 - val_mse: 0.4696 - val_mae: 0.5449 - val_root_mean_squared_error: 0.6853\n", "Epoch 196/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1038 - mse: 0.0462 - mae: 0.1599 - root_mean_squared_error: 0.2149\n", "Epoch 196: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.1038 - mse: 0.0462 - mae: 0.1599 - root_mean_squared_error: 0.2149 - val_loss: 0.4540 - val_mse: 0.3968 - val_mae: 0.4761 - val_root_mean_squared_error: 0.6299\n", "Epoch 197/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0989 - mse: 0.0421 - mae: 0.1492 - root_mean_squared_error: 0.2052\n", "Epoch 197: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0989 - mse: 0.0421 - mae: 0.1492 - root_mean_squared_error: 0.2052 - val_loss: 0.4360 - val_mse: 0.3796 - val_mae: 0.4700 - val_root_mean_squared_error: 0.6161\n", "Epoch 198/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1046 - mse: 0.0485 - mae: 0.1530 - root_mean_squared_error: 0.2203\n", "Epoch 198: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.1046 - mse: 0.0485 - mae: 0.1530 - root_mean_squared_error: 0.2203 - val_loss: 0.4531 - val_mse: 0.3974 - val_mae: 0.4741 - val_root_mean_squared_error: 0.6304\n", "Epoch 199/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1913 - mse: 0.1359 - mae: 0.2371 - root_mean_squared_error: 0.3686\n", "Epoch 199: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.1904 - mse: 0.1350 - mae: 0.2362 - root_mean_squared_error: 0.3674 - val_loss: 0.4832 - val_mse: 0.4279 - val_mae: 0.5000 - val_root_mean_squared_error: 0.6542\n", "Epoch 200/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1715 - mse: 0.1165 - mae: 0.2261 - root_mean_squared_error: 0.3414\n", "Epoch 200: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.1715 - mse: 0.1165 - mae: 0.2261 - root_mean_squared_error: 0.3414 - val_loss: 0.4796 - val_mse: 0.4248 - val_mae: 0.5152 - val_root_mean_squared_error: 0.6518\n", "Epoch 201/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1412 - mse: 0.0867 - mae: 0.1987 - root_mean_squared_error: 0.2944\n", "Epoch 201: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.1412 - mse: 0.0867 - mae: 0.1987 - root_mean_squared_error: 0.2944 - val_loss: 0.4730 - val_mse: 0.4187 - val_mae: 0.4998 - val_root_mean_squared_error: 0.6471\n", "Epoch 202/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1524 - mse: 0.0984 - mae: 0.2217 - root_mean_squared_error: 0.3136\n", "Epoch 202: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.1524 - mse: 0.0984 - mae: 0.2217 - root_mean_squared_error: 0.3136 - val_loss: 0.4663 - val_mse: 0.4126 - val_mae: 0.4882 - val_root_mean_squared_error: 0.6423\n", "Epoch 203/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1427 - mse: 0.0892 - mae: 0.1980 - root_mean_squared_error: 0.2986\n", "Epoch 203: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.1427 - mse: 0.0892 - mae: 0.1980 - root_mean_squared_error: 0.2986 - val_loss: 0.4420 - val_mse: 0.3887 - val_mae: 0.4641 - val_root_mean_squared_error: 0.6235\n", "Epoch 204/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1320 - mse: 0.0790 - mae: 0.1934 - root_mean_squared_error: 0.2811\n", "Epoch 204: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.1341 - mse: 0.0810 - mae: 0.1947 - root_mean_squared_error: 0.2846 - val_loss: 0.4554 - val_mse: 0.4026 - val_mae: 0.4785 - val_root_mean_squared_error: 0.6345\n", "Epoch 205/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1357 - mse: 0.0831 - mae: 0.1929 - root_mean_squared_error: 0.2883\n", "Epoch 205: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.1357 - mse: 0.0831 - mae: 0.1929 - root_mean_squared_error: 0.2883 - val_loss: 0.4699 - val_mse: 0.4176 - val_mae: 0.4810 - val_root_mean_squared_error: 0.6462\n", "Epoch 206/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1091 - mse: 0.0570 - mae: 0.1675 - root_mean_squared_error: 0.2388\n", "Epoch 206: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.1089 - mse: 0.0569 - mae: 0.1674 - root_mean_squared_error: 0.2385 - val_loss: 0.4538 - val_mse: 0.4021 - val_mae: 0.4821 - val_root_mean_squared_error: 0.6341\n", "Epoch 207/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1231 - mse: 0.0716 - mae: 0.1835 - root_mean_squared_error: 0.2677\n", "Epoch 207: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.1231 - mse: 0.0717 - mae: 0.1839 - root_mean_squared_error: 0.2677 - val_loss: 0.4397 - val_mse: 0.3885 - val_mae: 0.4682 - val_root_mean_squared_error: 0.6233\n", "Epoch 208/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1015 - mse: 0.0506 - mae: 0.1622 - root_mean_squared_error: 0.2250\n", "Epoch 208: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.1015 - mse: 0.0506 - mae: 0.1622 - root_mean_squared_error: 0.2250 - val_loss: 0.4613 - val_mse: 0.4108 - val_mae: 0.4840 - val_root_mean_squared_error: 0.6409\n", "Epoch 209/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0982 - mse: 0.0480 - mae: 0.1556 - root_mean_squared_error: 0.2191\n", "Epoch 209: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 56ms/step - loss: 0.0982 - mse: 0.0480 - mae: 0.1556 - root_mean_squared_error: 0.2191 - val_loss: 0.4386 - val_mse: 0.3887 - val_mae: 0.4746 - val_root_mean_squared_error: 0.6235\n", "Epoch 210/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0982 - mse: 0.0487 - mae: 0.1592 - root_mean_squared_error: 0.2206\n", "Epoch 210: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0979 - mse: 0.0484 - mae: 0.1585 - root_mean_squared_error: 0.2199 - val_loss: 0.4572 - val_mse: 0.4080 - val_mae: 0.4908 - val_root_mean_squared_error: 0.6387\n", "Epoch 211/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0924 - mse: 0.0434 - mae: 0.1475 - root_mean_squared_error: 0.2084\n", "Epoch 211: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0924 - mse: 0.0434 - mae: 0.1475 - root_mean_squared_error: 0.2084 - val_loss: 0.4425 - val_mse: 0.3939 - val_mae: 0.4636 - val_root_mean_squared_error: 0.6276\n", "Epoch 212/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0953 - mse: 0.0470 - mae: 0.1573 - root_mean_squared_error: 0.2169\n", "Epoch 212: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0953 - mse: 0.0470 - mae: 0.1573 - root_mean_squared_error: 0.2169 - val_loss: 0.4573 - val_mse: 0.4093 - val_mae: 0.4940 - val_root_mean_squared_error: 0.6398\n", "Epoch 213/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1065 - mse: 0.0588 - mae: 0.1725 - root_mean_squared_error: 0.2425\n", "Epoch 213: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.1065 - mse: 0.0588 - mae: 0.1725 - root_mean_squared_error: 0.2425 - val_loss: 0.4733 - val_mse: 0.4258 - val_mae: 0.4887 - val_root_mean_squared_error: 0.6525\n", "Epoch 214/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1117 - mse: 0.0645 - mae: 0.1762 - root_mean_squared_error: 0.2540\n", "Epoch 214: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.1115 - mse: 0.0643 - mae: 0.1759 - root_mean_squared_error: 0.2536 - val_loss: 0.4226 - val_mse: 0.3757 - val_mae: 0.4683 - val_root_mean_squared_error: 0.6129\n", "Epoch 215/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1014 - mse: 0.0548 - mae: 0.1559 - root_mean_squared_error: 0.2340\n", "Epoch 215: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 50ms/step - loss: 0.1011 - mse: 0.0545 - mae: 0.1555 - root_mean_squared_error: 0.2334 - val_loss: 0.4773 - val_mse: 0.4310 - val_mae: 0.4961 - val_root_mean_squared_error: 0.6565\n", "Epoch 216/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1520 - mse: 0.1059 - mae: 0.2130 - root_mean_squared_error: 0.3254\n", "Epoch 216: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.1520 - mse: 0.1059 - mae: 0.2133 - root_mean_squared_error: 0.3254 - val_loss: 0.4534 - val_mse: 0.4074 - val_mae: 0.4960 - val_root_mean_squared_error: 0.6383\n", "Epoch 217/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1266 - mse: 0.0809 - mae: 0.1915 - root_mean_squared_error: 0.2844\n", "Epoch 217: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.1265 - mse: 0.0808 - mae: 0.1914 - root_mean_squared_error: 0.2843 - val_loss: 0.5538 - val_mse: 0.5083 - val_mae: 0.5283 - val_root_mean_squared_error: 0.7129\n", "Epoch 218/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.1817 - mse: 0.1364 - mae: 0.2565 - root_mean_squared_error: 0.3693\n", "Epoch 218: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.1804 - mse: 0.1351 - mae: 0.2551 - root_mean_squared_error: 0.3675 - val_loss: 0.4139 - val_mse: 0.3687 - val_mae: 0.4565 - val_root_mean_squared_error: 0.6072\n", "Epoch 219/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1263 - mse: 0.0812 - mae: 0.1856 - root_mean_squared_error: 0.2850\n", "Epoch 219: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.1262 - mse: 0.0811 - mae: 0.1856 - root_mean_squared_error: 0.2849 - val_loss: 0.4910 - val_mse: 0.4462 - val_mae: 0.4956 - val_root_mean_squared_error: 0.6680\n", "Epoch 220/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.1383 - mse: 0.0936 - mae: 0.1987 - root_mean_squared_error: 0.3059\n", "Epoch 220: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.1379 - mse: 0.0932 - mae: 0.1986 - root_mean_squared_error: 0.3053 - val_loss: 0.4548 - val_mse: 0.4103 - val_mae: 0.4886 - val_root_mean_squared_error: 0.6405\n", "Epoch 221/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1104 - mse: 0.0661 - mae: 0.1754 - root_mean_squared_error: 0.2572\n", "Epoch 221: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.1104 - mse: 0.0661 - mae: 0.1754 - root_mean_squared_error: 0.2572 - val_loss: 0.4657 - val_mse: 0.4216 - val_mae: 0.4905 - val_root_mean_squared_error: 0.6493\n", "Epoch 222/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.2042 - mse: 0.1603 - mae: 0.2514 - root_mean_squared_error: 0.4003\n", "Epoch 222: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 59ms/step - loss: 0.2023 - mse: 0.1583 - mae: 0.2502 - root_mean_squared_error: 0.3979 - val_loss: 0.4228 - val_mse: 0.3789 - val_mae: 0.4713 - val_root_mean_squared_error: 0.6156\n", "Epoch 223/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.1048 - mse: 0.0611 - mae: 0.1752 - root_mean_squared_error: 0.2472\n", "Epoch 223: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.1043 - mse: 0.0606 - mae: 0.1746 - root_mean_squared_error: 0.2463 - val_loss: 0.4391 - val_mse: 0.3957 - val_mae: 0.4781 - val_root_mean_squared_error: 0.6290\n", "Epoch 224/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0925 - mse: 0.0492 - mae: 0.1628 - root_mean_squared_error: 0.2219\n", "Epoch 224: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0927 - mse: 0.0494 - mae: 0.1630 - root_mean_squared_error: 0.2223 - val_loss: 0.4404 - val_mse: 0.3973 - val_mae: 0.4737 - val_root_mean_squared_error: 0.6303\n", "Epoch 225/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0878 - mse: 0.0450 - mae: 0.1528 - root_mean_squared_error: 0.2121\n", "Epoch 225: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0875 - mse: 0.0447 - mae: 0.1525 - root_mean_squared_error: 0.2115 - val_loss: 0.4563 - val_mse: 0.4137 - val_mae: 0.4780 - val_root_mean_squared_error: 0.6432\n", "Epoch 226/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0912 - mse: 0.0489 - mae: 0.1594 - root_mean_squared_error: 0.2212\n", "Epoch 226: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0912 - mse: 0.0489 - mae: 0.1594 - root_mean_squared_error: 0.2212 - val_loss: 0.4763 - val_mse: 0.4343 - val_mae: 0.5012 - val_root_mean_squared_error: 0.6590\n", "Epoch 227/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0875 - mse: 0.0457 - mae: 0.1583 - root_mean_squared_error: 0.2138\n", "Epoch 227: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0875 - mse: 0.0457 - mae: 0.1583 - root_mean_squared_error: 0.2138 - val_loss: 0.4327 - val_mse: 0.3911 - val_mae: 0.4695 - val_root_mean_squared_error: 0.6254\n", "Epoch 228/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0837 - mse: 0.0424 - mae: 0.1509 - root_mean_squared_error: 0.2060\n", "Epoch 228: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0836 - mse: 0.0423 - mae: 0.1508 - root_mean_squared_error: 0.2057 - val_loss: 0.4498 - val_mse: 0.4087 - val_mae: 0.4810 - val_root_mean_squared_error: 0.6393\n", "Epoch 229/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0845 - mse: 0.0437 - mae: 0.1504 - root_mean_squared_error: 0.2090\n", "Epoch 229: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 53ms/step - loss: 0.0845 - mse: 0.0437 - mae: 0.1504 - root_mean_squared_error: 0.2090 - val_loss: 0.4576 - val_mse: 0.4171 - val_mae: 0.4908 - val_root_mean_squared_error: 0.6458\n", "Epoch 230/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0915 - mse: 0.0512 - mae: 0.1568 - root_mean_squared_error: 0.2264\n", "Epoch 230: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0915 - mse: 0.0512 - mae: 0.1568 - root_mean_squared_error: 0.2264 - val_loss: 0.4876 - val_mse: 0.4476 - val_mae: 0.5111 - val_root_mean_squared_error: 0.6690\n", "Epoch 231/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0843 - mse: 0.0445 - mae: 0.1514 - root_mean_squared_error: 0.2109\n", "Epoch 231: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0841 - mse: 0.0442 - mae: 0.1510 - root_mean_squared_error: 0.2103 - val_loss: 0.4448 - val_mse: 0.4052 - val_mae: 0.4717 - val_root_mean_squared_error: 0.6365\n", "Epoch 232/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0844 - mse: 0.0450 - mae: 0.1507 - root_mean_squared_error: 0.2122\n", "Epoch 232: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0844 - mse: 0.0450 - mae: 0.1507 - root_mean_squared_error: 0.2122 - val_loss: 0.4576 - val_mse: 0.4185 - val_mae: 0.4803 - val_root_mean_squared_error: 0.6469\n", "Epoch 233/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0844 - mse: 0.0455 - mae: 0.1568 - root_mean_squared_error: 0.2134\n", "Epoch 233: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 58ms/step - loss: 0.0842 - mse: 0.0453 - mae: 0.1565 - root_mean_squared_error: 0.2129 - val_loss: 0.4466 - val_mse: 0.4079 - val_mae: 0.4828 - val_root_mean_squared_error: 0.6387\n", "Epoch 234/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0869 - mse: 0.0484 - mae: 0.1631 - root_mean_squared_error: 0.2201\n", "Epoch 234: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0868 - mse: 0.0483 - mae: 0.1628 - root_mean_squared_error: 0.2198 - val_loss: 0.4555 - val_mse: 0.4173 - val_mae: 0.4810 - val_root_mean_squared_error: 0.6460\n", "Epoch 235/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0854 - mse: 0.0474 - mae: 0.1587 - root_mean_squared_error: 0.2177\n", "Epoch 235: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0854 - mse: 0.0474 - mae: 0.1587 - root_mean_squared_error: 0.2177 - val_loss: 0.4539 - val_mse: 0.4160 - val_mae: 0.4857 - val_root_mean_squared_error: 0.6450\n", "Epoch 236/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0836 - mse: 0.0460 - mae: 0.1562 - root_mean_squared_error: 0.2144\n", "Epoch 236: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0836 - mse: 0.0460 - mae: 0.1562 - root_mean_squared_error: 0.2144 - val_loss: 0.4566 - val_mse: 0.4192 - val_mae: 0.4820 - val_root_mean_squared_error: 0.6475\n", "Epoch 237/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0824 - mse: 0.0452 - mae: 0.1528 - root_mean_squared_error: 0.2126\n", "Epoch 237: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0823 - mse: 0.0451 - mae: 0.1526 - root_mean_squared_error: 0.2124 - val_loss: 0.4589 - val_mse: 0.4219 - val_mae: 0.5014 - val_root_mean_squared_error: 0.6495\n", "Epoch 238/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0840 - mse: 0.0472 - mae: 0.1533 - root_mean_squared_error: 0.2172\n", "Epoch 238: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0840 - mse: 0.0472 - mae: 0.1533 - root_mean_squared_error: 0.2172 - val_loss: 0.4607 - val_mse: 0.4241 - val_mae: 0.4890 - val_root_mean_squared_error: 0.6512\n", "Epoch 239/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1047 - mse: 0.0683 - mae: 0.1788 - root_mean_squared_error: 0.2613\n", "Epoch 239: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.1047 - mse: 0.0683 - mae: 0.1788 - root_mean_squared_error: 0.2613 - val_loss: 0.4988 - val_mse: 0.4626 - val_mae: 0.5112 - val_root_mean_squared_error: 0.6802\n", "Epoch 240/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1191 - mse: 0.0829 - mae: 0.2027 - root_mean_squared_error: 0.2880\n", "Epoch 240: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.1191 - mse: 0.0829 - mae: 0.2027 - root_mean_squared_error: 0.2880 - val_loss: 0.4344 - val_mse: 0.3983 - val_mae: 0.4685 - val_root_mean_squared_error: 0.6311\n", "Epoch 241/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1109 - mse: 0.0749 - mae: 0.1805 - root_mean_squared_error: 0.2737\n", "Epoch 241: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.1109 - mse: 0.0749 - mae: 0.1805 - root_mean_squared_error: 0.2737 - val_loss: 0.4177 - val_mse: 0.3820 - val_mae: 0.4732 - val_root_mean_squared_error: 0.6180\n", "Epoch 242/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1275 - mse: 0.0918 - mae: 0.1989 - root_mean_squared_error: 0.3030\n", "Epoch 242: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.1275 - mse: 0.0918 - mae: 0.1989 - root_mean_squared_error: 0.3030 - val_loss: 0.4621 - val_mse: 0.4265 - val_mae: 0.4828 - val_root_mean_squared_error: 0.6531\n", "Epoch 243/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.1078 - mse: 0.0724 - mae: 0.1866 - root_mean_squared_error: 0.2690\n", "Epoch 243: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.1078 - mse: 0.0724 - mae: 0.1866 - root_mean_squared_error: 0.2690 - val_loss: 0.4417 - val_mse: 0.4064 - val_mae: 0.4810 - val_root_mean_squared_error: 0.6375\n", "Epoch 244/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0914 - mse: 0.0563 - mae: 0.1674 - root_mean_squared_error: 0.2373\n", "Epoch 244: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 50ms/step - loss: 0.0914 - mse: 0.0563 - mae: 0.1674 - root_mean_squared_error: 0.2373 - val_loss: 0.4329 - val_mse: 0.3979 - val_mae: 0.4788 - val_root_mean_squared_error: 0.6308\n", "Epoch 245/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0880 - mse: 0.0532 - mae: 0.1601 - root_mean_squared_error: 0.2307\n", "Epoch 245: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 0.0880 - mse: 0.0532 - mae: 0.1601 - root_mean_squared_error: 0.2307 - val_loss: 0.4191 - val_mse: 0.3845 - val_mae: 0.4741 - val_root_mean_squared_error: 0.6201\n", "Epoch 246/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0850 - mse: 0.0506 - mae: 0.1584 - root_mean_squared_error: 0.2249\n", "Epoch 246: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 51ms/step - loss: 0.0850 - mse: 0.0506 - mae: 0.1584 - root_mean_squared_error: 0.2249 - val_loss: 0.4317 - val_mse: 0.3975 - val_mae: 0.4735 - val_root_mean_squared_error: 0.6305\n", "Epoch 247/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0870 - mse: 0.0529 - mae: 0.1699 - root_mean_squared_error: 0.2300\n", "Epoch 247: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0902 - mse: 0.0560 - mae: 0.1710 - root_mean_squared_error: 0.2367 - val_loss: 0.4337 - val_mse: 0.3997 - val_mae: 0.4748 - val_root_mean_squared_error: 0.6322\n", "Epoch 248/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0851 - mse: 0.0512 - mae: 0.1632 - root_mean_squared_error: 0.2263\n", "Epoch 248: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 0.0855 - mse: 0.0516 - mae: 0.1638 - root_mean_squared_error: 0.2271 - val_loss: 0.4380 - val_mse: 0.4043 - val_mae: 0.4807 - val_root_mean_squared_error: 0.6358\n", "Epoch 249/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0905 - mse: 0.0569 - mae: 0.1744 - root_mean_squared_error: 0.2386\n", "Epoch 249: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 48ms/step - loss: 0.0904 - mse: 0.0569 - mae: 0.1745 - root_mean_squared_error: 0.2385 - val_loss: 0.5120 - val_mse: 0.4786 - val_mae: 0.5316 - val_root_mean_squared_error: 0.6918\n", "Epoch 250/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0828 - mse: 0.0495 - mae: 0.1628 - root_mean_squared_error: 0.2226\n", "Epoch 250: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0828 - mse: 0.0495 - mae: 0.1628 - root_mean_squared_error: 0.2226 - val_loss: 0.4286 - val_mse: 0.3954 - val_mae: 0.4775 - val_root_mean_squared_error: 0.6288\n", "Epoch 251/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0839 - mse: 0.0509 - mae: 0.1611 - root_mean_squared_error: 0.2257\n", "Epoch 251: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0838 - mse: 0.0508 - mae: 0.1610 - root_mean_squared_error: 0.2254 - val_loss: 0.4231 - val_mse: 0.3903 - val_mae: 0.4707 - val_root_mean_squared_error: 0.6247\n", "Epoch 252/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0702 - mse: 0.0376 - mae: 0.1404 - root_mean_squared_error: 0.1938\n", "Epoch 252: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0704 - mse: 0.0378 - mae: 0.1411 - root_mean_squared_error: 0.1944 - val_loss: 0.4581 - val_mse: 0.4256 - val_mae: 0.4912 - val_root_mean_squared_error: 0.6524\n", "Epoch 253/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0756 - mse: 0.0432 - mae: 0.1505 - root_mean_squared_error: 0.2079\n", "Epoch 253: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0755 - mse: 0.0432 - mae: 0.1505 - root_mean_squared_error: 0.2079 - val_loss: 0.4248 - val_mse: 0.3926 - val_mae: 0.4802 - val_root_mean_squared_error: 0.6266\n", "Epoch 254/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0782 - mse: 0.0462 - mae: 0.1534 - root_mean_squared_error: 0.2150\n", "Epoch 254: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0782 - mse: 0.0462 - mae: 0.1534 - root_mean_squared_error: 0.2150 - val_loss: 0.4760 - val_mse: 0.4441 - val_mae: 0.4996 - val_root_mean_squared_error: 0.6664\n", "Epoch 255/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0804 - mse: 0.0487 - mae: 0.1558 - root_mean_squared_error: 0.2207\n", "Epoch 255: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0804 - mse: 0.0487 - mae: 0.1558 - root_mean_squared_error: 0.2207 - val_loss: 0.4241 - val_mse: 0.3925 - val_mae: 0.4743 - val_root_mean_squared_error: 0.6265\n", "Epoch 256/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0788 - mse: 0.0474 - mae: 0.1531 - root_mean_squared_error: 0.2178\n", "Epoch 256: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0788 - mse: 0.0474 - mae: 0.1531 - root_mean_squared_error: 0.2178 - val_loss: 0.4525 - val_mse: 0.4213 - val_mae: 0.4879 - val_root_mean_squared_error: 0.6491\n", "Epoch 257/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0809 - mse: 0.0498 - mae: 0.1625 - root_mean_squared_error: 0.2232\n", "Epoch 257: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0809 - mse: 0.0498 - mae: 0.1625 - root_mean_squared_error: 0.2232 - val_loss: 0.4099 - val_mse: 0.3789 - val_mae: 0.4592 - val_root_mean_squared_error: 0.6156\n", "Epoch 258/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0858 - mse: 0.0550 - mae: 0.1633 - root_mean_squared_error: 0.2346\n", "Epoch 258: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0857 - mse: 0.0549 - mae: 0.1633 - root_mean_squared_error: 0.2342 - val_loss: 0.5020 - val_mse: 0.4714 - val_mae: 0.5157 - val_root_mean_squared_error: 0.6866\n", "Epoch 259/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0894 - mse: 0.0588 - mae: 0.1648 - root_mean_squared_error: 0.2426\n", "Epoch 259: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 54ms/step - loss: 0.0897 - mse: 0.0592 - mae: 0.1655 - root_mean_squared_error: 0.2433 - val_loss: 0.4642 - val_mse: 0.4339 - val_mae: 0.4869 - val_root_mean_squared_error: 0.6587\n", "Epoch 260/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0945 - mse: 0.0642 - mae: 0.1716 - root_mean_squared_error: 0.2534\n", "Epoch 260: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0936 - mse: 0.0633 - mae: 0.1703 - root_mean_squared_error: 0.2516 - val_loss: 0.4352 - val_mse: 0.4050 - val_mae: 0.4839 - val_root_mean_squared_error: 0.6364\n", "Epoch 261/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0784 - mse: 0.0483 - mae: 0.1516 - root_mean_squared_error: 0.2198\n", "Epoch 261: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0784 - mse: 0.0483 - mae: 0.1518 - root_mean_squared_error: 0.2198 - val_loss: 0.4301 - val_mse: 0.4001 - val_mae: 0.4800 - val_root_mean_squared_error: 0.6325\n", "Epoch 262/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0796 - mse: 0.0498 - mae: 0.1607 - root_mean_squared_error: 0.2232\n", "Epoch 262: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0795 - mse: 0.0497 - mae: 0.1607 - root_mean_squared_error: 0.2229 - val_loss: 0.4464 - val_mse: 0.4167 - val_mae: 0.4885 - val_root_mean_squared_error: 0.6455\n", "Epoch 263/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0695 - mse: 0.0399 - mae: 0.1406 - root_mean_squared_error: 0.1998\n", "Epoch 263: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0693 - mse: 0.0397 - mae: 0.1402 - root_mean_squared_error: 0.1993 - val_loss: 0.4204 - val_mse: 0.3910 - val_mae: 0.4639 - val_root_mean_squared_error: 0.6253\n", "Epoch 264/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0677 - mse: 0.0385 - mae: 0.1420 - root_mean_squared_error: 0.1961\n", "Epoch 264: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0678 - mse: 0.0386 - mae: 0.1426 - root_mean_squared_error: 0.1965 - val_loss: 0.4257 - val_mse: 0.3967 - val_mae: 0.4701 - val_root_mean_squared_error: 0.6298\n", "Epoch 265/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0659 - mse: 0.0370 - mae: 0.1374 - root_mean_squared_error: 0.1922\n", "Epoch 265: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0659 - mse: 0.0370 - mae: 0.1374 - root_mean_squared_error: 0.1922 - val_loss: 0.4511 - val_mse: 0.4223 - val_mae: 0.4813 - val_root_mean_squared_error: 0.6499\n", "Epoch 266/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0746 - mse: 0.0459 - mae: 0.1573 - root_mean_squared_error: 0.2142\n", "Epoch 266: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0750 - mse: 0.0463 - mae: 0.1579 - root_mean_squared_error: 0.2153 - val_loss: 0.4534 - val_mse: 0.4249 - val_mae: 0.4911 - val_root_mean_squared_error: 0.6518\n", "Epoch 267/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0749 - mse: 0.0464 - mae: 0.1570 - root_mean_squared_error: 0.2155\n", "Epoch 267: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 48ms/step - loss: 0.0749 - mse: 0.0464 - mae: 0.1570 - root_mean_squared_error: 0.2155 - val_loss: 0.4549 - val_mse: 0.4266 - val_mae: 0.4891 - val_root_mean_squared_error: 0.6531\n", "Epoch 268/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0724 - mse: 0.0442 - mae: 0.1507 - root_mean_squared_error: 0.2102\n", "Epoch 268: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0724 - mse: 0.0442 - mae: 0.1509 - root_mean_squared_error: 0.2103 - val_loss: 0.4616 - val_mse: 0.4335 - val_mae: 0.5017 - val_root_mean_squared_error: 0.6584\n", "Epoch 269/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0762 - mse: 0.0483 - mae: 0.1566 - root_mean_squared_error: 0.2197\n", "Epoch 269: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0762 - mse: 0.0483 - mae: 0.1566 - root_mean_squared_error: 0.2197 - val_loss: 0.4746 - val_mse: 0.4468 - val_mae: 0.5058 - val_root_mean_squared_error: 0.6684\n", "Epoch 270/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0898 - mse: 0.0620 - mae: 0.1704 - root_mean_squared_error: 0.2490\n", "Epoch 270: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0898 - mse: 0.0620 - mae: 0.1704 - root_mean_squared_error: 0.2490 - val_loss: 0.4280 - val_mse: 0.4003 - val_mae: 0.4756 - val_root_mean_squared_error: 0.6327\n", "Epoch 271/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0746 - mse: 0.0470 - mae: 0.1534 - root_mean_squared_error: 0.2169\n", "Epoch 271: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0746 - mse: 0.0470 - mae: 0.1534 - root_mean_squared_error: 0.2169 - val_loss: 0.4316 - val_mse: 0.4041 - val_mae: 0.4766 - val_root_mean_squared_error: 0.6357\n", "Epoch 272/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0701 - mse: 0.0427 - mae: 0.1501 - root_mean_squared_error: 0.2067\n", "Epoch 272: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0701 - mse: 0.0427 - mae: 0.1501 - root_mean_squared_error: 0.2067 - val_loss: 0.3991 - val_mse: 0.3718 - val_mae: 0.4606 - val_root_mean_squared_error: 0.6098\n", "Epoch 273/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0738 - mse: 0.0467 - mae: 0.1553 - root_mean_squared_error: 0.2161\n", "Epoch 273: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 52ms/step - loss: 0.0738 - mse: 0.0467 - mae: 0.1553 - root_mean_squared_error: 0.2161 - val_loss: 0.4568 - val_mse: 0.4297 - val_mae: 0.4961 - val_root_mean_squared_error: 0.6555\n", "Epoch 274/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0837 - mse: 0.0567 - mae: 0.1652 - root_mean_squared_error: 0.2381\n", "Epoch 274: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 51ms/step - loss: 0.0837 - mse: 0.0567 - mae: 0.1652 - root_mean_squared_error: 0.2381 - val_loss: 0.4221 - val_mse: 0.3952 - val_mae: 0.4751 - val_root_mean_squared_error: 0.6287\n", "Epoch 275/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0774 - mse: 0.0507 - mae: 0.1564 - root_mean_squared_error: 0.2252\n", "Epoch 275: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0774 - mse: 0.0507 - mae: 0.1564 - root_mean_squared_error: 0.2252 - val_loss: 0.4250 - val_mse: 0.3983 - val_mae: 0.4825 - val_root_mean_squared_error: 0.6311\n", "Epoch 276/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0836 - mse: 0.0570 - mae: 0.1700 - root_mean_squared_error: 0.2388\n", "Epoch 276: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0836 - mse: 0.0570 - mae: 0.1700 - root_mean_squared_error: 0.2388 - val_loss: 0.4294 - val_mse: 0.4029 - val_mae: 0.4783 - val_root_mean_squared_error: 0.6348\n", "Epoch 277/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0761 - mse: 0.0498 - mae: 0.1569 - root_mean_squared_error: 0.2231\n", "Epoch 277: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0761 - mse: 0.0498 - mae: 0.1569 - root_mean_squared_error: 0.2231 - val_loss: 0.4409 - val_mse: 0.4146 - val_mae: 0.4860 - val_root_mean_squared_error: 0.6439\n", "Epoch 278/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0777 - mse: 0.0515 - mae: 0.1587 - root_mean_squared_error: 0.2270\n", "Epoch 278: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0774 - mse: 0.0513 - mae: 0.1580 - root_mean_squared_error: 0.2264 - val_loss: 0.4096 - val_mse: 0.3835 - val_mae: 0.4632 - val_root_mean_squared_error: 0.6193\n", "Epoch 279/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0865 - mse: 0.0605 - mae: 0.1753 - root_mean_squared_error: 0.2460\n", "Epoch 279: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 48ms/step - loss: 0.0868 - mse: 0.0608 - mae: 0.1760 - root_mean_squared_error: 0.2466 - val_loss: 0.4803 - val_mse: 0.4544 - val_mae: 0.4947 - val_root_mean_squared_error: 0.6741\n", "Epoch 280/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0916 - mse: 0.0657 - mae: 0.1754 - root_mean_squared_error: 0.2564\n", "Epoch 280: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0913 - mse: 0.0654 - mae: 0.1750 - root_mean_squared_error: 0.2558 - val_loss: 0.4347 - val_mse: 0.4089 - val_mae: 0.4795 - val_root_mean_squared_error: 0.6394\n", "Epoch 281/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0950 - mse: 0.0692 - mae: 0.1827 - root_mean_squared_error: 0.2630\n", "Epoch 281: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0950 - mse: 0.0692 - mae: 0.1830 - root_mean_squared_error: 0.2630 - val_loss: 0.4302 - val_mse: 0.4044 - val_mae: 0.4775 - val_root_mean_squared_error: 0.6360\n", "Epoch 282/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0765 - mse: 0.0508 - mae: 0.1643 - root_mean_squared_error: 0.2254\n", "Epoch 282: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0781 - mse: 0.0524 - mae: 0.1664 - root_mean_squared_error: 0.2290 - val_loss: 0.4257 - val_mse: 0.4001 - val_mae: 0.4754 - val_root_mean_squared_error: 0.6326\n", "Epoch 283/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0770 - mse: 0.0515 - mae: 0.1601 - root_mean_squared_error: 0.2269\n", "Epoch 283: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0768 - mse: 0.0513 - mae: 0.1599 - root_mean_squared_error: 0.2264 - val_loss: 0.4349 - val_mse: 0.4095 - val_mae: 0.4891 - val_root_mean_squared_error: 0.6399\n", "Epoch 284/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0692 - mse: 0.0439 - mae: 0.1495 - root_mean_squared_error: 0.2096\n", "Epoch 284: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 61ms/step - loss: 0.0695 - mse: 0.0442 - mae: 0.1500 - root_mean_squared_error: 0.2102 - val_loss: 0.4111 - val_mse: 0.3859 - val_mae: 0.4651 - val_root_mean_squared_error: 0.6212\n", "Epoch 285/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0652 - mse: 0.0401 - mae: 0.1412 - root_mean_squared_error: 0.2003\n", "Epoch 285: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0652 - mse: 0.0401 - mae: 0.1412 - root_mean_squared_error: 0.2003 - val_loss: 0.4273 - val_mse: 0.4024 - val_mae: 0.4675 - val_root_mean_squared_error: 0.6343\n", "Epoch 286/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0591 - mse: 0.0343 - mae: 0.1342 - root_mean_squared_error: 0.1851\n", "Epoch 286: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0591 - mse: 0.0343 - mae: 0.1344 - root_mean_squared_error: 0.1852 - val_loss: 0.4194 - val_mse: 0.3947 - val_mae: 0.4704 - val_root_mean_squared_error: 0.6282\n", "Epoch 287/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0656 - mse: 0.0410 - mae: 0.1470 - root_mean_squared_error: 0.2024\n", "Epoch 287: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0656 - mse: 0.0410 - mae: 0.1470 - root_mean_squared_error: 0.2024 - val_loss: 0.4124 - val_mse: 0.3879 - val_mae: 0.4628 - val_root_mean_squared_error: 0.6228\n", "Epoch 288/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0644 - mse: 0.0400 - mae: 0.1468 - root_mean_squared_error: 0.2001\n", "Epoch 288: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0644 - mse: 0.0400 - mae: 0.1468 - root_mean_squared_error: 0.2001 - val_loss: 0.4129 - val_mse: 0.3886 - val_mae: 0.4675 - val_root_mean_squared_error: 0.6234\n", "Epoch 289/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0600 - mse: 0.0358 - mae: 0.1351 - root_mean_squared_error: 0.1891\n", "Epoch 289: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0600 - mse: 0.0358 - mae: 0.1351 - root_mean_squared_error: 0.1891 - val_loss: 0.4246 - val_mse: 0.4005 - val_mae: 0.4762 - val_root_mean_squared_error: 0.6328\n", "Epoch 290/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0615 - mse: 0.0375 - mae: 0.1354 - root_mean_squared_error: 0.1936\n", "Epoch 290: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0615 - mse: 0.0375 - mae: 0.1354 - root_mean_squared_error: 0.1936 - val_loss: 0.4100 - val_mse: 0.3862 - val_mae: 0.4684 - val_root_mean_squared_error: 0.6214\n", "Epoch 291/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0576 - mse: 0.0338 - mae: 0.1320 - root_mean_squared_error: 0.1839\n", "Epoch 291: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0579 - mse: 0.0341 - mae: 0.1325 - root_mean_squared_error: 0.1846 - val_loss: 0.4409 - val_mse: 0.4172 - val_mae: 0.4910 - val_root_mean_squared_error: 0.6459\n", "Epoch 292/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0660 - mse: 0.0425 - mae: 0.1530 - root_mean_squared_error: 0.2061\n", "Epoch 292: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0660 - mse: 0.0425 - mae: 0.1530 - root_mean_squared_error: 0.2061 - val_loss: 0.4149 - val_mse: 0.3914 - val_mae: 0.4662 - val_root_mean_squared_error: 0.6256\n", "Epoch 293/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0649 - mse: 0.0415 - mae: 0.1451 - root_mean_squared_error: 0.2038\n", "Epoch 293: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0649 - mse: 0.0415 - mae: 0.1453 - root_mean_squared_error: 0.2038 - val_loss: 0.4254 - val_mse: 0.4021 - val_mae: 0.4796 - val_root_mean_squared_error: 0.6341\n", "Epoch 294/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0720 - mse: 0.0487 - mae: 0.1603 - root_mean_squared_error: 0.2208\n", "Epoch 294: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0718 - mse: 0.0486 - mae: 0.1602 - root_mean_squared_error: 0.2204 - val_loss: 0.4258 - val_mse: 0.4027 - val_mae: 0.4706 - val_root_mean_squared_error: 0.6346\n", "Epoch 295/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0647 - mse: 0.0416 - mae: 0.1498 - root_mean_squared_error: 0.2041\n", "Epoch 295: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0647 - mse: 0.0416 - mae: 0.1498 - root_mean_squared_error: 0.2041 - val_loss: 0.4291 - val_mse: 0.4061 - val_mae: 0.4751 - val_root_mean_squared_error: 0.6372\n", "Epoch 296/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0723 - mse: 0.0494 - mae: 0.1573 - root_mean_squared_error: 0.2223\n", "Epoch 296: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0744 - mse: 0.0515 - mae: 0.1599 - root_mean_squared_error: 0.2268 - val_loss: 0.4497 - val_mse: 0.4268 - val_mae: 0.4896 - val_root_mean_squared_error: 0.6533\n", "Epoch 297/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0784 - mse: 0.0555 - mae: 0.1669 - root_mean_squared_error: 0.2357\n", "Epoch 297: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0784 - mse: 0.0555 - mae: 0.1669 - root_mean_squared_error: 0.2357 - val_loss: 0.4341 - val_mse: 0.4113 - val_mae: 0.4964 - val_root_mean_squared_error: 0.6413\n", "Epoch 298/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0724 - mse: 0.0496 - mae: 0.1594 - root_mean_squared_error: 0.2228\n", "Epoch 298: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 59ms/step - loss: 0.0721 - mse: 0.0493 - mae: 0.1587 - root_mean_squared_error: 0.2220 - val_loss: 0.4271 - val_mse: 0.4044 - val_mae: 0.4819 - val_root_mean_squared_error: 0.6360\n", "Epoch 299/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0611 - mse: 0.0385 - mae: 0.1379 - root_mean_squared_error: 0.1963\n", "Epoch 299: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0611 - mse: 0.0384 - mae: 0.1380 - root_mean_squared_error: 0.1961 - val_loss: 0.4342 - val_mse: 0.4116 - val_mae: 0.4902 - val_root_mean_squared_error: 0.6416\n", "Epoch 300/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0658 - mse: 0.0433 - mae: 0.1494 - root_mean_squared_error: 0.2082\n", "Epoch 300: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0658 - mse: 0.0434 - mae: 0.1492 - root_mean_squared_error: 0.2083 - val_loss: 0.4086 - val_mse: 0.3863 - val_mae: 0.4759 - val_root_mean_squared_error: 0.6215\n", "Epoch 301/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0734 - mse: 0.0511 - mae: 0.1613 - root_mean_squared_error: 0.2262\n", "Epoch 301: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0734 - mse: 0.0511 - mae: 0.1613 - root_mean_squared_error: 0.2262 - val_loss: 0.4060 - val_mse: 0.3837 - val_mae: 0.4672 - val_root_mean_squared_error: 0.6195\n", "Epoch 302/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0608 - mse: 0.0386 - mae: 0.1370 - root_mean_squared_error: 0.1964\n", "Epoch 302: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 0.0608 - mse: 0.0386 - mae: 0.1370 - root_mean_squared_error: 0.1964 - val_loss: 0.4207 - val_mse: 0.3985 - val_mae: 0.4794 - val_root_mean_squared_error: 0.6313\n", "Epoch 303/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0635 - mse: 0.0415 - mae: 0.1518 - root_mean_squared_error: 0.2037\n", "Epoch 303: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 51ms/step - loss: 0.0635 - mse: 0.0415 - mae: 0.1518 - root_mean_squared_error: 0.2037 - val_loss: 0.4144 - val_mse: 0.3925 - val_mae: 0.4740 - val_root_mean_squared_error: 0.6265\n", "Epoch 304/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0748 - mse: 0.0529 - mae: 0.1699 - root_mean_squared_error: 0.2301\n", "Epoch 304: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0748 - mse: 0.0529 - mae: 0.1699 - root_mean_squared_error: 0.2301 - val_loss: 0.4241 - val_mse: 0.4022 - val_mae: 0.4691 - val_root_mean_squared_error: 0.6342\n", "Epoch 305/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0653 - mse: 0.0435 - mae: 0.1513 - root_mean_squared_error: 0.2087\n", "Epoch 305: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0653 - mse: 0.0435 - mae: 0.1513 - root_mean_squared_error: 0.2087 - val_loss: 0.4796 - val_mse: 0.4579 - val_mae: 0.4982 - val_root_mean_squared_error: 0.6767\n", "Epoch 306/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0662 - mse: 0.0446 - mae: 0.1565 - root_mean_squared_error: 0.2111\n", "Epoch 306: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0662 - mse: 0.0446 - mae: 0.1565 - root_mean_squared_error: 0.2111 - val_loss: 0.4229 - val_mse: 0.4013 - val_mae: 0.4833 - val_root_mean_squared_error: 0.6335\n", "Epoch 307/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0590 - mse: 0.0375 - mae: 0.1384 - root_mean_squared_error: 0.1937\n", "Epoch 307: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0590 - mse: 0.0375 - mae: 0.1384 - root_mean_squared_error: 0.1937 - val_loss: 0.4118 - val_mse: 0.3904 - val_mae: 0.4691 - val_root_mean_squared_error: 0.6248\n", "Epoch 308/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0612 - mse: 0.0398 - mae: 0.1438 - root_mean_squared_error: 0.1995\n", "Epoch 308: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0612 - mse: 0.0398 - mae: 0.1438 - root_mean_squared_error: 0.1995 - val_loss: 0.4496 - val_mse: 0.4283 - val_mae: 0.4886 - val_root_mean_squared_error: 0.6544\n", "Epoch 309/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0604 - mse: 0.0391 - mae: 0.1396 - root_mean_squared_error: 0.1979\n", "Epoch 309: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0604 - mse: 0.0391 - mae: 0.1396 - root_mean_squared_error: 0.1979 - val_loss: 0.4661 - val_mse: 0.4449 - val_mae: 0.5264 - val_root_mean_squared_error: 0.6670\n", "Epoch 310/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0586 - mse: 0.0375 - mae: 0.1388 - root_mean_squared_error: 0.1936\n", "Epoch 310: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0590 - mse: 0.0379 - mae: 0.1398 - root_mean_squared_error: 0.1948 - val_loss: 0.4322 - val_mse: 0.4112 - val_mae: 0.4855 - val_root_mean_squared_error: 0.6412\n", "Epoch 311/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0598 - mse: 0.0388 - mae: 0.1425 - root_mean_squared_error: 0.1971\n", "Epoch 311: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 5s 63ms/step - loss: 0.0595 - mse: 0.0386 - mae: 0.1420 - root_mean_squared_error: 0.1965 - val_loss: 0.4061 - val_mse: 0.3853 - val_mae: 0.4691 - val_root_mean_squared_error: 0.6207\n", "Epoch 312/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0581 - mse: 0.0373 - mae: 0.1387 - root_mean_squared_error: 0.1931\n", "Epoch 312: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0580 - mse: 0.0372 - mae: 0.1384 - root_mean_squared_error: 0.1928 - val_loss: 0.4158 - val_mse: 0.3951 - val_mae: 0.4760 - val_root_mean_squared_error: 0.6286\n", "Epoch 313/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0550 - mse: 0.0344 - mae: 0.1358 - root_mean_squared_error: 0.1855\n", "Epoch 313: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0550 - mse: 0.0344 - mae: 0.1358 - root_mean_squared_error: 0.1855 - val_loss: 0.4336 - val_mse: 0.4131 - val_mae: 0.4825 - val_root_mean_squared_error: 0.6427\n", "Epoch 314/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0631 - mse: 0.0426 - mae: 0.1508 - root_mean_squared_error: 0.2064\n", "Epoch 314: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0629 - mse: 0.0424 - mae: 0.1505 - root_mean_squared_error: 0.2059 - val_loss: 0.4515 - val_mse: 0.4311 - val_mae: 0.4987 - val_root_mean_squared_error: 0.6566\n", "Epoch 315/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0775 - mse: 0.0571 - mae: 0.1652 - root_mean_squared_error: 0.2390\n", "Epoch 315: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0775 - mse: 0.0571 - mae: 0.1652 - root_mean_squared_error: 0.2390 - val_loss: 0.4200 - val_mse: 0.3996 - val_mae: 0.4835 - val_root_mean_squared_error: 0.6321\n", "Epoch 316/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0626 - mse: 0.0423 - mae: 0.1504 - root_mean_squared_error: 0.2056\n", "Epoch 316: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0626 - mse: 0.0423 - mae: 0.1504 - root_mean_squared_error: 0.2056 - val_loss: 0.4341 - val_mse: 0.4139 - val_mae: 0.4905 - val_root_mean_squared_error: 0.6433\n", "Epoch 317/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0642 - mse: 0.0440 - mae: 0.1509 - root_mean_squared_error: 0.2098\n", "Epoch 317: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0641 - mse: 0.0438 - mae: 0.1506 - root_mean_squared_error: 0.2094 - val_loss: 0.4452 - val_mse: 0.4250 - val_mae: 0.4957 - val_root_mean_squared_error: 0.6520\n", "Epoch 318/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0538 - mse: 0.0337 - mae: 0.1339 - root_mean_squared_error: 0.1835\n", "Epoch 318: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0539 - mse: 0.0339 - mae: 0.1342 - root_mean_squared_error: 0.1840 - val_loss: 0.4175 - val_mse: 0.3974 - val_mae: 0.4738 - val_root_mean_squared_error: 0.6304\n", "Epoch 319/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0586 - mse: 0.0386 - mae: 0.1395 - root_mean_squared_error: 0.1966\n", "Epoch 319: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 34ms/step - loss: 0.0590 - mse: 0.0391 - mae: 0.1401 - root_mean_squared_error: 0.1977 - val_loss: 0.4272 - val_mse: 0.4073 - val_mae: 0.4838 - val_root_mean_squared_error: 0.6382\n", "Epoch 320/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0628 - mse: 0.0430 - mae: 0.1467 - root_mean_squared_error: 0.2073\n", "Epoch 320: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0626 - mse: 0.0428 - mae: 0.1464 - root_mean_squared_error: 0.2068 - val_loss: 0.4118 - val_mse: 0.3920 - val_mae: 0.4682 - val_root_mean_squared_error: 0.6261\n", "Epoch 321/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0666 - mse: 0.0469 - mae: 0.1534 - root_mean_squared_error: 0.2165\n", "Epoch 321: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0664 - mse: 0.0467 - mae: 0.1533 - root_mean_squared_error: 0.2161 - val_loss: 0.4448 - val_mse: 0.4251 - val_mae: 0.5034 - val_root_mean_squared_error: 0.6520\n", "Epoch 322/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0578 - mse: 0.0382 - mae: 0.1399 - root_mean_squared_error: 0.1954\n", "Epoch 322: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0578 - mse: 0.0382 - mae: 0.1399 - root_mean_squared_error: 0.1954 - val_loss: 0.4279 - val_mse: 0.4083 - val_mae: 0.4780 - val_root_mean_squared_error: 0.6390\n", "Epoch 323/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0732 - mse: 0.0537 - mae: 0.1619 - root_mean_squared_error: 0.2316\n", "Epoch 323: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0732 - mse: 0.0537 - mae: 0.1619 - root_mean_squared_error: 0.2316 - val_loss: 0.4383 - val_mse: 0.4187 - val_mae: 0.4981 - val_root_mean_squared_error: 0.6471\n", "Epoch 324/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0871 - mse: 0.0676 - mae: 0.1793 - root_mean_squared_error: 0.2599\n", "Epoch 324: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0871 - mse: 0.0676 - mae: 0.1793 - root_mean_squared_error: 0.2599 - val_loss: 0.4140 - val_mse: 0.3945 - val_mae: 0.4774 - val_root_mean_squared_error: 0.6281\n", "Epoch 325/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0789 - mse: 0.0594 - mae: 0.1750 - root_mean_squared_error: 0.2437\n", "Epoch 325: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0788 - mse: 0.0593 - mae: 0.1752 - root_mean_squared_error: 0.2435 - val_loss: 0.4260 - val_mse: 0.4065 - val_mae: 0.4714 - val_root_mean_squared_error: 0.6376\n", "Epoch 326/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0698 - mse: 0.0503 - mae: 0.1579 - root_mean_squared_error: 0.2242\n", "Epoch 326: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 61ms/step - loss: 0.0697 - mse: 0.0502 - mae: 0.1579 - root_mean_squared_error: 0.2242 - val_loss: 0.4310 - val_mse: 0.4116 - val_mae: 0.4910 - val_root_mean_squared_error: 0.6416\n", "Epoch 327/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0604 - mse: 0.0410 - mae: 0.1404 - root_mean_squared_error: 0.2025\n", "Epoch 327: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0604 - mse: 0.0410 - mae: 0.1404 - root_mean_squared_error: 0.2025 - val_loss: 0.4208 - val_mse: 0.4014 - val_mae: 0.4848 - val_root_mean_squared_error: 0.6336\n", "Epoch 328/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0571 - mse: 0.0379 - mae: 0.1402 - root_mean_squared_error: 0.1946\n", "Epoch 328: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0571 - mse: 0.0379 - mae: 0.1402 - root_mean_squared_error: 0.1946 - val_loss: 0.4312 - val_mse: 0.4119 - val_mae: 0.4827 - val_root_mean_squared_error: 0.6418\n", "Epoch 329/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0579 - mse: 0.0387 - mae: 0.1392 - root_mean_squared_error: 0.1968\n", "Epoch 329: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0580 - mse: 0.0389 - mae: 0.1395 - root_mean_squared_error: 0.1972 - val_loss: 0.4070 - val_mse: 0.3879 - val_mae: 0.4696 - val_root_mean_squared_error: 0.6229\n", "Epoch 330/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0565 - mse: 0.0375 - mae: 0.1393 - root_mean_squared_error: 0.1937\n", "Epoch 330: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0561 - mse: 0.0371 - mae: 0.1386 - root_mean_squared_error: 0.1927 - val_loss: 0.4102 - val_mse: 0.3913 - val_mae: 0.4750 - val_root_mean_squared_error: 0.6255\n", "Epoch 331/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0550 - mse: 0.0361 - mae: 0.1414 - root_mean_squared_error: 0.1900\n", "Epoch 331: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0550 - mse: 0.0361 - mae: 0.1413 - root_mean_squared_error: 0.1899 - val_loss: 0.4165 - val_mse: 0.3976 - val_mae: 0.4719 - val_root_mean_squared_error: 0.6306\n", "Epoch 332/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0561 - mse: 0.0373 - mae: 0.1397 - root_mean_squared_error: 0.1932\n", "Epoch 332: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0563 - mse: 0.0375 - mae: 0.1402 - root_mean_squared_error: 0.1936 - val_loss: 0.4113 - val_mse: 0.3926 - val_mae: 0.4751 - val_root_mean_squared_error: 0.6266\n", "Epoch 333/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0621 - mse: 0.0434 - mae: 0.1527 - root_mean_squared_error: 0.2084\n", "Epoch 333: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0621 - mse: 0.0434 - mae: 0.1527 - root_mean_squared_error: 0.2084 - val_loss: 0.3928 - val_mse: 0.3742 - val_mae: 0.4659 - val_root_mean_squared_error: 0.6117\n", "Epoch 334/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0587 - mse: 0.0402 - mae: 0.1449 - root_mean_squared_error: 0.2004\n", "Epoch 334: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0593 - mse: 0.0407 - mae: 0.1456 - root_mean_squared_error: 0.2018 - val_loss: 0.4308 - val_mse: 0.4123 - val_mae: 0.4833 - val_root_mean_squared_error: 0.6421\n", "Epoch 335/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0514 - mse: 0.0329 - mae: 0.1311 - root_mean_squared_error: 0.1814\n", "Epoch 335: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0517 - mse: 0.0332 - mae: 0.1317 - root_mean_squared_error: 0.1822 - val_loss: 0.4074 - val_mse: 0.3890 - val_mae: 0.4669 - val_root_mean_squared_error: 0.6237\n", "Epoch 336/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0542 - mse: 0.0359 - mae: 0.1385 - root_mean_squared_error: 0.1894\n", "Epoch 336: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0541 - mse: 0.0357 - mae: 0.1381 - root_mean_squared_error: 0.1890 - val_loss: 0.4254 - val_mse: 0.4071 - val_mae: 0.4799 - val_root_mean_squared_error: 0.6381\n", "Epoch 337/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0571 - mse: 0.0389 - mae: 0.1457 - root_mean_squared_error: 0.1972\n", "Epoch 337: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0570 - mse: 0.0388 - mae: 0.1455 - root_mean_squared_error: 0.1970 - val_loss: 0.4192 - val_mse: 0.4010 - val_mae: 0.4745 - val_root_mean_squared_error: 0.6333\n", "Epoch 338/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0491 - mse: 0.0310 - mae: 0.1275 - root_mean_squared_error: 0.1761\n", "Epoch 338: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0491 - mse: 0.0310 - mae: 0.1275 - root_mean_squared_error: 0.1761 - val_loss: 0.4185 - val_mse: 0.4004 - val_mae: 0.4758 - val_root_mean_squared_error: 0.6328\n", "Epoch 339/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0559 - mse: 0.0379 - mae: 0.1387 - root_mean_squared_error: 0.1947\n", "Epoch 339: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0559 - mse: 0.0379 - mae: 0.1387 - root_mean_squared_error: 0.1947 - val_loss: 0.4182 - val_mse: 0.4003 - val_mae: 0.4726 - val_root_mean_squared_error: 0.6327\n", "Epoch 340/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0571 - mse: 0.0392 - mae: 0.1416 - root_mean_squared_error: 0.1979\n", "Epoch 340: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0571 - mse: 0.0392 - mae: 0.1416 - root_mean_squared_error: 0.1979 - val_loss: 0.4259 - val_mse: 0.4080 - val_mae: 0.4862 - val_root_mean_squared_error: 0.6388\n", "Epoch 341/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0599 - mse: 0.0421 - mae: 0.1518 - root_mean_squared_error: 0.2051\n", "Epoch 341: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0601 - mse: 0.0423 - mae: 0.1522 - root_mean_squared_error: 0.2056 - val_loss: 0.4228 - val_mse: 0.4050 - val_mae: 0.4717 - val_root_mean_squared_error: 0.6364\n", "Epoch 342/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0716 - mse: 0.0538 - mae: 0.1695 - root_mean_squared_error: 0.2320\n", "Epoch 342: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 59ms/step - loss: 0.0716 - mse: 0.0538 - mae: 0.1693 - root_mean_squared_error: 0.2319 - val_loss: 0.4348 - val_mse: 0.4170 - val_mae: 0.4859 - val_root_mean_squared_error: 0.6457\n", "Epoch 343/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0704 - mse: 0.0527 - mae: 0.1635 - root_mean_squared_error: 0.2295\n", "Epoch 343: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0704 - mse: 0.0527 - mae: 0.1635 - root_mean_squared_error: 0.2295 - val_loss: 0.4299 - val_mse: 0.4121 - val_mae: 0.4797 - val_root_mean_squared_error: 0.6420\n", "Epoch 344/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0576 - mse: 0.0399 - mae: 0.1415 - root_mean_squared_error: 0.1997\n", "Epoch 344: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0574 - mse: 0.0397 - mae: 0.1411 - root_mean_squared_error: 0.1991 - val_loss: 0.4225 - val_mse: 0.4048 - val_mae: 0.4771 - val_root_mean_squared_error: 0.6362\n", "Epoch 345/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0481 - mse: 0.0305 - mae: 0.1233 - root_mean_squared_error: 0.1747\n", "Epoch 345: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0481 - mse: 0.0305 - mae: 0.1233 - root_mean_squared_error: 0.1747 - val_loss: 0.4347 - val_mse: 0.4172 - val_mae: 0.4827 - val_root_mean_squared_error: 0.6459\n", "Epoch 346/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0542 - mse: 0.0367 - mae: 0.1385 - root_mean_squared_error: 0.1916\n", "Epoch 346: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 57ms/step - loss: 0.0541 - mse: 0.0366 - mae: 0.1383 - root_mean_squared_error: 0.1913 - val_loss: 0.4357 - val_mse: 0.4182 - val_mae: 0.4826 - val_root_mean_squared_error: 0.6467\n", "Epoch 347/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0619 - mse: 0.0445 - mae: 0.1543 - root_mean_squared_error: 0.2110\n", "Epoch 347: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0613 - mse: 0.0439 - mae: 0.1532 - root_mean_squared_error: 0.2096 - val_loss: 0.4330 - val_mse: 0.4157 - val_mae: 0.4803 - val_root_mean_squared_error: 0.6447\n", "Epoch 348/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0521 - mse: 0.0348 - mae: 0.1360 - root_mean_squared_error: 0.1865\n", "Epoch 348: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0521 - mse: 0.0348 - mae: 0.1360 - root_mean_squared_error: 0.1865 - val_loss: 0.4341 - val_mse: 0.4168 - val_mae: 0.4931 - val_root_mean_squared_error: 0.6456\n", "Epoch 349/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0582 - mse: 0.0410 - mae: 0.1379 - root_mean_squared_error: 0.2024\n", "Epoch 349: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0582 - mse: 0.0410 - mae: 0.1379 - root_mean_squared_error: 0.2024 - val_loss: 0.4177 - val_mse: 0.4006 - val_mae: 0.4748 - val_root_mean_squared_error: 0.6329\n", "Epoch 350/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0618 - mse: 0.0446 - mae: 0.1484 - root_mean_squared_error: 0.2113\n", "Epoch 350: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0620 - mse: 0.0448 - mae: 0.1491 - root_mean_squared_error: 0.2118 - val_loss: 0.4234 - val_mse: 0.4063 - val_mae: 0.4818 - val_root_mean_squared_error: 0.6374\n", "Epoch 351/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0702 - mse: 0.0531 - mae: 0.1666 - root_mean_squared_error: 0.2304\n", "Epoch 351: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0699 - mse: 0.0528 - mae: 0.1660 - root_mean_squared_error: 0.2297 - val_loss: 0.4231 - val_mse: 0.4060 - val_mae: 0.4728 - val_root_mean_squared_error: 0.6372\n", "Epoch 352/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0684 - mse: 0.0512 - mae: 0.1618 - root_mean_squared_error: 0.2264\n", "Epoch 352: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0685 - mse: 0.0513 - mae: 0.1619 - root_mean_squared_error: 0.2266 - val_loss: 0.4521 - val_mse: 0.4350 - val_mae: 0.4971 - val_root_mean_squared_error: 0.6595\n", "Epoch 353/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0624 - mse: 0.0453 - mae: 0.1488 - root_mean_squared_error: 0.2129\n", "Epoch 353: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0624 - mse: 0.0453 - mae: 0.1488 - root_mean_squared_error: 0.2129 - val_loss: 0.4191 - val_mse: 0.4020 - val_mae: 0.4737 - val_root_mean_squared_error: 0.6341\n", "Epoch 354/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0559 - mse: 0.0389 - mae: 0.1420 - root_mean_squared_error: 0.1971\n", "Epoch 354: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0559 - mse: 0.0389 - mae: 0.1420 - root_mean_squared_error: 0.1971 - val_loss: 0.4321 - val_mse: 0.4151 - val_mae: 0.4909 - val_root_mean_squared_error: 0.6443\n", "Epoch 355/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0533 - mse: 0.0363 - mae: 0.1407 - root_mean_squared_error: 0.1906\n", "Epoch 355: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 50ms/step - loss: 0.0533 - mse: 0.0363 - mae: 0.1407 - root_mean_squared_error: 0.1906 - val_loss: 0.4353 - val_mse: 0.4184 - val_mae: 0.4878 - val_root_mean_squared_error: 0.6468\n", "Epoch 356/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0517 - mse: 0.0348 - mae: 0.1362 - root_mean_squared_error: 0.1866\n", "Epoch 356: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 0.0517 - mse: 0.0348 - mae: 0.1362 - root_mean_squared_error: 0.1866 - val_loss: 0.4310 - val_mse: 0.4142 - val_mae: 0.4840 - val_root_mean_squared_error: 0.6436\n", "Epoch 357/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0529 - mse: 0.0362 - mae: 0.1401 - root_mean_squared_error: 0.1902\n", "Epoch 357: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0529 - mse: 0.0362 - mae: 0.1401 - root_mean_squared_error: 0.1902 - val_loss: 0.4116 - val_mse: 0.3949 - val_mae: 0.4717 - val_root_mean_squared_error: 0.6284\n", "Epoch 358/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0556 - mse: 0.0389 - mae: 0.1428 - root_mean_squared_error: 0.1972\n", "Epoch 358: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0556 - mse: 0.0389 - mae: 0.1428 - root_mean_squared_error: 0.1972 - val_loss: 0.4095 - val_mse: 0.3929 - val_mae: 0.4791 - val_root_mean_squared_error: 0.6268\n", "Epoch 359/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0498 - mse: 0.0333 - mae: 0.1326 - root_mean_squared_error: 0.1824\n", "Epoch 359: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 0.0498 - mse: 0.0332 - mae: 0.1326 - root_mean_squared_error: 0.1823 - val_loss: 0.4260 - val_mse: 0.4094 - val_mae: 0.4796 - val_root_mean_squared_error: 0.6399\n", "Epoch 360/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0526 - mse: 0.0361 - mae: 0.1406 - root_mean_squared_error: 0.1901\n", "Epoch 360: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0533 - mse: 0.0368 - mae: 0.1418 - root_mean_squared_error: 0.1919 - val_loss: 0.4170 - val_mse: 0.4005 - val_mae: 0.4757 - val_root_mean_squared_error: 0.6329\n", "Epoch 361/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0506 - mse: 0.0342 - mae: 0.1324 - root_mean_squared_error: 0.1849\n", "Epoch 361: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0504 - mse: 0.0340 - mae: 0.1320 - root_mean_squared_error: 0.1844 - val_loss: 0.4277 - val_mse: 0.4113 - val_mae: 0.4842 - val_root_mean_squared_error: 0.6413\n", "Epoch 362/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0469 - mse: 0.0306 - mae: 0.1241 - root_mean_squared_error: 0.1750\n", "Epoch 362: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0470 - mse: 0.0307 - mae: 0.1245 - root_mean_squared_error: 0.1752 - val_loss: 0.4419 - val_mse: 0.4257 - val_mae: 0.4965 - val_root_mean_squared_error: 0.6524\n", "Epoch 363/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0504 - mse: 0.0341 - mae: 0.1339 - root_mean_squared_error: 0.1848\n", "Epoch 363: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0504 - mse: 0.0341 - mae: 0.1339 - root_mean_squared_error: 0.1848 - val_loss: 0.4266 - val_mse: 0.4105 - val_mae: 0.4841 - val_root_mean_squared_error: 0.6407\n", "Epoch 364/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0719 - mse: 0.0557 - mae: 0.1707 - root_mean_squared_error: 0.2361\n", "Epoch 364: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0719 - mse: 0.0557 - mae: 0.1707 - root_mean_squared_error: 0.2361 - val_loss: 0.4590 - val_mse: 0.4428 - val_mae: 0.5055 - val_root_mean_squared_error: 0.6654\n", "Epoch 365/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0578 - mse: 0.0416 - mae: 0.1526 - root_mean_squared_error: 0.2041\n", "Epoch 365: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0577 - mse: 0.0416 - mae: 0.1527 - root_mean_squared_error: 0.2039 - val_loss: 0.4193 - val_mse: 0.4031 - val_mae: 0.4808 - val_root_mean_squared_error: 0.6349\n", "Epoch 366/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0582 - mse: 0.0421 - mae: 0.1457 - root_mean_squared_error: 0.2052\n", "Epoch 366: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0582 - mse: 0.0421 - mae: 0.1457 - root_mean_squared_error: 0.2052 - val_loss: 0.4159 - val_mse: 0.3998 - val_mae: 0.4855 - val_root_mean_squared_error: 0.6323\n", "Epoch 367/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0685 - mse: 0.0525 - mae: 0.1558 - root_mean_squared_error: 0.2290\n", "Epoch 367: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0680 - mse: 0.0520 - mae: 0.1554 - root_mean_squared_error: 0.2279 - val_loss: 0.4191 - val_mse: 0.4030 - val_mae: 0.4857 - val_root_mean_squared_error: 0.6348\n", "Epoch 368/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0665 - mse: 0.0504 - mae: 0.1622 - root_mean_squared_error: 0.2245\n", "Epoch 368: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 6s 77ms/step - loss: 0.0663 - mse: 0.0502 - mae: 0.1620 - root_mean_squared_error: 0.2241 - val_loss: 0.4232 - val_mse: 0.4071 - val_mae: 0.4773 - val_root_mean_squared_error: 0.6380\n", "Epoch 369/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0568 - mse: 0.0408 - mae: 0.1476 - root_mean_squared_error: 0.2019\n", "Epoch 369: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0568 - mse: 0.0408 - mae: 0.1476 - root_mean_squared_error: 0.2019 - val_loss: 0.4298 - val_mse: 0.4137 - val_mae: 0.4910 - val_root_mean_squared_error: 0.6432\n", "Epoch 370/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0559 - mse: 0.0399 - mae: 0.1453 - root_mean_squared_error: 0.1998\n", "Epoch 370: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0559 - mse: 0.0399 - mae: 0.1455 - root_mean_squared_error: 0.1997 - val_loss: 0.4010 - val_mse: 0.3850 - val_mae: 0.4656 - val_root_mean_squared_error: 0.6205\n", "Epoch 371/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0511 - mse: 0.0351 - mae: 0.1364 - root_mean_squared_error: 0.1874\n", "Epoch 371: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0511 - mse: 0.0351 - mae: 0.1364 - root_mean_squared_error: 0.1874 - val_loss: 0.4133 - val_mse: 0.3973 - val_mae: 0.4728 - val_root_mean_squared_error: 0.6303\n", "Epoch 372/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0482 - mse: 0.0323 - mae: 0.1302 - root_mean_squared_error: 0.1797\n", "Epoch 372: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0482 - mse: 0.0323 - mae: 0.1302 - root_mean_squared_error: 0.1797 - val_loss: 0.4967 - val_mse: 0.4809 - val_mae: 0.5488 - val_root_mean_squared_error: 0.6935\n", "Epoch 373/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0571 - mse: 0.0413 - mae: 0.1482 - root_mean_squared_error: 0.2033\n", "Epoch 373: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0572 - mse: 0.0414 - mae: 0.1486 - root_mean_squared_error: 0.2034 - val_loss: 0.4250 - val_mse: 0.4092 - val_mae: 0.4888 - val_root_mean_squared_error: 0.6397\n", "Epoch 374/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0670 - mse: 0.0512 - mae: 0.1659 - root_mean_squared_error: 0.2264\n", "Epoch 374: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0670 - mse: 0.0512 - mae: 0.1659 - root_mean_squared_error: 0.2264 - val_loss: 0.4536 - val_mse: 0.4378 - val_mae: 0.4947 - val_root_mean_squared_error: 0.6617\n", "Epoch 375/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0622 - mse: 0.0464 - mae: 0.1541 - root_mean_squared_error: 0.2155\n", "Epoch 375: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0622 - mse: 0.0464 - mae: 0.1541 - root_mean_squared_error: 0.2155 - val_loss: 0.4397 - val_mse: 0.4240 - val_mae: 0.4960 - val_root_mean_squared_error: 0.6511\n", "Epoch 376/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0521 - mse: 0.0364 - mae: 0.1383 - root_mean_squared_error: 0.1908\n", "Epoch 376: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0521 - mse: 0.0364 - mae: 0.1384 - root_mean_squared_error: 0.1908 - val_loss: 0.4517 - val_mse: 0.4360 - val_mae: 0.4928 - val_root_mean_squared_error: 0.6603\n", "Epoch 377/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0474 - mse: 0.0318 - mae: 0.1283 - root_mean_squared_error: 0.1783\n", "Epoch 377: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0473 - mse: 0.0316 - mae: 0.1279 - root_mean_squared_error: 0.1778 - val_loss: 0.4262 - val_mse: 0.4106 - val_mae: 0.4878 - val_root_mean_squared_error: 0.6408\n", "Epoch 378/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0544 - mse: 0.0388 - mae: 0.1411 - root_mean_squared_error: 0.1971\n", "Epoch 378: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0543 - mse: 0.0387 - mae: 0.1411 - root_mean_squared_error: 0.1968 - val_loss: 0.4235 - val_mse: 0.4080 - val_mae: 0.4907 - val_root_mean_squared_error: 0.6387\n", "Epoch 379/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0572 - mse: 0.0417 - mae: 0.1498 - root_mean_squared_error: 0.2042\n", "Epoch 379: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0572 - mse: 0.0417 - mae: 0.1498 - root_mean_squared_error: 0.2042 - val_loss: 0.4203 - val_mse: 0.4048 - val_mae: 0.4773 - val_root_mean_squared_error: 0.6363\n", "Epoch 380/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0493 - mse: 0.0338 - mae: 0.1329 - root_mean_squared_error: 0.1839\n", "Epoch 380: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0493 - mse: 0.0338 - mae: 0.1329 - root_mean_squared_error: 0.1839 - val_loss: 0.4375 - val_mse: 0.4221 - val_mae: 0.4876 - val_root_mean_squared_error: 0.6497\n", "Epoch 381/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0479 - mse: 0.0325 - mae: 0.1313 - root_mean_squared_error: 0.1803\n", "Epoch 381: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 55ms/step - loss: 0.0479 - mse: 0.0325 - mae: 0.1313 - root_mean_squared_error: 0.1803 - val_loss: 0.4280 - val_mse: 0.4127 - val_mae: 0.4911 - val_root_mean_squared_error: 0.6424\n", "Epoch 382/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0472 - mse: 0.0319 - mae: 0.1299 - root_mean_squared_error: 0.1786\n", "Epoch 382: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0470 - mse: 0.0317 - mae: 0.1294 - root_mean_squared_error: 0.1781 - val_loss: 0.4257 - val_mse: 0.4105 - val_mae: 0.4897 - val_root_mean_squared_error: 0.6407\n", "Epoch 383/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0449 - mse: 0.0296 - mae: 0.1256 - root_mean_squared_error: 0.1722\n", "Epoch 383: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0448 - mse: 0.0296 - mae: 0.1255 - root_mean_squared_error: 0.1720 - val_loss: 0.4269 - val_mse: 0.4118 - val_mae: 0.4836 - val_root_mean_squared_error: 0.6417\n", "Epoch 384/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0502 - mse: 0.0351 - mae: 0.1344 - root_mean_squared_error: 0.1874\n", "Epoch 384: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 33ms/step - loss: 0.0502 - mse: 0.0351 - mae: 0.1344 - root_mean_squared_error: 0.1874 - val_loss: 0.4287 - val_mse: 0.4136 - val_mae: 0.4883 - val_root_mean_squared_error: 0.6431\n", "Epoch 385/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0539 - mse: 0.0388 - mae: 0.1418 - root_mean_squared_error: 0.1970\n", "Epoch 385: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0538 - mse: 0.0387 - mae: 0.1418 - root_mean_squared_error: 0.1968 - val_loss: 0.4271 - val_mse: 0.4120 - val_mae: 0.4836 - val_root_mean_squared_error: 0.6419\n", "Epoch 386/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0554 - mse: 0.0404 - mae: 0.1452 - root_mean_squared_error: 0.2009\n", "Epoch 386: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0552 - mse: 0.0402 - mae: 0.1449 - root_mean_squared_error: 0.2005 - val_loss: 0.4287 - val_mse: 0.4137 - val_mae: 0.4817 - val_root_mean_squared_error: 0.6432\n", "Epoch 387/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0540 - mse: 0.0389 - mae: 0.1435 - root_mean_squared_error: 0.1974\n", "Epoch 387: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0540 - mse: 0.0389 - mae: 0.1435 - root_mean_squared_error: 0.1974 - val_loss: 0.4563 - val_mse: 0.4414 - val_mae: 0.5026 - val_root_mean_squared_error: 0.6644\n", "Epoch 388/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0515 - mse: 0.0365 - mae: 0.1412 - root_mean_squared_error: 0.1911\n", "Epoch 388: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0512 - mse: 0.0363 - mae: 0.1408 - root_mean_squared_error: 0.1905 - val_loss: 0.4279 - val_mse: 0.4129 - val_mae: 0.4819 - val_root_mean_squared_error: 0.6426\n", "Epoch 389/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0511 - mse: 0.0362 - mae: 0.1356 - root_mean_squared_error: 0.1902\n", "Epoch 389: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0513 - mse: 0.0364 - mae: 0.1361 - root_mean_squared_error: 0.1908 - val_loss: 0.4254 - val_mse: 0.4105 - val_mae: 0.4916 - val_root_mean_squared_error: 0.6407\n", "Epoch 390/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0528 - mse: 0.0380 - mae: 0.1415 - root_mean_squared_error: 0.1948\n", "Epoch 390: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0529 - mse: 0.0380 - mae: 0.1419 - root_mean_squared_error: 0.1949 - val_loss: 0.4151 - val_mse: 0.4003 - val_mae: 0.4699 - val_root_mean_squared_error: 0.6327\n", "Epoch 391/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0619 - mse: 0.0471 - mae: 0.1532 - root_mean_squared_error: 0.2170\n", "Epoch 391: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0619 - mse: 0.0471 - mae: 0.1532 - root_mean_squared_error: 0.2170 - val_loss: 0.4140 - val_mse: 0.3992 - val_mae: 0.4742 - val_root_mean_squared_error: 0.6318\n", "Epoch 392/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0479 - mse: 0.0331 - mae: 0.1318 - root_mean_squared_error: 0.1819\n", "Epoch 392: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0478 - mse: 0.0330 - mae: 0.1317 - root_mean_squared_error: 0.1818 - val_loss: 0.4303 - val_mse: 0.4156 - val_mae: 0.4908 - val_root_mean_squared_error: 0.6447\n", "Epoch 393/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0572 - mse: 0.0425 - mae: 0.1497 - root_mean_squared_error: 0.2061\n", "Epoch 393: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0570 - mse: 0.0423 - mae: 0.1500 - root_mean_squared_error: 0.2058 - val_loss: 0.4323 - val_mse: 0.4176 - val_mae: 0.4900 - val_root_mean_squared_error: 0.6462\n", "Epoch 394/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0494 - mse: 0.0347 - mae: 0.1361 - root_mean_squared_error: 0.1864\n", "Epoch 394: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0494 - mse: 0.0347 - mae: 0.1361 - root_mean_squared_error: 0.1864 - val_loss: 0.4394 - val_mse: 0.4246 - val_mae: 0.5033 - val_root_mean_squared_error: 0.6516\n", "Epoch 395/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0478 - mse: 0.0331 - mae: 0.1333 - root_mean_squared_error: 0.1820\n", "Epoch 395: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0478 - mse: 0.0331 - mae: 0.1333 - root_mean_squared_error: 0.1820 - val_loss: 0.4197 - val_mse: 0.4051 - val_mae: 0.4798 - val_root_mean_squared_error: 0.6365\n", "Epoch 396/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0544 - mse: 0.0398 - mae: 0.1474 - root_mean_squared_error: 0.1996\n", "Epoch 396: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0544 - mse: 0.0398 - mae: 0.1474 - root_mean_squared_error: 0.1996 - val_loss: 0.4160 - val_mse: 0.4015 - val_mae: 0.4752 - val_root_mean_squared_error: 0.6336\n", "Epoch 397/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0468 - mse: 0.0323 - mae: 0.1297 - root_mean_squared_error: 0.1797\n", "Epoch 397: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0477 - mse: 0.0332 - mae: 0.1304 - root_mean_squared_error: 0.1821 - val_loss: 0.4105 - val_mse: 0.3961 - val_mae: 0.4745 - val_root_mean_squared_error: 0.6293\n", "Epoch 398/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0483 - mse: 0.0338 - mae: 0.1315 - root_mean_squared_error: 0.1839\n", "Epoch 398: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0483 - mse: 0.0338 - mae: 0.1315 - root_mean_squared_error: 0.1839 - val_loss: 0.4095 - val_mse: 0.3951 - val_mae: 0.4797 - val_root_mean_squared_error: 0.6286\n", "Epoch 399/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0619 - mse: 0.0475 - mae: 0.1549 - root_mean_squared_error: 0.2180\n", "Epoch 399: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0618 - mse: 0.0474 - mae: 0.1548 - root_mean_squared_error: 0.2177 - val_loss: 0.4543 - val_mse: 0.4399 - val_mae: 0.4983 - val_root_mean_squared_error: 0.6633\n", "Epoch 400/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0641 - mse: 0.0497 - mae: 0.1585 - root_mean_squared_error: 0.2229\n", "Epoch 400: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0639 - mse: 0.0495 - mae: 0.1584 - root_mean_squared_error: 0.2225 - val_loss: 0.4083 - val_mse: 0.3939 - val_mae: 0.4742 - val_root_mean_squared_error: 0.6276\n", "Epoch 401/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0498 - mse: 0.0354 - mae: 0.1381 - root_mean_squared_error: 0.1882\n", "Epoch 401: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0498 - mse: 0.0354 - mae: 0.1378 - root_mean_squared_error: 0.1880 - val_loss: 0.4227 - val_mse: 0.4083 - val_mae: 0.4768 - val_root_mean_squared_error: 0.6390\n", "Epoch 402/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0497 - mse: 0.0354 - mae: 0.1366 - root_mean_squared_error: 0.1880\n", "Epoch 402: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0497 - mse: 0.0354 - mae: 0.1366 - root_mean_squared_error: 0.1880 - val_loss: 0.4357 - val_mse: 0.4213 - val_mae: 0.4936 - val_root_mean_squared_error: 0.6491\n", "Epoch 403/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0497 - mse: 0.0354 - mae: 0.1369 - root_mean_squared_error: 0.1881\n", "Epoch 403: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0497 - mse: 0.0354 - mae: 0.1369 - root_mean_squared_error: 0.1881 - val_loss: 0.4244 - val_mse: 0.4101 - val_mae: 0.4848 - val_root_mean_squared_error: 0.6404\n", "Epoch 404/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0446 - mse: 0.0304 - mae: 0.1275 - root_mean_squared_error: 0.1742\n", "Epoch 404: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0445 - mse: 0.0302 - mae: 0.1272 - root_mean_squared_error: 0.1739 - val_loss: 0.4030 - val_mse: 0.3888 - val_mae: 0.4637 - val_root_mean_squared_error: 0.6235\n", "Epoch 405/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0400 - mse: 0.0259 - mae: 0.1214 - root_mean_squared_error: 0.1609\n", "Epoch 405: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0400 - mse: 0.0259 - mae: 0.1214 - root_mean_squared_error: 0.1609 - val_loss: 0.4171 - val_mse: 0.4030 - val_mae: 0.4731 - val_root_mean_squared_error: 0.6348\n", "Epoch 406/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0413 - mse: 0.0272 - mae: 0.1195 - root_mean_squared_error: 0.1650\n", "Epoch 406: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0413 - mse: 0.0272 - mae: 0.1195 - root_mean_squared_error: 0.1650 - val_loss: 0.4176 - val_mse: 0.4036 - val_mae: 0.4738 - val_root_mean_squared_error: 0.6353\n", "Epoch 407/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0540 - mse: 0.0400 - mae: 0.1432 - root_mean_squared_error: 0.1999\n", "Epoch 407: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0535 - mse: 0.0395 - mae: 0.1420 - root_mean_squared_error: 0.1988 - val_loss: 0.4191 - val_mse: 0.4051 - val_mae: 0.4846 - val_root_mean_squared_error: 0.6365\n", "Epoch 408/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0430 - mse: 0.0290 - mae: 0.1208 - root_mean_squared_error: 0.1703\n", "Epoch 408: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0431 - mse: 0.0291 - mae: 0.1210 - root_mean_squared_error: 0.1707 - val_loss: 0.4227 - val_mse: 0.4087 - val_mae: 0.4864 - val_root_mean_squared_error: 0.6393\n", "Epoch 409/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0581 - mse: 0.0441 - mae: 0.1452 - root_mean_squared_error: 0.2101\n", "Epoch 409: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0579 - mse: 0.0440 - mae: 0.1451 - root_mean_squared_error: 0.2097 - val_loss: 0.4388 - val_mse: 0.4248 - val_mae: 0.4984 - val_root_mean_squared_error: 0.6518\n", "Epoch 410/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0476 - mse: 0.0336 - mae: 0.1299 - root_mean_squared_error: 0.1834\n", "Epoch 410: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0473 - mse: 0.0334 - mae: 0.1296 - root_mean_squared_error: 0.1828 - val_loss: 0.4357 - val_mse: 0.4218 - val_mae: 0.4986 - val_root_mean_squared_error: 0.6495\n", "Epoch 411/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0486 - mse: 0.0347 - mae: 0.1324 - root_mean_squared_error: 0.1863\n", "Epoch 411: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0486 - mse: 0.0347 - mae: 0.1324 - root_mean_squared_error: 0.1863 - val_loss: 0.4180 - val_mse: 0.4041 - val_mae: 0.4810 - val_root_mean_squared_error: 0.6357\n", "Epoch 412/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0462 - mse: 0.0324 - mae: 0.1283 - root_mean_squared_error: 0.1799\n", "Epoch 412: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0460 - mse: 0.0323 - mae: 0.1281 - root_mean_squared_error: 0.1796 - val_loss: 0.4223 - val_mse: 0.4085 - val_mae: 0.4769 - val_root_mean_squared_error: 0.6392\n", "Epoch 413/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0427 - mse: 0.0289 - mae: 0.1205 - root_mean_squared_error: 0.1700\n", "Epoch 413: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0427 - mse: 0.0289 - mae: 0.1205 - root_mean_squared_error: 0.1700 - val_loss: 0.4209 - val_mse: 0.4072 - val_mae: 0.4863 - val_root_mean_squared_error: 0.6381\n", "Epoch 414/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0505 - mse: 0.0368 - mae: 0.1371 - root_mean_squared_error: 0.1919\n", "Epoch 414: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0505 - mse: 0.0368 - mae: 0.1371 - root_mean_squared_error: 0.1919 - val_loss: 0.4174 - val_mse: 0.4038 - val_mae: 0.4790 - val_root_mean_squared_error: 0.6354\n", "Epoch 415/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0467 - mse: 0.0330 - mae: 0.1322 - root_mean_squared_error: 0.1818\n", "Epoch 415: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0466 - mse: 0.0329 - mae: 0.1321 - root_mean_squared_error: 0.1815 - val_loss: 0.4140 - val_mse: 0.4003 - val_mae: 0.4774 - val_root_mean_squared_error: 0.6327\n", "Epoch 416/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0451 - mse: 0.0314 - mae: 0.1286 - root_mean_squared_error: 0.1772\n", "Epoch 416: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0450 - mse: 0.0313 - mae: 0.1286 - root_mean_squared_error: 0.1771 - val_loss: 0.4200 - val_mse: 0.4064 - val_mae: 0.4828 - val_root_mean_squared_error: 0.6375\n", "Epoch 417/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0457 - mse: 0.0320 - mae: 0.1273 - root_mean_squared_error: 0.1790\n", "Epoch 417: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0455 - mse: 0.0319 - mae: 0.1271 - root_mean_squared_error: 0.1786 - val_loss: 0.4199 - val_mse: 0.4063 - val_mae: 0.4776 - val_root_mean_squared_error: 0.6374\n", "Epoch 418/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0542 - mse: 0.0406 - mae: 0.1437 - root_mean_squared_error: 0.2015\n", "Epoch 418: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0542 - mse: 0.0406 - mae: 0.1437 - root_mean_squared_error: 0.2015 - val_loss: 0.4467 - val_mse: 0.4332 - val_mae: 0.5072 - val_root_mean_squared_error: 0.6582\n", "Epoch 419/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0614 - mse: 0.0478 - mae: 0.1641 - root_mean_squared_error: 0.2187\n", "Epoch 419: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0614 - mse: 0.0478 - mae: 0.1641 - root_mean_squared_error: 0.2187 - val_loss: 0.4460 - val_mse: 0.4324 - val_mae: 0.4882 - val_root_mean_squared_error: 0.6576\n", "Epoch 420/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0475 - mse: 0.0339 - mae: 0.1335 - root_mean_squared_error: 0.1842\n", "Epoch 420: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0475 - mse: 0.0339 - mae: 0.1335 - root_mean_squared_error: 0.1842 - val_loss: 0.4228 - val_mse: 0.4093 - val_mae: 0.4867 - val_root_mean_squared_error: 0.6397\n", "Epoch 421/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0484 - mse: 0.0348 - mae: 0.1359 - root_mean_squared_error: 0.1867\n", "Epoch 421: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0484 - mse: 0.0348 - mae: 0.1359 - root_mean_squared_error: 0.1867 - val_loss: 0.4415 - val_mse: 0.4279 - val_mae: 0.4984 - val_root_mean_squared_error: 0.6542\n", "Epoch 422/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0539 - mse: 0.0404 - mae: 0.1459 - root_mean_squared_error: 0.2009\n", "Epoch 422: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0539 - mse: 0.0404 - mae: 0.1459 - root_mean_squared_error: 0.2009 - val_loss: 0.4438 - val_mse: 0.4303 - val_mae: 0.4910 - val_root_mean_squared_error: 0.6559\n", "Epoch 423/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0430 - mse: 0.0295 - mae: 0.1208 - root_mean_squared_error: 0.1717\n", "Epoch 423: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0430 - mse: 0.0295 - mae: 0.1210 - root_mean_squared_error: 0.1719 - val_loss: 0.4405 - val_mse: 0.4271 - val_mae: 0.5056 - val_root_mean_squared_error: 0.6535\n", "Epoch 424/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0443 - mse: 0.0309 - mae: 0.1287 - root_mean_squared_error: 0.1758\n", "Epoch 424: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0442 - mse: 0.0308 - mae: 0.1284 - root_mean_squared_error: 0.1754 - val_loss: 0.4449 - val_mse: 0.4315 - val_mae: 0.4853 - val_root_mean_squared_error: 0.6569\n", "Epoch 425/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0479 - mse: 0.0346 - mae: 0.1345 - root_mean_squared_error: 0.1859\n", "Epoch 425: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0478 - mse: 0.0345 - mae: 0.1343 - root_mean_squared_error: 0.1857 - val_loss: 0.4216 - val_mse: 0.4082 - val_mae: 0.4780 - val_root_mean_squared_error: 0.6389\n", "Epoch 426/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0454 - mse: 0.0321 - mae: 0.1260 - root_mean_squared_error: 0.1792\n", "Epoch 426: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0454 - mse: 0.0321 - mae: 0.1260 - root_mean_squared_error: 0.1792 - val_loss: 0.4087 - val_mse: 0.3954 - val_mae: 0.4785 - val_root_mean_squared_error: 0.6288\n", "Epoch 427/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0447 - mse: 0.0314 - mae: 0.1269 - root_mean_squared_error: 0.1771\n", "Epoch 427: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0447 - mse: 0.0314 - mae: 0.1269 - root_mean_squared_error: 0.1771 - val_loss: 0.4519 - val_mse: 0.4386 - val_mae: 0.4980 - val_root_mean_squared_error: 0.6623\n", "Epoch 428/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0597 - mse: 0.0464 - mae: 0.1572 - root_mean_squared_error: 0.2155\n", "Epoch 428: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0597 - mse: 0.0464 - mae: 0.1572 - root_mean_squared_error: 0.2155 - val_loss: 0.4326 - val_mse: 0.4193 - val_mae: 0.4917 - val_root_mean_squared_error: 0.6475\n", "Epoch 429/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0461 - mse: 0.0329 - mae: 0.1324 - root_mean_squared_error: 0.1813\n", "Epoch 429: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 34ms/step - loss: 0.0461 - mse: 0.0329 - mae: 0.1324 - root_mean_squared_error: 0.1813 - val_loss: 0.4100 - val_mse: 0.3968 - val_mae: 0.4762 - val_root_mean_squared_error: 0.6299\n", "Epoch 430/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0426 - mse: 0.0294 - mae: 0.1265 - root_mean_squared_error: 0.1713\n", "Epoch 430: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 34ms/step - loss: 0.0426 - mse: 0.0294 - mae: 0.1265 - root_mean_squared_error: 0.1713 - val_loss: 0.4476 - val_mse: 0.4344 - val_mae: 0.5027 - val_root_mean_squared_error: 0.6591\n", "Epoch 431/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0510 - mse: 0.0379 - mae: 0.1429 - root_mean_squared_error: 0.1947\n", "Epoch 431: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0514 - mse: 0.0382 - mae: 0.1435 - root_mean_squared_error: 0.1955 - val_loss: 0.4061 - val_mse: 0.3930 - val_mae: 0.4716 - val_root_mean_squared_error: 0.6269\n", "Epoch 432/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0474 - mse: 0.0343 - mae: 0.1354 - root_mean_squared_error: 0.1852\n", "Epoch 432: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0474 - mse: 0.0343 - mae: 0.1354 - root_mean_squared_error: 0.1852 - val_loss: 0.4253 - val_mse: 0.4122 - val_mae: 0.4899 - val_root_mean_squared_error: 0.6420\n", "Epoch 433/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0475 - mse: 0.0344 - mae: 0.1298 - root_mean_squared_error: 0.1855\n", "Epoch 433: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0473 - mse: 0.0342 - mae: 0.1294 - root_mean_squared_error: 0.1850 - val_loss: 0.4171 - val_mse: 0.4040 - val_mae: 0.4795 - val_root_mean_squared_error: 0.6356\n", "Epoch 434/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0469 - mse: 0.0338 - mae: 0.1339 - root_mean_squared_error: 0.1839\n", "Epoch 434: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0469 - mse: 0.0338 - mae: 0.1339 - root_mean_squared_error: 0.1839 - val_loss: 0.4029 - val_mse: 0.3899 - val_mae: 0.4682 - val_root_mean_squared_error: 0.6244\n", "Epoch 435/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0407 - mse: 0.0277 - mae: 0.1230 - root_mean_squared_error: 0.1663\n", "Epoch 435: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0405 - mse: 0.0275 - mae: 0.1227 - root_mean_squared_error: 0.1660 - val_loss: 0.4062 - val_mse: 0.3933 - val_mae: 0.4737 - val_root_mean_squared_error: 0.6271\n", "Epoch 436/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0443 - mse: 0.0314 - mae: 0.1276 - root_mean_squared_error: 0.1771\n", "Epoch 436: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0443 - mse: 0.0314 - mae: 0.1276 - root_mean_squared_error: 0.1771 - val_loss: 0.4175 - val_mse: 0.4046 - val_mae: 0.4799 - val_root_mean_squared_error: 0.6360\n", "Epoch 437/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0453 - mse: 0.0324 - mae: 0.1282 - root_mean_squared_error: 0.1800\n", "Epoch 437: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0455 - mse: 0.0326 - mae: 0.1285 - root_mean_squared_error: 0.1805 - val_loss: 0.4508 - val_mse: 0.4379 - val_mae: 0.4938 - val_root_mean_squared_error: 0.6617\n", "Epoch 438/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0549 - mse: 0.0420 - mae: 0.1468 - root_mean_squared_error: 0.2050\n", "Epoch 438: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0549 - mse: 0.0420 - mae: 0.1468 - root_mean_squared_error: 0.2050 - val_loss: 0.4108 - val_mse: 0.3979 - val_mae: 0.4813 - val_root_mean_squared_error: 0.6308\n", "Epoch 439/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0544 - mse: 0.0415 - mae: 0.1471 - root_mean_squared_error: 0.2038\n", "Epoch 439: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0544 - mse: 0.0415 - mae: 0.1471 - root_mean_squared_error: 0.2038 - val_loss: 0.4081 - val_mse: 0.3952 - val_mae: 0.4835 - val_root_mean_squared_error: 0.6286\n", "Epoch 440/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0455 - mse: 0.0327 - mae: 0.1273 - root_mean_squared_error: 0.1808\n", "Epoch 440: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0454 - mse: 0.0325 - mae: 0.1273 - root_mean_squared_error: 0.1803 - val_loss: 0.4321 - val_mse: 0.4192 - val_mae: 0.4937 - val_root_mean_squared_error: 0.6475\n", "Epoch 441/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0482 - mse: 0.0353 - mae: 0.1353 - root_mean_squared_error: 0.1879\n", "Epoch 441: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0481 - mse: 0.0353 - mae: 0.1354 - root_mean_squared_error: 0.1878 - val_loss: 0.4447 - val_mse: 0.4319 - val_mae: 0.5029 - val_root_mean_squared_error: 0.6572\n", "Epoch 442/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0478 - mse: 0.0350 - mae: 0.1338 - root_mean_squared_error: 0.1870\n", "Epoch 442: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0477 - mse: 0.0349 - mae: 0.1338 - root_mean_squared_error: 0.1868 - val_loss: 0.4034 - val_mse: 0.3906 - val_mae: 0.4737 - val_root_mean_squared_error: 0.6250\n", "Epoch 443/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0396 - mse: 0.0268 - mae: 0.1159 - root_mean_squared_error: 0.1637\n", "Epoch 443: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0396 - mse: 0.0268 - mae: 0.1159 - root_mean_squared_error: 0.1637 - val_loss: 0.4177 - val_mse: 0.4049 - val_mae: 0.4831 - val_root_mean_squared_error: 0.6363\n", "Epoch 444/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0441 - mse: 0.0314 - mae: 0.1287 - root_mean_squared_error: 0.1771\n", "Epoch 444: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0441 - mse: 0.0314 - mae: 0.1287 - root_mean_squared_error: 0.1771 - val_loss: 0.4529 - val_mse: 0.4403 - val_mae: 0.5065 - val_root_mean_squared_error: 0.6635\n", "Epoch 445/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0523 - mse: 0.0396 - mae: 0.1444 - root_mean_squared_error: 0.1991\n", "Epoch 445: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0523 - mse: 0.0396 - mae: 0.1444 - root_mean_squared_error: 0.1991 - val_loss: 0.4087 - val_mse: 0.3960 - val_mae: 0.4730 - val_root_mean_squared_error: 0.6293\n", "Epoch 446/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0481 - mse: 0.0354 - mae: 0.1341 - root_mean_squared_error: 0.1883\n", "Epoch 446: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0481 - mse: 0.0354 - mae: 0.1341 - root_mean_squared_error: 0.1883 - val_loss: 0.4621 - val_mse: 0.4494 - val_mae: 0.5122 - val_root_mean_squared_error: 0.6704\n", "Epoch 447/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0438 - mse: 0.0311 - mae: 0.1299 - root_mean_squared_error: 0.1764\n", "Epoch 447: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0437 - mse: 0.0310 - mae: 0.1298 - root_mean_squared_error: 0.1762 - val_loss: 0.4221 - val_mse: 0.4095 - val_mae: 0.4800 - val_root_mean_squared_error: 0.6399\n", "Epoch 448/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0430 - mse: 0.0304 - mae: 0.1238 - root_mean_squared_error: 0.1745\n", "Epoch 448: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0430 - mse: 0.0304 - mae: 0.1238 - root_mean_squared_error: 0.1745 - val_loss: 0.4325 - val_mse: 0.4200 - val_mae: 0.4923 - val_root_mean_squared_error: 0.6481\n", "Epoch 449/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0465 - mse: 0.0339 - mae: 0.1342 - root_mean_squared_error: 0.1842\n", "Epoch 449: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0464 - mse: 0.0339 - mae: 0.1342 - root_mean_squared_error: 0.1840 - val_loss: 0.4205 - val_mse: 0.4079 - val_mae: 0.4822 - val_root_mean_squared_error: 0.6387\n", "Epoch 450/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0452 - mse: 0.0327 - mae: 0.1318 - root_mean_squared_error: 0.1808\n", "Epoch 450: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0468 - mse: 0.0342 - mae: 0.1332 - root_mean_squared_error: 0.1850 - val_loss: 0.4182 - val_mse: 0.4057 - val_mae: 0.4847 - val_root_mean_squared_error: 0.6369\n", "Epoch 451/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0454 - mse: 0.0329 - mae: 0.1323 - root_mean_squared_error: 0.1813\n", "Epoch 451: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0454 - mse: 0.0329 - mae: 0.1323 - root_mean_squared_error: 0.1813 - val_loss: 0.4081 - val_mse: 0.3956 - val_mae: 0.4759 - val_root_mean_squared_error: 0.6290\n", "Epoch 452/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0432 - mse: 0.0307 - mae: 0.1287 - root_mean_squared_error: 0.1752\n", "Epoch 452: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0432 - mse: 0.0307 - mae: 0.1287 - root_mean_squared_error: 0.1752 - val_loss: 0.4089 - val_mse: 0.3964 - val_mae: 0.4747 - val_root_mean_squared_error: 0.6296\n", "Epoch 453/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0408 - mse: 0.0283 - mae: 0.1211 - root_mean_squared_error: 0.1683\n", "Epoch 453: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 52ms/step - loss: 0.0408 - mse: 0.0283 - mae: 0.1211 - root_mean_squared_error: 0.1683 - val_loss: 0.3965 - val_mse: 0.3841 - val_mae: 0.4625 - val_root_mean_squared_error: 0.6197\n", "Epoch 454/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0459 - mse: 0.0335 - mae: 0.1311 - root_mean_squared_error: 0.1830\n", "Epoch 454: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0459 - mse: 0.0335 - mae: 0.1311 - root_mean_squared_error: 0.1830 - val_loss: 0.4115 - val_mse: 0.3990 - val_mae: 0.4811 - val_root_mean_squared_error: 0.6317\n", "Epoch 455/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0483 - mse: 0.0359 - mae: 0.1419 - root_mean_squared_error: 0.1895\n", "Epoch 455: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0484 - mse: 0.0360 - mae: 0.1423 - root_mean_squared_error: 0.1899 - val_loss: 0.4251 - val_mse: 0.4127 - val_mae: 0.4901 - val_root_mean_squared_error: 0.6424\n", "Epoch 456/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0433 - mse: 0.0309 - mae: 0.1266 - root_mean_squared_error: 0.1758\n", "Epoch 456: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0433 - mse: 0.0309 - mae: 0.1266 - root_mean_squared_error: 0.1758 - val_loss: 0.4313 - val_mse: 0.4189 - val_mae: 0.4940 - val_root_mean_squared_error: 0.6472\n", "Epoch 457/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0441 - mse: 0.0317 - mae: 0.1282 - root_mean_squared_error: 0.1781\n", "Epoch 457: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0442 - mse: 0.0318 - mae: 0.1283 - root_mean_squared_error: 0.1784 - val_loss: 0.4303 - val_mse: 0.4180 - val_mae: 0.4902 - val_root_mean_squared_error: 0.6465\n", "Epoch 458/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0489 - mse: 0.0365 - mae: 0.1380 - root_mean_squared_error: 0.1911\n", "Epoch 458: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0489 - mse: 0.0365 - mae: 0.1380 - root_mean_squared_error: 0.1911 - val_loss: 0.4063 - val_mse: 0.3939 - val_mae: 0.4734 - val_root_mean_squared_error: 0.6276\n", "Epoch 459/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0442 - mse: 0.0319 - mae: 0.1323 - root_mean_squared_error: 0.1787\n", "Epoch 459: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0441 - mse: 0.0318 - mae: 0.1322 - root_mean_squared_error: 0.1784 - val_loss: 0.4144 - val_mse: 0.4021 - val_mae: 0.4804 - val_root_mean_squared_error: 0.6341\n", "Epoch 460/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0463 - mse: 0.0340 - mae: 0.1315 - root_mean_squared_error: 0.1844\n", "Epoch 460: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0463 - mse: 0.0340 - mae: 0.1315 - root_mean_squared_error: 0.1844 - val_loss: 0.4469 - val_mse: 0.4347 - val_mae: 0.5097 - val_root_mean_squared_error: 0.6593\n", "Epoch 461/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0495 - mse: 0.0372 - mae: 0.1424 - root_mean_squared_error: 0.1929\n", "Epoch 461: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0492 - mse: 0.0369 - mae: 0.1418 - root_mean_squared_error: 0.1922 - val_loss: 0.4307 - val_mse: 0.4184 - val_mae: 0.4918 - val_root_mean_squared_error: 0.6469\n", "Epoch 462/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0552 - mse: 0.0430 - mae: 0.1451 - root_mean_squared_error: 0.2073\n", "Epoch 462: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0552 - mse: 0.0430 - mae: 0.1451 - root_mean_squared_error: 0.2073 - val_loss: 0.4555 - val_mse: 0.4431 - val_mae: 0.5043 - val_root_mean_squared_error: 0.6657\n", "Epoch 463/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0720 - mse: 0.0597 - mae: 0.1757 - root_mean_squared_error: 0.2443\n", "Epoch 463: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0720 - mse: 0.0597 - mae: 0.1757 - root_mean_squared_error: 0.2443 - val_loss: 0.4449 - val_mse: 0.4325 - val_mae: 0.4886 - val_root_mean_squared_error: 0.6576\n", "Epoch 464/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0565 - mse: 0.0442 - mae: 0.1538 - root_mean_squared_error: 0.2102\n", "Epoch 464: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0568 - mse: 0.0444 - mae: 0.1542 - root_mean_squared_error: 0.2108 - val_loss: 0.4088 - val_mse: 0.3964 - val_mae: 0.4740 - val_root_mean_squared_error: 0.6296\n", "Epoch 465/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0497 - mse: 0.0373 - mae: 0.1401 - root_mean_squared_error: 0.1932\n", "Epoch 465: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0498 - mse: 0.0374 - mae: 0.1404 - root_mean_squared_error: 0.1935 - val_loss: 0.4309 - val_mse: 0.4185 - val_mae: 0.4847 - val_root_mean_squared_error: 0.6469\n", "Epoch 466/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0445 - mse: 0.0321 - mae: 0.1293 - root_mean_squared_error: 0.1791\n", "Epoch 466: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0447 - mse: 0.0323 - mae: 0.1296 - root_mean_squared_error: 0.1797 - val_loss: 0.4212 - val_mse: 0.4088 - val_mae: 0.4836 - val_root_mean_squared_error: 0.6394\n", "Epoch 467/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0498 - mse: 0.0375 - mae: 0.1390 - root_mean_squared_error: 0.1935\n", "Epoch 467: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0497 - mse: 0.0374 - mae: 0.1390 - root_mean_squared_error: 0.1933 - val_loss: 0.4429 - val_mse: 0.4306 - val_mae: 0.4982 - val_root_mean_squared_error: 0.6562\n", "Epoch 468/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0419 - mse: 0.0295 - mae: 0.1217 - root_mean_squared_error: 0.1719\n", "Epoch 468: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 54ms/step - loss: 0.0421 - mse: 0.0298 - mae: 0.1222 - root_mean_squared_error: 0.1725 - val_loss: 0.4184 - val_mse: 0.4061 - val_mae: 0.4846 - val_root_mean_squared_error: 0.6372\n", "Epoch 469/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0491 - mse: 0.0369 - mae: 0.1405 - root_mean_squared_error: 0.1920\n", "Epoch 469: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0488 - mse: 0.0365 - mae: 0.1399 - root_mean_squared_error: 0.1912 - val_loss: 0.4352 - val_mse: 0.4230 - val_mae: 0.4954 - val_root_mean_squared_error: 0.6504\n", "Epoch 470/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0414 - mse: 0.0291 - mae: 0.1228 - root_mean_squared_error: 0.1707\n", "Epoch 470: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0414 - mse: 0.0291 - mae: 0.1228 - root_mean_squared_error: 0.1707 - val_loss: 0.4058 - val_mse: 0.3936 - val_mae: 0.4705 - val_root_mean_squared_error: 0.6274\n", "Epoch 471/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0471 - mse: 0.0349 - mae: 0.1345 - root_mean_squared_error: 0.1867\n", "Epoch 471: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0471 - mse: 0.0349 - mae: 0.1345 - root_mean_squared_error: 0.1867 - val_loss: 0.4063 - val_mse: 0.3941 - val_mae: 0.4764 - val_root_mean_squared_error: 0.6278\n", "Epoch 472/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0421 - mse: 0.0299 - mae: 0.1256 - root_mean_squared_error: 0.1730\n", "Epoch 472: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 32ms/step - loss: 0.0421 - mse: 0.0299 - mae: 0.1256 - root_mean_squared_error: 0.1729 - val_loss: 0.4387 - val_mse: 0.4266 - val_mae: 0.4939 - val_root_mean_squared_error: 0.6531\n", "Epoch 473/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0375 - mse: 0.0254 - mae: 0.1123 - root_mean_squared_error: 0.1594\n", "Epoch 473: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0375 - mse: 0.0254 - mae: 0.1123 - root_mean_squared_error: 0.1594 - val_loss: 0.4289 - val_mse: 0.4168 - val_mae: 0.4952 - val_root_mean_squared_error: 0.6456\n", "Epoch 474/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0465 - mse: 0.0344 - mae: 0.1333 - root_mean_squared_error: 0.1855\n", "Epoch 474: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 34ms/step - loss: 0.0462 - mse: 0.0342 - mae: 0.1328 - root_mean_squared_error: 0.1848 - val_loss: 0.4236 - val_mse: 0.4116 - val_mae: 0.4847 - val_root_mean_squared_error: 0.6415\n", "Epoch 475/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0392 - mse: 0.0272 - mae: 0.1186 - root_mean_squared_error: 0.1649\n", "Epoch 475: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0399 - mse: 0.0278 - mae: 0.1200 - root_mean_squared_error: 0.1668 - val_loss: 0.4181 - val_mse: 0.4061 - val_mae: 0.4817 - val_root_mean_squared_error: 0.6372\n", "Epoch 476/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0467 - mse: 0.0347 - mae: 0.1368 - root_mean_squared_error: 0.1864\n", "Epoch 476: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0465 - mse: 0.0346 - mae: 0.1365 - root_mean_squared_error: 0.1859 - val_loss: 0.4080 - val_mse: 0.3960 - val_mae: 0.4800 - val_root_mean_squared_error: 0.6293\n", "Epoch 477/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0415 - mse: 0.0296 - mae: 0.1218 - root_mean_squared_error: 0.1719\n", "Epoch 477: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0415 - mse: 0.0296 - mae: 0.1218 - root_mean_squared_error: 0.1719 - val_loss: 0.4246 - val_mse: 0.4127 - val_mae: 0.4910 - val_root_mean_squared_error: 0.6424\n", "Epoch 478/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0434 - mse: 0.0314 - mae: 0.1292 - root_mean_squared_error: 0.1773\n", "Epoch 478: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0434 - mse: 0.0314 - mae: 0.1292 - root_mean_squared_error: 0.1773 - val_loss: 0.4119 - val_mse: 0.3999 - val_mae: 0.4827 - val_root_mean_squared_error: 0.6324\n", "Epoch 479/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0490 - mse: 0.0371 - mae: 0.1426 - root_mean_squared_error: 0.1926\n", "Epoch 479: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0490 - mse: 0.0371 - mae: 0.1426 - root_mean_squared_error: 0.1925 - val_loss: 0.4328 - val_mse: 0.4209 - val_mae: 0.4935 - val_root_mean_squared_error: 0.6488\n", "Epoch 480/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0498 - mse: 0.0379 - mae: 0.1410 - root_mean_squared_error: 0.1947\n", "Epoch 480: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0498 - mse: 0.0379 - mae: 0.1410 - root_mean_squared_error: 0.1947 - val_loss: 0.4095 - val_mse: 0.3976 - val_mae: 0.4736 - val_root_mean_squared_error: 0.6305\n", "Epoch 481/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0514 - mse: 0.0396 - mae: 0.1451 - root_mean_squared_error: 0.1989\n", "Epoch 481: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0514 - mse: 0.0396 - mae: 0.1451 - root_mean_squared_error: 0.1989 - val_loss: 0.4329 - val_mse: 0.4210 - val_mae: 0.5000 - val_root_mean_squared_error: 0.6489\n", "Epoch 482/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0457 - mse: 0.0338 - mae: 0.1345 - root_mean_squared_error: 0.1837\n", "Epoch 482: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0457 - mse: 0.0338 - mae: 0.1345 - root_mean_squared_error: 0.1837 - val_loss: 0.4136 - val_mse: 0.4016 - val_mae: 0.4824 - val_root_mean_squared_error: 0.6338\n", "Epoch 483/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0378 - mse: 0.0259 - mae: 0.1162 - root_mean_squared_error: 0.1609\n", "Epoch 483: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 55ms/step - loss: 0.0378 - mse: 0.0259 - mae: 0.1162 - root_mean_squared_error: 0.1609 - val_loss: 0.4136 - val_mse: 0.4017 - val_mae: 0.4764 - val_root_mean_squared_error: 0.6338\n", "Epoch 484/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0384 - mse: 0.0266 - mae: 0.1198 - root_mean_squared_error: 0.1631\n", "Epoch 484: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 33ms/step - loss: 0.0385 - mse: 0.0267 - mae: 0.1197 - root_mean_squared_error: 0.1633 - val_loss: 0.4109 - val_mse: 0.3991 - val_mae: 0.4779 - val_root_mean_squared_error: 0.6317\n", "Epoch 485/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0377 - mse: 0.0259 - mae: 0.1143 - root_mean_squared_error: 0.1610\n", "Epoch 485: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0377 - mse: 0.0259 - mae: 0.1143 - root_mean_squared_error: 0.1610 - val_loss: 0.4068 - val_mse: 0.3951 - val_mae: 0.4727 - val_root_mean_squared_error: 0.6285\n", "Epoch 486/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0485 - mse: 0.0368 - mae: 0.1348 - root_mean_squared_error: 0.1919\n", "Epoch 486: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0485 - mse: 0.0368 - mae: 0.1348 - root_mean_squared_error: 0.1919 - val_loss: 0.3974 - val_mse: 0.3857 - val_mae: 0.4686 - val_root_mean_squared_error: 0.6211\n", "Epoch 487/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0485 - mse: 0.0368 - mae: 0.1398 - root_mean_squared_error: 0.1919\n", "Epoch 487: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0485 - mse: 0.0368 - mae: 0.1398 - root_mean_squared_error: 0.1919 - val_loss: 0.4466 - val_mse: 0.4348 - val_mae: 0.5041 - val_root_mean_squared_error: 0.6594\n", "Epoch 488/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0439 - mse: 0.0322 - mae: 0.1281 - root_mean_squared_error: 0.1793\n", "Epoch 488: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0438 - mse: 0.0321 - mae: 0.1282 - root_mean_squared_error: 0.1791 - val_loss: 0.4345 - val_mse: 0.4228 - val_mae: 0.4957 - val_root_mean_squared_error: 0.6502\n", "Epoch 489/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0404 - mse: 0.0287 - mae: 0.1231 - root_mean_squared_error: 0.1694\n", "Epoch 489: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0404 - mse: 0.0288 - mae: 0.1234 - root_mean_squared_error: 0.1696 - val_loss: 0.4596 - val_mse: 0.4479 - val_mae: 0.5243 - val_root_mean_squared_error: 0.6693\n", "Epoch 490/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0493 - mse: 0.0377 - mae: 0.1395 - root_mean_squared_error: 0.1941\n", "Epoch 490: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0492 - mse: 0.0375 - mae: 0.1393 - root_mean_squared_error: 0.1937 - val_loss: 0.4177 - val_mse: 0.4061 - val_mae: 0.4811 - val_root_mean_squared_error: 0.6373\n", "Epoch 491/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0549 - mse: 0.0432 - mae: 0.1523 - root_mean_squared_error: 0.2079\n", "Epoch 491: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0549 - mse: 0.0432 - mae: 0.1523 - root_mean_squared_error: 0.2079 - val_loss: 0.4245 - val_mse: 0.4128 - val_mae: 0.4954 - val_root_mean_squared_error: 0.6425\n", "Epoch 492/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0550 - mse: 0.0433 - mae: 0.1495 - root_mean_squared_error: 0.2081\n", "Epoch 492: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0550 - mse: 0.0433 - mae: 0.1495 - root_mean_squared_error: 0.2081 - val_loss: 0.4011 - val_mse: 0.3894 - val_mae: 0.4809 - val_root_mean_squared_error: 0.6240\n", "Epoch 493/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0474 - mse: 0.0357 - mae: 0.1363 - root_mean_squared_error: 0.1891\n", "Epoch 493: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0474 - mse: 0.0357 - mae: 0.1363 - root_mean_squared_error: 0.1891 - val_loss: 0.4075 - val_mse: 0.3958 - val_mae: 0.4757 - val_root_mean_squared_error: 0.6292\n", "Epoch 494/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0440 - mse: 0.0323 - mae: 0.1306 - root_mean_squared_error: 0.1798\n", "Epoch 494: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0439 - mse: 0.0322 - mae: 0.1307 - root_mean_squared_error: 0.1796 - val_loss: 0.4249 - val_mse: 0.4132 - val_mae: 0.4769 - val_root_mean_squared_error: 0.6428\n", "Epoch 495/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0409 - mse: 0.0292 - mae: 0.1231 - root_mean_squared_error: 0.1709\n", "Epoch 495: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0409 - mse: 0.0292 - mae: 0.1231 - root_mean_squared_error: 0.1709 - val_loss: 0.4044 - val_mse: 0.3927 - val_mae: 0.4766 - val_root_mean_squared_error: 0.6266\n", "Epoch 496/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0427 - mse: 0.0311 - mae: 0.1253 - root_mean_squared_error: 0.1763\n", "Epoch 496: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0427 - mse: 0.0311 - mae: 0.1253 - root_mean_squared_error: 0.1763 - val_loss: 0.4367 - val_mse: 0.4251 - val_mae: 0.5007 - val_root_mean_squared_error: 0.6520\n", "Epoch 497/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0459 - mse: 0.0343 - mae: 0.1352 - root_mean_squared_error: 0.1852\n", "Epoch 497: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0459 - mse: 0.0343 - mae: 0.1352 - root_mean_squared_error: 0.1852 - val_loss: 0.4423 - val_mse: 0.4307 - val_mae: 0.4991 - val_root_mean_squared_error: 0.6563\n", "Epoch 498/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0459 - mse: 0.0343 - mae: 0.1319 - root_mean_squared_error: 0.1852\n", "Epoch 498: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0459 - mse: 0.0343 - mae: 0.1319 - root_mean_squared_error: 0.1852 - val_loss: 0.4195 - val_mse: 0.4080 - val_mae: 0.4854 - val_root_mean_squared_error: 0.6387\n", "Epoch 499/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0395 - mse: 0.0279 - mae: 0.1189 - root_mean_squared_error: 0.1671\n", "Epoch 499: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0395 - mse: 0.0279 - mae: 0.1189 - root_mean_squared_error: 0.1671 - val_loss: 0.4331 - val_mse: 0.4215 - val_mae: 0.4842 - val_root_mean_squared_error: 0.6493\n", "Epoch 500/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0357 - mse: 0.0242 - mae: 0.1129 - root_mean_squared_error: 0.1555\n", "Epoch 500: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0357 - mse: 0.0242 - mae: 0.1129 - root_mean_squared_error: 0.1555 - val_loss: 0.4290 - val_mse: 0.4175 - val_mae: 0.5028 - val_root_mean_squared_error: 0.6461\n", "Epoch 501/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0386 - mse: 0.0271 - mae: 0.1154 - root_mean_squared_error: 0.1647\n", "Epoch 501: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0385 - mse: 0.0270 - mae: 0.1151 - root_mean_squared_error: 0.1644 - val_loss: 0.4314 - val_mse: 0.4200 - val_mae: 0.4839 - val_root_mean_squared_error: 0.6481\n", "Epoch 502/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0428 - mse: 0.0314 - mae: 0.1261 - root_mean_squared_error: 0.1771\n", "Epoch 502: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 0.0428 - mse: 0.0314 - mae: 0.1261 - root_mean_squared_error: 0.1771 - val_loss: 0.4166 - val_mse: 0.4053 - val_mae: 0.4831 - val_root_mean_squared_error: 0.6366\n", "Epoch 503/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0493 - mse: 0.0379 - mae: 0.1378 - root_mean_squared_error: 0.1947\n", "Epoch 503: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0493 - mse: 0.0379 - mae: 0.1383 - root_mean_squared_error: 0.1947 - val_loss: 0.4196 - val_mse: 0.4082 - val_mae: 0.4897 - val_root_mean_squared_error: 0.6389\n", "Epoch 504/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0441 - mse: 0.0327 - mae: 0.1305 - root_mean_squared_error: 0.1807\n", "Epoch 504: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0441 - mse: 0.0327 - mae: 0.1305 - root_mean_squared_error: 0.1807 - val_loss: 0.4218 - val_mse: 0.4104 - val_mae: 0.4844 - val_root_mean_squared_error: 0.6406\n", "Epoch 505/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0430 - mse: 0.0316 - mae: 0.1268 - root_mean_squared_error: 0.1778\n", "Epoch 505: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0430 - mse: 0.0316 - mae: 0.1268 - root_mean_squared_error: 0.1778 - val_loss: 0.4229 - val_mse: 0.4115 - val_mae: 0.4953 - val_root_mean_squared_error: 0.6415\n", "Epoch 506/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0467 - mse: 0.0353 - mae: 0.1356 - root_mean_squared_error: 0.1879\n", "Epoch 506: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0467 - mse: 0.0353 - mae: 0.1360 - root_mean_squared_error: 0.1879 - val_loss: 0.4362 - val_mse: 0.4248 - val_mae: 0.5024 - val_root_mean_squared_error: 0.6518\n", "Epoch 507/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0463 - mse: 0.0349 - mae: 0.1344 - root_mean_squared_error: 0.1868\n", "Epoch 507: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0460 - mse: 0.0346 - mae: 0.1341 - root_mean_squared_error: 0.1860 - val_loss: 0.4186 - val_mse: 0.4072 - val_mae: 0.4837 - val_root_mean_squared_error: 0.6382\n", "Epoch 508/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0508 - mse: 0.0394 - mae: 0.1453 - root_mean_squared_error: 0.1986\n", "Epoch 508: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0507 - mse: 0.0393 - mae: 0.1451 - root_mean_squared_error: 0.1982 - val_loss: 0.4045 - val_mse: 0.3931 - val_mae: 0.4723 - val_root_mean_squared_error: 0.6270\n", "Epoch 509/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0396 - mse: 0.0283 - mae: 0.1199 - root_mean_squared_error: 0.1681\n", "Epoch 509: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0396 - mse: 0.0283 - mae: 0.1199 - root_mean_squared_error: 0.1681 - val_loss: 0.4338 - val_mse: 0.4224 - val_mae: 0.4916 - val_root_mean_squared_error: 0.6499\n", "Epoch 510/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0475 - mse: 0.0362 - mae: 0.1371 - root_mean_squared_error: 0.1901\n", "Epoch 510: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0475 - mse: 0.0362 - mae: 0.1371 - root_mean_squared_error: 0.1901 - val_loss: 0.4157 - val_mse: 0.4044 - val_mae: 0.4851 - val_root_mean_squared_error: 0.6359\n", "Epoch 511/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0507 - mse: 0.0394 - mae: 0.1409 - root_mean_squared_error: 0.1984\n", "Epoch 511: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0508 - mse: 0.0394 - mae: 0.1412 - root_mean_squared_error: 0.1986 - val_loss: 0.4185 - val_mse: 0.4071 - val_mae: 0.4773 - val_root_mean_squared_error: 0.6381\n", "Epoch 512/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0410 - mse: 0.0297 - mae: 0.1237 - root_mean_squared_error: 0.1723\n", "Epoch 512: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 34ms/step - loss: 0.0408 - mse: 0.0294 - mae: 0.1232 - root_mean_squared_error: 0.1716 - val_loss: 0.4079 - val_mse: 0.3966 - val_mae: 0.4825 - val_root_mean_squared_error: 0.6298\n", "Epoch 513/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0434 - mse: 0.0321 - mae: 0.1284 - root_mean_squared_error: 0.1792\n", "Epoch 513: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0438 - mse: 0.0325 - mae: 0.1290 - root_mean_squared_error: 0.1802 - val_loss: 0.4118 - val_mse: 0.4005 - val_mae: 0.4795 - val_root_mean_squared_error: 0.6328\n", "Epoch 514/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0455 - mse: 0.0343 - mae: 0.1313 - root_mean_squared_error: 0.1852\n", "Epoch 514: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0455 - mse: 0.0343 - mae: 0.1313 - root_mean_squared_error: 0.1852 - val_loss: 0.4126 - val_mse: 0.4014 - val_mae: 0.4836 - val_root_mean_squared_error: 0.6335\n", "Epoch 515/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0397 - mse: 0.0285 - mae: 0.1232 - root_mean_squared_error: 0.1688\n", "Epoch 515: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0397 - mse: 0.0285 - mae: 0.1232 - root_mean_squared_error: 0.1688 - val_loss: 0.4125 - val_mse: 0.4013 - val_mae: 0.4770 - val_root_mean_squared_error: 0.6335\n", "Epoch 516/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0450 - mse: 0.0338 - mae: 0.1333 - root_mean_squared_error: 0.1838\n", "Epoch 516: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0450 - mse: 0.0338 - mae: 0.1333 - root_mean_squared_error: 0.1838 - val_loss: 0.4036 - val_mse: 0.3924 - val_mae: 0.4746 - val_root_mean_squared_error: 0.6264\n", "Epoch 517/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0395 - mse: 0.0283 - mae: 0.1215 - root_mean_squared_error: 0.1683\n", "Epoch 517: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0394 - mse: 0.0282 - mae: 0.1212 - root_mean_squared_error: 0.1679 - val_loss: 0.4159 - val_mse: 0.4047 - val_mae: 0.4798 - val_root_mean_squared_error: 0.6362\n", "Epoch 518/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0453 - mse: 0.0341 - mae: 0.1316 - root_mean_squared_error: 0.1846\n", "Epoch 518: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0453 - mse: 0.0341 - mae: 0.1316 - root_mean_squared_error: 0.1846 - val_loss: 0.4007 - val_mse: 0.3895 - val_mae: 0.4716 - val_root_mean_squared_error: 0.6241\n", "Epoch 519/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0380 - mse: 0.0269 - mae: 0.1167 - root_mean_squared_error: 0.1639\n", "Epoch 519: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0381 - mse: 0.0269 - mae: 0.1170 - root_mean_squared_error: 0.1640 - val_loss: 0.4315 - val_mse: 0.4204 - val_mae: 0.4894 - val_root_mean_squared_error: 0.6484\n", "Epoch 520/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0405 - mse: 0.0294 - mae: 0.1234 - root_mean_squared_error: 0.1715\n", "Epoch 520: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0405 - mse: 0.0294 - mae: 0.1234 - root_mean_squared_error: 0.1715 - val_loss: 0.4425 - val_mse: 0.4314 - val_mae: 0.4941 - val_root_mean_squared_error: 0.6568\n", "Epoch 521/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0430 - mse: 0.0320 - mae: 0.1273 - root_mean_squared_error: 0.1788\n", "Epoch 521: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0430 - mse: 0.0320 - mae: 0.1273 - root_mean_squared_error: 0.1788 - val_loss: 0.4129 - val_mse: 0.4019 - val_mae: 0.4812 - val_root_mean_squared_error: 0.6339\n", "Epoch 522/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0406 - mse: 0.0295 - mae: 0.1237 - root_mean_squared_error: 0.1718\n", "Epoch 522: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0406 - mse: 0.0295 - mae: 0.1238 - root_mean_squared_error: 0.1718 - val_loss: 0.4134 - val_mse: 0.4023 - val_mae: 0.4824 - val_root_mean_squared_error: 0.6343\n", "Epoch 523/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0451 - mse: 0.0341 - mae: 0.1343 - root_mean_squared_error: 0.1847\n", "Epoch 523: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0450 - mse: 0.0340 - mae: 0.1341 - root_mean_squared_error: 0.1844 - val_loss: 0.4188 - val_mse: 0.4078 - val_mae: 0.4830 - val_root_mean_squared_error: 0.6386\n", "Epoch 524/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0398 - mse: 0.0288 - mae: 0.1231 - root_mean_squared_error: 0.1696\n", "Epoch 524: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0398 - mse: 0.0288 - mae: 0.1231 - root_mean_squared_error: 0.1696 - val_loss: 0.3952 - val_mse: 0.3843 - val_mae: 0.4667 - val_root_mean_squared_error: 0.6199\n", "Epoch 525/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0413 - mse: 0.0303 - mae: 0.1233 - root_mean_squared_error: 0.1741\n", "Epoch 525: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0409 - mse: 0.0299 - mae: 0.1224 - root_mean_squared_error: 0.1729 - val_loss: 0.3931 - val_mse: 0.3821 - val_mae: 0.4682 - val_root_mean_squared_error: 0.6182\n", "Epoch 526/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0381 - mse: 0.0271 - mae: 0.1165 - root_mean_squared_error: 0.1647\n", "Epoch 526: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0380 - mse: 0.0271 - mae: 0.1166 - root_mean_squared_error: 0.1646 - val_loss: 0.4136 - val_mse: 0.4027 - val_mae: 0.4831 - val_root_mean_squared_error: 0.6346\n", "Epoch 527/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0447 - mse: 0.0337 - mae: 0.1339 - root_mean_squared_error: 0.1837\n", "Epoch 527: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0445 - mse: 0.0336 - mae: 0.1337 - root_mean_squared_error: 0.1832 - val_loss: 0.4358 - val_mse: 0.4249 - val_mae: 0.4886 - val_root_mean_squared_error: 0.6518\n", "Epoch 528/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0401 - mse: 0.0292 - mae: 0.1241 - root_mean_squared_error: 0.1707\n", "Epoch 528: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 60ms/step - loss: 0.0401 - mse: 0.0292 - mae: 0.1241 - root_mean_squared_error: 0.1707 - val_loss: 0.4070 - val_mse: 0.3961 - val_mae: 0.4653 - val_root_mean_squared_error: 0.6294\n", "Epoch 529/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0566 - mse: 0.0457 - mae: 0.1544 - root_mean_squared_error: 0.2137\n", "Epoch 529: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0566 - mse: 0.0457 - mae: 0.1544 - root_mean_squared_error: 0.2137 - val_loss: 0.3998 - val_mse: 0.3888 - val_mae: 0.4750 - val_root_mean_squared_error: 0.6236\n", "Epoch 530/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0400 - mse: 0.0290 - mae: 0.1215 - root_mean_squared_error: 0.1704\n", "Epoch 530: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0400 - mse: 0.0290 - mae: 0.1215 - root_mean_squared_error: 0.1704 - val_loss: 0.4069 - val_mse: 0.3959 - val_mae: 0.4832 - val_root_mean_squared_error: 0.6292\n", "Epoch 531/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0391 - mse: 0.0282 - mae: 0.1205 - root_mean_squared_error: 0.1679\n", "Epoch 531: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0391 - mse: 0.0282 - mae: 0.1205 - root_mean_squared_error: 0.1679 - val_loss: 0.4117 - val_mse: 0.4008 - val_mae: 0.4799 - val_root_mean_squared_error: 0.6331\n", "Epoch 532/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0540 - mse: 0.0431 - mae: 0.1515 - root_mean_squared_error: 0.2077\n", "Epoch 532: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0542 - mse: 0.0433 - mae: 0.1520 - root_mean_squared_error: 0.2080 - val_loss: 0.4301 - val_mse: 0.4191 - val_mae: 0.5013 - val_root_mean_squared_error: 0.6474\n", "Epoch 533/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0459 - mse: 0.0349 - mae: 0.1335 - root_mean_squared_error: 0.1868\n", "Epoch 533: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0457 - mse: 0.0347 - mae: 0.1332 - root_mean_squared_error: 0.1864 - val_loss: 0.4073 - val_mse: 0.3964 - val_mae: 0.4787 - val_root_mean_squared_error: 0.6296\n", "Epoch 534/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0389 - mse: 0.0280 - mae: 0.1221 - root_mean_squared_error: 0.1674\n", "Epoch 534: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0389 - mse: 0.0280 - mae: 0.1221 - root_mean_squared_error: 0.1674 - val_loss: 0.4207 - val_mse: 0.4098 - val_mae: 0.4857 - val_root_mean_squared_error: 0.6402\n", "Epoch 535/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0398 - mse: 0.0289 - mae: 0.1220 - root_mean_squared_error: 0.1699\n", "Epoch 535: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0398 - mse: 0.0289 - mae: 0.1220 - root_mean_squared_error: 0.1699 - val_loss: 0.4090 - val_mse: 0.3982 - val_mae: 0.4782 - val_root_mean_squared_error: 0.6310\n", "Epoch 536/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0519 - mse: 0.0410 - mae: 0.1425 - root_mean_squared_error: 0.2026\n", "Epoch 536: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0519 - mse: 0.0410 - mae: 0.1425 - root_mean_squared_error: 0.2026 - val_loss: 0.4403 - val_mse: 0.4295 - val_mae: 0.4973 - val_root_mean_squared_error: 0.6553\n", "Epoch 537/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0447 - mse: 0.0338 - mae: 0.1324 - root_mean_squared_error: 0.1839\n", "Epoch 537: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0447 - mse: 0.0338 - mae: 0.1324 - root_mean_squared_error: 0.1839 - val_loss: 0.4172 - val_mse: 0.4063 - val_mae: 0.4844 - val_root_mean_squared_error: 0.6375\n", "Epoch 538/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0401 - mse: 0.0293 - mae: 0.1233 - root_mean_squared_error: 0.1712\n", "Epoch 538: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0400 - mse: 0.0292 - mae: 0.1232 - root_mean_squared_error: 0.1709 - val_loss: 0.4131 - val_mse: 0.4023 - val_mae: 0.4814 - val_root_mean_squared_error: 0.6342\n", "Epoch 539/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0425 - mse: 0.0317 - mae: 0.1260 - root_mean_squared_error: 0.1781\n", "Epoch 539: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0425 - mse: 0.0317 - mae: 0.1260 - root_mean_squared_error: 0.1781 - val_loss: 0.4380 - val_mse: 0.4272 - val_mae: 0.4889 - val_root_mean_squared_error: 0.6536\n", "Epoch 540/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0390 - mse: 0.0282 - mae: 0.1216 - root_mean_squared_error: 0.1680\n", "Epoch 540: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0390 - mse: 0.0282 - mae: 0.1217 - root_mean_squared_error: 0.1679 - val_loss: 0.4011 - val_mse: 0.3903 - val_mae: 0.4764 - val_root_mean_squared_error: 0.6248\n", "Epoch 541/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0482 - mse: 0.0375 - mae: 0.1428 - root_mean_squared_error: 0.1936\n", "Epoch 541: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0481 - mse: 0.0373 - mae: 0.1425 - root_mean_squared_error: 0.1932 - val_loss: 0.4254 - val_mse: 0.4147 - val_mae: 0.4838 - val_root_mean_squared_error: 0.6439\n", "Epoch 542/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0438 - mse: 0.0331 - mae: 0.1309 - root_mean_squared_error: 0.1818\n", "Epoch 542: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0438 - mse: 0.0331 - mae: 0.1309 - root_mean_squared_error: 0.1818 - val_loss: 0.4150 - val_mse: 0.4043 - val_mae: 0.4938 - val_root_mean_squared_error: 0.6358\n", "Epoch 543/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0397 - mse: 0.0290 - mae: 0.1226 - root_mean_squared_error: 0.1702\n", "Epoch 543: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0398 - mse: 0.0291 - mae: 0.1228 - root_mean_squared_error: 0.1705 - val_loss: 0.3948 - val_mse: 0.3841 - val_mae: 0.4758 - val_root_mean_squared_error: 0.6197\n", "Epoch 544/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0464 - mse: 0.0356 - mae: 0.1363 - root_mean_squared_error: 0.1888\n", "Epoch 544: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 52ms/step - loss: 0.0462 - mse: 0.0355 - mae: 0.1361 - root_mean_squared_error: 0.1884 - val_loss: 0.4136 - val_mse: 0.4028 - val_mae: 0.4792 - val_root_mean_squared_error: 0.6347\n", "Epoch 545/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0392 - mse: 0.0285 - mae: 0.1253 - root_mean_squared_error: 0.1687\n", "Epoch 545: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0392 - mse: 0.0285 - mae: 0.1253 - root_mean_squared_error: 0.1687 - val_loss: 0.4038 - val_mse: 0.3931 - val_mae: 0.4742 - val_root_mean_squared_error: 0.6270\n", "Epoch 546/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0430 - mse: 0.0323 - mae: 0.1289 - root_mean_squared_error: 0.1796\n", "Epoch 546: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0428 - mse: 0.0321 - mae: 0.1286 - root_mean_squared_error: 0.1793 - val_loss: 0.3873 - val_mse: 0.3766 - val_mae: 0.4631 - val_root_mean_squared_error: 0.6137\n", "Epoch 547/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0378 - mse: 0.0271 - mae: 0.1195 - root_mean_squared_error: 0.1647\n", "Epoch 547: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0378 - mse: 0.0271 - mae: 0.1195 - root_mean_squared_error: 0.1647 - val_loss: 0.4144 - val_mse: 0.4037 - val_mae: 0.4838 - val_root_mean_squared_error: 0.6354\n", "Epoch 548/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0415 - mse: 0.0308 - mae: 0.1271 - root_mean_squared_error: 0.1755\n", "Epoch 548: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0415 - mse: 0.0308 - mae: 0.1269 - root_mean_squared_error: 0.1755 - val_loss: 0.4154 - val_mse: 0.4047 - val_mae: 0.4807 - val_root_mean_squared_error: 0.6362\n", "Epoch 549/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0430 - mse: 0.0324 - mae: 0.1291 - root_mean_squared_error: 0.1799\n", "Epoch 549: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0430 - mse: 0.0324 - mae: 0.1291 - root_mean_squared_error: 0.1799 - val_loss: 0.4250 - val_mse: 0.4144 - val_mae: 0.4957 - val_root_mean_squared_error: 0.6437\n", "Epoch 550/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0437 - mse: 0.0331 - mae: 0.1306 - root_mean_squared_error: 0.1820\n", "Epoch 550: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0437 - mse: 0.0330 - mae: 0.1304 - root_mean_squared_error: 0.1818 - val_loss: 0.3970 - val_mse: 0.3864 - val_mae: 0.4694 - val_root_mean_squared_error: 0.6216\n", "Epoch 551/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0451 - mse: 0.0345 - mae: 0.1345 - root_mean_squared_error: 0.1858\n", "Epoch 551: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0451 - mse: 0.0345 - mae: 0.1345 - root_mean_squared_error: 0.1857 - val_loss: 0.4028 - val_mse: 0.3922 - val_mae: 0.4712 - val_root_mean_squared_error: 0.6263\n", "Epoch 552/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0387 - mse: 0.0281 - mae: 0.1199 - root_mean_squared_error: 0.1677\n", "Epoch 552: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0387 - mse: 0.0281 - mae: 0.1199 - root_mean_squared_error: 0.1677 - val_loss: 0.4016 - val_mse: 0.3910 - val_mae: 0.4705 - val_root_mean_squared_error: 0.6253\n", "Epoch 553/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0397 - mse: 0.0291 - mae: 0.1230 - root_mean_squared_error: 0.1705\n", "Epoch 553: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0397 - mse: 0.0291 - mae: 0.1230 - root_mean_squared_error: 0.1705 - val_loss: 0.4225 - val_mse: 0.4119 - val_mae: 0.4882 - val_root_mean_squared_error: 0.6418\n", "Epoch 554/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0418 - mse: 0.0313 - mae: 0.1245 - root_mean_squared_error: 0.1768\n", "Epoch 554: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0418 - mse: 0.0313 - mae: 0.1245 - root_mean_squared_error: 0.1768 - val_loss: 0.4105 - val_mse: 0.3999 - val_mae: 0.4764 - val_root_mean_squared_error: 0.6324\n", "Epoch 555/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0484 - mse: 0.0378 - mae: 0.1360 - root_mean_squared_error: 0.1944\n", "Epoch 555: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0482 - mse: 0.0376 - mae: 0.1357 - root_mean_squared_error: 0.1940 - val_loss: 0.4161 - val_mse: 0.4055 - val_mae: 0.4902 - val_root_mean_squared_error: 0.6368\n", "Epoch 556/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0471 - mse: 0.0365 - mae: 0.1422 - root_mean_squared_error: 0.1911\n", "Epoch 556: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 51ms/step - loss: 0.0471 - mse: 0.0365 - mae: 0.1422 - root_mean_squared_error: 0.1911 - val_loss: 0.4114 - val_mse: 0.4008 - val_mae: 0.4843 - val_root_mean_squared_error: 0.6331\n", "Epoch 557/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0428 - mse: 0.0322 - mae: 0.1309 - root_mean_squared_error: 0.1794\n", "Epoch 557: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0428 - mse: 0.0322 - mae: 0.1311 - root_mean_squared_error: 0.1795 - val_loss: 0.4078 - val_mse: 0.3972 - val_mae: 0.4755 - val_root_mean_squared_error: 0.6303\n", "Epoch 558/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0406 - mse: 0.0300 - mae: 0.1228 - root_mean_squared_error: 0.1731\n", "Epoch 558: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0406 - mse: 0.0300 - mae: 0.1228 - root_mean_squared_error: 0.1731 - val_loss: 0.4171 - val_mse: 0.4065 - val_mae: 0.4829 - val_root_mean_squared_error: 0.6376\n", "Epoch 559/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0397 - mse: 0.0292 - mae: 0.1209 - root_mean_squared_error: 0.1708\n", "Epoch 559: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0397 - mse: 0.0292 - mae: 0.1209 - root_mean_squared_error: 0.1708 - val_loss: 0.4087 - val_mse: 0.3982 - val_mae: 0.4756 - val_root_mean_squared_error: 0.6310\n", "Epoch 560/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0479 - mse: 0.0373 - mae: 0.1398 - root_mean_squared_error: 0.1933\n", "Epoch 560: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0479 - mse: 0.0373 - mae: 0.1398 - root_mean_squared_error: 0.1933 - val_loss: 0.4081 - val_mse: 0.3976 - val_mae: 0.4773 - val_root_mean_squared_error: 0.6305\n", "Epoch 561/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0410 - mse: 0.0305 - mae: 0.1263 - root_mean_squared_error: 0.1745\n", "Epoch 561: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0410 - mse: 0.0305 - mae: 0.1263 - root_mean_squared_error: 0.1745 - val_loss: 0.4067 - val_mse: 0.3961 - val_mae: 0.4775 - val_root_mean_squared_error: 0.6294\n", "Epoch 562/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0435 - mse: 0.0330 - mae: 0.1292 - root_mean_squared_error: 0.1816\n", "Epoch 562: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0437 - mse: 0.0331 - mae: 0.1296 - root_mean_squared_error: 0.1820 - val_loss: 0.4205 - val_mse: 0.4100 - val_mae: 0.4908 - val_root_mean_squared_error: 0.6403\n", "Epoch 563/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0457 - mse: 0.0352 - mae: 0.1386 - root_mean_squared_error: 0.1876\n", "Epoch 563: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0457 - mse: 0.0352 - mae: 0.1386 - root_mean_squared_error: 0.1876 - val_loss: 0.4138 - val_mse: 0.4033 - val_mae: 0.4827 - val_root_mean_squared_error: 0.6351\n", "Epoch 564/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0464 - mse: 0.0359 - mae: 0.1339 - root_mean_squared_error: 0.1894\n", "Epoch 564: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0464 - mse: 0.0359 - mae: 0.1339 - root_mean_squared_error: 0.1894 - val_loss: 0.4301 - val_mse: 0.4196 - val_mae: 0.4898 - val_root_mean_squared_error: 0.6478\n", "Epoch 565/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0435 - mse: 0.0330 - mae: 0.1275 - root_mean_squared_error: 0.1817\n", "Epoch 565: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0434 - mse: 0.0329 - mae: 0.1275 - root_mean_squared_error: 0.1815 - val_loss: 0.3986 - val_mse: 0.3881 - val_mae: 0.4780 - val_root_mean_squared_error: 0.6230\n", "Epoch 566/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0496 - mse: 0.0392 - mae: 0.1418 - root_mean_squared_error: 0.1979\n", "Epoch 566: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0496 - mse: 0.0392 - mae: 0.1418 - root_mean_squared_error: 0.1979 - val_loss: 0.5119 - val_mse: 0.5014 - val_mae: 0.5491 - val_root_mean_squared_error: 0.7081\n", "Epoch 567/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0505 - mse: 0.0400 - mae: 0.1445 - root_mean_squared_error: 0.2001\n", "Epoch 567: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0504 - mse: 0.0399 - mae: 0.1442 - root_mean_squared_error: 0.1997 - val_loss: 0.4189 - val_mse: 0.4084 - val_mae: 0.4846 - val_root_mean_squared_error: 0.6391\n", "Epoch 568/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0451 - mse: 0.0346 - mae: 0.1366 - root_mean_squared_error: 0.1860\n", "Epoch 568: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0451 - mse: 0.0346 - mae: 0.1366 - root_mean_squared_error: 0.1860 - val_loss: 0.4124 - val_mse: 0.4019 - val_mae: 0.4793 - val_root_mean_squared_error: 0.6339\n", "Epoch 569/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0378 - mse: 0.0273 - mae: 0.1179 - root_mean_squared_error: 0.1652\n", "Epoch 569: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 53ms/step - loss: 0.0378 - mse: 0.0273 - mae: 0.1179 - root_mean_squared_error: 0.1652 - val_loss: 0.4032 - val_mse: 0.3928 - val_mae: 0.4815 - val_root_mean_squared_error: 0.6267\n", "Epoch 570/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0368 - mse: 0.0264 - mae: 0.1158 - root_mean_squared_error: 0.1624\n", "Epoch 570: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0367 - mse: 0.0263 - mae: 0.1157 - root_mean_squared_error: 0.1621 - val_loss: 0.4118 - val_mse: 0.4014 - val_mae: 0.4843 - val_root_mean_squared_error: 0.6335\n", "Epoch 571/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0606 - mse: 0.0502 - mae: 0.1644 - root_mean_squared_error: 0.2239\n", "Epoch 571: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0621 - mse: 0.0516 - mae: 0.1669 - root_mean_squared_error: 0.2272 - val_loss: 0.4475 - val_mse: 0.4370 - val_mae: 0.5054 - val_root_mean_squared_error: 0.6611\n", "Epoch 572/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0506 - mse: 0.0401 - mae: 0.1456 - root_mean_squared_error: 0.2001\n", "Epoch 572: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 51ms/step - loss: 0.0504 - mse: 0.0399 - mae: 0.1452 - root_mean_squared_error: 0.1998 - val_loss: 0.3928 - val_mse: 0.3822 - val_mae: 0.4708 - val_root_mean_squared_error: 0.6182\n", "Epoch 573/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0460 - mse: 0.0354 - mae: 0.1376 - root_mean_squared_error: 0.1882\n", "Epoch 573: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0460 - mse: 0.0354 - mae: 0.1376 - root_mean_squared_error: 0.1882 - val_loss: 0.4202 - val_mse: 0.4096 - val_mae: 0.4785 - val_root_mean_squared_error: 0.6400\n", "Epoch 574/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0353 - mse: 0.0248 - mae: 0.1144 - root_mean_squared_error: 0.1576\n", "Epoch 574: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0352 - mse: 0.0247 - mae: 0.1141 - root_mean_squared_error: 0.1572 - val_loss: 0.4221 - val_mse: 0.4116 - val_mae: 0.4852 - val_root_mean_squared_error: 0.6416\n", "Epoch 575/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0394 - mse: 0.0289 - mae: 0.1268 - root_mean_squared_error: 0.1700\n", "Epoch 575: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0410 - mse: 0.0306 - mae: 0.1280 - root_mean_squared_error: 0.1749 - val_loss: 0.4384 - val_mse: 0.4279 - val_mae: 0.5019 - val_root_mean_squared_error: 0.6542\n", "Epoch 576/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0442 - mse: 0.0338 - mae: 0.1326 - root_mean_squared_error: 0.1838\n", "Epoch 576: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0441 - mse: 0.0337 - mae: 0.1325 - root_mean_squared_error: 0.1835 - val_loss: 0.4029 - val_mse: 0.3924 - val_mae: 0.4781 - val_root_mean_squared_error: 0.6264\n", "Epoch 577/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0420 - mse: 0.0316 - mae: 0.1285 - root_mean_squared_error: 0.1777\n", "Epoch 577: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0420 - mse: 0.0316 - mae: 0.1285 - root_mean_squared_error: 0.1777 - val_loss: 0.4098 - val_mse: 0.3994 - val_mae: 0.4757 - val_root_mean_squared_error: 0.6320\n", "Epoch 578/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0362 - mse: 0.0258 - mae: 0.1120 - root_mean_squared_error: 0.1606\n", "Epoch 578: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0362 - mse: 0.0258 - mae: 0.1120 - root_mean_squared_error: 0.1606 - val_loss: 0.4186 - val_mse: 0.4082 - val_mae: 0.4910 - val_root_mean_squared_error: 0.6389\n", "Epoch 579/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0359 - mse: 0.0255 - mae: 0.1163 - root_mean_squared_error: 0.1597\n", "Epoch 579: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0361 - mse: 0.0257 - mae: 0.1164 - root_mean_squared_error: 0.1603 - val_loss: 0.4091 - val_mse: 0.3987 - val_mae: 0.4799 - val_root_mean_squared_error: 0.6314\n", "Epoch 580/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0402 - mse: 0.0299 - mae: 0.1203 - root_mean_squared_error: 0.1729\n", "Epoch 580: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0402 - mse: 0.0299 - mae: 0.1203 - root_mean_squared_error: 0.1729 - val_loss: 0.4084 - val_mse: 0.3980 - val_mae: 0.4809 - val_root_mean_squared_error: 0.6309\n", "Epoch 581/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0411 - mse: 0.0308 - mae: 0.1253 - root_mean_squared_error: 0.1756\n", "Epoch 581: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0411 - mse: 0.0308 - mae: 0.1253 - root_mean_squared_error: 0.1756 - val_loss: 0.4298 - val_mse: 0.4195 - val_mae: 0.4980 - val_root_mean_squared_error: 0.6477\n", "Epoch 582/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0516 - mse: 0.0413 - mae: 0.1481 - root_mean_squared_error: 0.2032\n", "Epoch 582: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0514 - mse: 0.0410 - mae: 0.1475 - root_mean_squared_error: 0.2025 - val_loss: 0.4047 - val_mse: 0.3944 - val_mae: 0.4762 - val_root_mean_squared_error: 0.6280\n", "Epoch 583/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0388 - mse: 0.0285 - mae: 0.1206 - root_mean_squared_error: 0.1687\n", "Epoch 583: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0388 - mse: 0.0285 - mae: 0.1206 - root_mean_squared_error: 0.1687 - val_loss: 0.4124 - val_mse: 0.4021 - val_mae: 0.4792 - val_root_mean_squared_error: 0.6341\n", "Epoch 584/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0391 - mse: 0.0288 - mae: 0.1228 - root_mean_squared_error: 0.1698\n", "Epoch 584: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 53ms/step - loss: 0.0390 - mse: 0.0287 - mae: 0.1226 - root_mean_squared_error: 0.1694 - val_loss: 0.4078 - val_mse: 0.3975 - val_mae: 0.4822 - val_root_mean_squared_error: 0.6305\n", "Epoch 585/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0361 - mse: 0.0258 - mae: 0.1178 - root_mean_squared_error: 0.1607\n", "Epoch 585: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0361 - mse: 0.0258 - mae: 0.1178 - root_mean_squared_error: 0.1607 - val_loss: 0.4218 - val_mse: 0.4116 - val_mae: 0.4861 - val_root_mean_squared_error: 0.6416\n", "Epoch 586/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0454 - mse: 0.0351 - mae: 0.1353 - root_mean_squared_error: 0.1874\n", "Epoch 586: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0454 - mse: 0.0351 - mae: 0.1353 - root_mean_squared_error: 0.1874 - val_loss: 0.4112 - val_mse: 0.4009 - val_mae: 0.4809 - val_root_mean_squared_error: 0.6332\n", "Epoch 587/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0447 - mse: 0.0344 - mae: 0.1328 - root_mean_squared_error: 0.1854\n", "Epoch 587: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0447 - mse: 0.0344 - mae: 0.1328 - root_mean_squared_error: 0.1854 - val_loss: 0.4089 - val_mse: 0.3987 - val_mae: 0.4762 - val_root_mean_squared_error: 0.6314\n", "Epoch 588/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0420 - mse: 0.0317 - mae: 0.1268 - root_mean_squared_error: 0.1781\n", "Epoch 588: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0419 - mse: 0.0316 - mae: 0.1265 - root_mean_squared_error: 0.1779 - val_loss: 0.4106 - val_mse: 0.4003 - val_mae: 0.4814 - val_root_mean_squared_error: 0.6327\n", "Epoch 589/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0412 - mse: 0.0309 - mae: 0.1285 - root_mean_squared_error: 0.1759\n", "Epoch 589: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0412 - mse: 0.0309 - mae: 0.1285 - root_mean_squared_error: 0.1759 - val_loss: 0.4030 - val_mse: 0.3927 - val_mae: 0.4754 - val_root_mean_squared_error: 0.6267\n", "Epoch 590/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0345 - mse: 0.0243 - mae: 0.1131 - root_mean_squared_error: 0.1559\n", "Epoch 590: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0348 - mse: 0.0246 - mae: 0.1134 - root_mean_squared_error: 0.1567 - val_loss: 0.4006 - val_mse: 0.3904 - val_mae: 0.4801 - val_root_mean_squared_error: 0.6248\n", "Epoch 591/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0384 - mse: 0.0283 - mae: 0.1177 - root_mean_squared_error: 0.1682\n", "Epoch 591: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0384 - mse: 0.0282 - mae: 0.1178 - root_mean_squared_error: 0.1680 - val_loss: 0.4166 - val_mse: 0.4065 - val_mae: 0.4875 - val_root_mean_squared_error: 0.6376\n", "Epoch 592/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0403 - mse: 0.0301 - mae: 0.1261 - root_mean_squared_error: 0.1735\n", "Epoch 592: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0403 - mse: 0.0301 - mae: 0.1261 - root_mean_squared_error: 0.1735 - val_loss: 0.3859 - val_mse: 0.3758 - val_mae: 0.4647 - val_root_mean_squared_error: 0.6130\n", "Epoch 593/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0411 - mse: 0.0310 - mae: 0.1277 - root_mean_squared_error: 0.1760\n", "Epoch 593: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0410 - mse: 0.0309 - mae: 0.1275 - root_mean_squared_error: 0.1757 - val_loss: 0.4032 - val_mse: 0.3931 - val_mae: 0.4757 - val_root_mean_squared_error: 0.6270\n", "Epoch 594/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0408 - mse: 0.0307 - mae: 0.1272 - root_mean_squared_error: 0.1751\n", "Epoch 594: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0408 - mse: 0.0306 - mae: 0.1273 - root_mean_squared_error: 0.1750 - val_loss: 0.4136 - val_mse: 0.4035 - val_mae: 0.4815 - val_root_mean_squared_error: 0.6352\n", "Epoch 595/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0399 - mse: 0.0297 - mae: 0.1244 - root_mean_squared_error: 0.1725\n", "Epoch 595: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0399 - mse: 0.0297 - mae: 0.1244 - root_mean_squared_error: 0.1725 - val_loss: 0.4434 - val_mse: 0.4333 - val_mae: 0.5046 - val_root_mean_squared_error: 0.6583\n", "Epoch 596/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0433 - mse: 0.0332 - mae: 0.1275 - root_mean_squared_error: 0.1821\n", "Epoch 596: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0431 - mse: 0.0330 - mae: 0.1272 - root_mean_squared_error: 0.1816 - val_loss: 0.4025 - val_mse: 0.3924 - val_mae: 0.4771 - val_root_mean_squared_error: 0.6265\n", "Epoch 597/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0377 - mse: 0.0276 - mae: 0.1222 - root_mean_squared_error: 0.1661\n", "Epoch 597: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 5s 66ms/step - loss: 0.0376 - mse: 0.0275 - mae: 0.1220 - root_mean_squared_error: 0.1658 - val_loss: 0.3987 - val_mse: 0.3886 - val_mae: 0.4713 - val_root_mean_squared_error: 0.6234\n", "Epoch 598/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0397 - mse: 0.0296 - mae: 0.1213 - root_mean_squared_error: 0.1720\n", "Epoch 598: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0401 - mse: 0.0300 - mae: 0.1219 - root_mean_squared_error: 0.1732 - val_loss: 0.4139 - val_mse: 0.4038 - val_mae: 0.4833 - val_root_mean_squared_error: 0.6354\n", "Epoch 599/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0393 - mse: 0.0293 - mae: 0.1231 - root_mean_squared_error: 0.1711\n", "Epoch 599: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0393 - mse: 0.0293 - mae: 0.1232 - root_mean_squared_error: 0.1711 - val_loss: 0.4009 - val_mse: 0.3908 - val_mae: 0.4690 - val_root_mean_squared_error: 0.6252\n", "Epoch 600/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0362 - mse: 0.0261 - mae: 0.1148 - root_mean_squared_error: 0.1617\n", "Epoch 600: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0362 - mse: 0.0261 - mae: 0.1148 - root_mean_squared_error: 0.1617 - val_loss: 0.4055 - val_mse: 0.3955 - val_mae: 0.4757 - val_root_mean_squared_error: 0.6289\n", "Epoch 601/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0433 - mse: 0.0333 - mae: 0.1347 - root_mean_squared_error: 0.1825\n", "Epoch 601: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0433 - mse: 0.0333 - mae: 0.1347 - root_mean_squared_error: 0.1825 - val_loss: 0.4019 - val_mse: 0.3919 - val_mae: 0.4772 - val_root_mean_squared_error: 0.6260\n", "Epoch 602/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0419 - mse: 0.0319 - mae: 0.1300 - root_mean_squared_error: 0.1786\n", "Epoch 602: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0419 - mse: 0.0319 - mae: 0.1300 - root_mean_squared_error: 0.1786 - val_loss: 0.4087 - val_mse: 0.3986 - val_mae: 0.4785 - val_root_mean_squared_error: 0.6314\n", "Epoch 603/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0407 - mse: 0.0307 - mae: 0.1313 - root_mean_squared_error: 0.1752\n", "Epoch 603: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0407 - mse: 0.0307 - mae: 0.1313 - root_mean_squared_error: 0.1752 - val_loss: 0.4344 - val_mse: 0.4243 - val_mae: 0.5020 - val_root_mean_squared_error: 0.6514\n", "Epoch 604/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0519 - mse: 0.0418 - mae: 0.1466 - root_mean_squared_error: 0.2045\n", "Epoch 604: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0519 - mse: 0.0418 - mae: 0.1466 - root_mean_squared_error: 0.2045 - val_loss: 0.4312 - val_mse: 0.4211 - val_mae: 0.4826 - val_root_mean_squared_error: 0.6489\n", "Epoch 605/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0408 - mse: 0.0308 - mae: 0.1255 - root_mean_squared_error: 0.1755\n", "Epoch 605: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0408 - mse: 0.0307 - mae: 0.1254 - root_mean_squared_error: 0.1753 - val_loss: 0.4121 - val_mse: 0.4021 - val_mae: 0.4822 - val_root_mean_squared_error: 0.6341\n", "Epoch 606/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0398 - mse: 0.0298 - mae: 0.1257 - root_mean_squared_error: 0.1726\n", "Epoch 606: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0397 - mse: 0.0297 - mae: 0.1256 - root_mean_squared_error: 0.1724 - val_loss: 0.4248 - val_mse: 0.4147 - val_mae: 0.4903 - val_root_mean_squared_error: 0.6440\n", "Epoch 607/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0400 - mse: 0.0300 - mae: 0.1248 - root_mean_squared_error: 0.1733\n", "Epoch 607: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0400 - mse: 0.0300 - mae: 0.1248 - root_mean_squared_error: 0.1733 - val_loss: 0.4288 - val_mse: 0.4188 - val_mae: 0.4874 - val_root_mean_squared_error: 0.6471\n", "Epoch 608/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0425 - mse: 0.0325 - mae: 0.1294 - root_mean_squared_error: 0.1802\n", "Epoch 608: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0425 - mse: 0.0325 - mae: 0.1294 - root_mean_squared_error: 0.1802 - val_loss: 0.4212 - val_mse: 0.4112 - val_mae: 0.4828 - val_root_mean_squared_error: 0.6413\n", "Epoch 609/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0396 - mse: 0.0296 - mae: 0.1255 - root_mean_squared_error: 0.1720\n", "Epoch 609: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0395 - mse: 0.0295 - mae: 0.1255 - root_mean_squared_error: 0.1719 - val_loss: 0.4255 - val_mse: 0.4155 - val_mae: 0.4813 - val_root_mean_squared_error: 0.6446\n", "Epoch 610/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0368 - mse: 0.0269 - mae: 0.1173 - root_mean_squared_error: 0.1639\n", "Epoch 610: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0367 - mse: 0.0268 - mae: 0.1171 - root_mean_squared_error: 0.1636 - val_loss: 0.4208 - val_mse: 0.4109 - val_mae: 0.4857 - val_root_mean_squared_error: 0.6410\n", "Epoch 611/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0385 - mse: 0.0286 - mae: 0.1219 - root_mean_squared_error: 0.1691\n", "Epoch 611: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0385 - mse: 0.0286 - mae: 0.1219 - root_mean_squared_error: 0.1691 - val_loss: 0.4253 - val_mse: 0.4154 - val_mae: 0.4887 - val_root_mean_squared_error: 0.6445\n", "Epoch 612/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0411 - mse: 0.0312 - mae: 0.1280 - root_mean_squared_error: 0.1766\n", "Epoch 612: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0410 - mse: 0.0311 - mae: 0.1278 - root_mean_squared_error: 0.1763 - val_loss: 0.3977 - val_mse: 0.3878 - val_mae: 0.4726 - val_root_mean_squared_error: 0.6227\n", "Epoch 613/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0408 - mse: 0.0309 - mae: 0.1267 - root_mean_squared_error: 0.1757\n", "Epoch 613: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 34ms/step - loss: 0.0407 - mse: 0.0308 - mae: 0.1269 - root_mean_squared_error: 0.1756 - val_loss: 0.4650 - val_mse: 0.4551 - val_mae: 0.5336 - val_root_mean_squared_error: 0.6746\n", "Epoch 614/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0378 - mse: 0.0279 - mae: 0.1212 - root_mean_squared_error: 0.1670\n", "Epoch 614: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 0.0378 - mse: 0.0279 - mae: 0.1212 - root_mean_squared_error: 0.1670 - val_loss: 0.4100 - val_mse: 0.4002 - val_mae: 0.4818 - val_root_mean_squared_error: 0.6326\n", "Epoch 615/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0396 - mse: 0.0298 - mae: 0.1245 - root_mean_squared_error: 0.1725\n", "Epoch 615: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0396 - mse: 0.0298 - mae: 0.1245 - root_mean_squared_error: 0.1725 - val_loss: 0.4310 - val_mse: 0.4211 - val_mae: 0.4994 - val_root_mean_squared_error: 0.6489\n", "Epoch 616/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0415 - mse: 0.0316 - mae: 0.1311 - root_mean_squared_error: 0.1778\n", "Epoch 616: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0414 - mse: 0.0315 - mae: 0.1310 - root_mean_squared_error: 0.1775 - val_loss: 0.4521 - val_mse: 0.4422 - val_mae: 0.5055 - val_root_mean_squared_error: 0.6650\n", "Epoch 617/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0419 - mse: 0.0321 - mae: 0.1276 - root_mean_squared_error: 0.1791\n", "Epoch 617: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0417 - mse: 0.0319 - mae: 0.1271 - root_mean_squared_error: 0.1785 - val_loss: 0.4057 - val_mse: 0.3959 - val_mae: 0.4808 - val_root_mean_squared_error: 0.6292\n", "Epoch 618/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0371 - mse: 0.0272 - mae: 0.1184 - root_mean_squared_error: 0.1650\n", "Epoch 618: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0370 - mse: 0.0272 - mae: 0.1182 - root_mean_squared_error: 0.1648 - val_loss: 0.4273 - val_mse: 0.4174 - val_mae: 0.4942 - val_root_mean_squared_error: 0.6461\n", "Epoch 619/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0379 - mse: 0.0281 - mae: 0.1160 - root_mean_squared_error: 0.1676\n", "Epoch 619: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0379 - mse: 0.0280 - mae: 0.1160 - root_mean_squared_error: 0.1675 - val_loss: 0.4001 - val_mse: 0.3903 - val_mae: 0.4811 - val_root_mean_squared_error: 0.6247\n", "Epoch 620/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0361 - mse: 0.0263 - mae: 0.1172 - root_mean_squared_error: 0.1623\n", "Epoch 620: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0361 - mse: 0.0263 - mae: 0.1172 - root_mean_squared_error: 0.1623 - val_loss: 0.4115 - val_mse: 0.4017 - val_mae: 0.4901 - val_root_mean_squared_error: 0.6338\n", "Epoch 621/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0401 - mse: 0.0303 - mae: 0.1269 - root_mean_squared_error: 0.1741\n", "Epoch 621: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 0.0401 - mse: 0.0303 - mae: 0.1269 - root_mean_squared_error: 0.1741 - val_loss: 0.4005 - val_mse: 0.3908 - val_mae: 0.4768 - val_root_mean_squared_error: 0.6251\n", "Epoch 622/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0413 - mse: 0.0315 - mae: 0.1265 - root_mean_squared_error: 0.1776\n", "Epoch 622: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0411 - mse: 0.0314 - mae: 0.1264 - root_mean_squared_error: 0.1771 - val_loss: 0.3980 - val_mse: 0.3882 - val_mae: 0.4822 - val_root_mean_squared_error: 0.6231\n", "Epoch 623/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0417 - mse: 0.0319 - mae: 0.1314 - root_mean_squared_error: 0.1786\n", "Epoch 623: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0417 - mse: 0.0319 - mae: 0.1314 - root_mean_squared_error: 0.1786 - val_loss: 0.4198 - val_mse: 0.4101 - val_mae: 0.4856 - val_root_mean_squared_error: 0.6404\n", "Epoch 624/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0373 - mse: 0.0275 - mae: 0.1193 - root_mean_squared_error: 0.1658\n", "Epoch 624: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0371 - mse: 0.0274 - mae: 0.1190 - root_mean_squared_error: 0.1654 - val_loss: 0.4262 - val_mse: 0.4164 - val_mae: 0.4984 - val_root_mean_squared_error: 0.6453\n", "Epoch 625/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0383 - mse: 0.0286 - mae: 0.1228 - root_mean_squared_error: 0.1691\n", "Epoch 625: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0383 - mse: 0.0286 - mae: 0.1228 - root_mean_squared_error: 0.1691 - val_loss: 0.4284 - val_mse: 0.4186 - val_mae: 0.4860 - val_root_mean_squared_error: 0.6470\n", "Epoch 626/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0388 - mse: 0.0291 - mae: 0.1224 - root_mean_squared_error: 0.1705\n", "Epoch 626: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0388 - mse: 0.0291 - mae: 0.1224 - root_mean_squared_error: 0.1705 - val_loss: 0.4067 - val_mse: 0.3970 - val_mae: 0.4811 - val_root_mean_squared_error: 0.6301\n", "Epoch 627/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0366 - mse: 0.0269 - mae: 0.1190 - root_mean_squared_error: 0.1641\n", "Epoch 627: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 55ms/step - loss: 0.0366 - mse: 0.0268 - mae: 0.1189 - root_mean_squared_error: 0.1638 - val_loss: 0.4284 - val_mse: 0.4187 - val_mae: 0.4832 - val_root_mean_squared_error: 0.6471\n", "Epoch 628/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0502 - mse: 0.0405 - mae: 0.1463 - root_mean_squared_error: 0.2013\n", "Epoch 628: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0502 - mse: 0.0405 - mae: 0.1464 - root_mean_squared_error: 0.2013 - val_loss: 0.4470 - val_mse: 0.4373 - val_mae: 0.5070 - val_root_mean_squared_error: 0.6613\n", "Epoch 629/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0508 - mse: 0.0411 - mae: 0.1421 - root_mean_squared_error: 0.2028\n", "Epoch 629: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0508 - mse: 0.0411 - mae: 0.1423 - root_mean_squared_error: 0.2027 - val_loss: 0.4302 - val_mse: 0.4204 - val_mae: 0.4897 - val_root_mean_squared_error: 0.6484\n", "Epoch 630/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0496 - mse: 0.0398 - mae: 0.1439 - root_mean_squared_error: 0.1996\n", "Epoch 630: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0496 - mse: 0.0398 - mae: 0.1439 - root_mean_squared_error: 0.1996 - val_loss: 0.4231 - val_mse: 0.4134 - val_mae: 0.4943 - val_root_mean_squared_error: 0.6429\n", "Epoch 631/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0427 - mse: 0.0329 - mae: 0.1309 - root_mean_squared_error: 0.1815\n", "Epoch 631: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0425 - mse: 0.0328 - mae: 0.1307 - root_mean_squared_error: 0.1811 - val_loss: 0.4021 - val_mse: 0.3924 - val_mae: 0.4737 - val_root_mean_squared_error: 0.6264\n", "Epoch 632/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0365 - mse: 0.0267 - mae: 0.1190 - root_mean_squared_error: 0.1635\n", "Epoch 632: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0364 - mse: 0.0266 - mae: 0.1189 - root_mean_squared_error: 0.1632 - val_loss: 0.4417 - val_mse: 0.4320 - val_mae: 0.5017 - val_root_mean_squared_error: 0.6572\n", "Epoch 633/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0458 - mse: 0.0361 - mae: 0.1364 - root_mean_squared_error: 0.1900\n", "Epoch 633: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0456 - mse: 0.0359 - mae: 0.1361 - root_mean_squared_error: 0.1895 - val_loss: 0.4118 - val_mse: 0.4021 - val_mae: 0.4815 - val_root_mean_squared_error: 0.6341\n", "Epoch 634/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0385 - mse: 0.0287 - mae: 0.1226 - root_mean_squared_error: 0.1695\n", "Epoch 634: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0385 - mse: 0.0287 - mae: 0.1226 - root_mean_squared_error: 0.1695 - val_loss: 0.4281 - val_mse: 0.4184 - val_mae: 0.4869 - val_root_mean_squared_error: 0.6468\n", "Epoch 635/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0369 - mse: 0.0271 - mae: 0.1157 - root_mean_squared_error: 0.1648\n", "Epoch 635: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0369 - mse: 0.0271 - mae: 0.1157 - root_mean_squared_error: 0.1648 - val_loss: 0.4217 - val_mse: 0.4120 - val_mae: 0.4858 - val_root_mean_squared_error: 0.6418\n", "Epoch 636/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0374 - mse: 0.0277 - mae: 0.1188 - root_mean_squared_error: 0.1664\n", "Epoch 636: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0374 - mse: 0.0277 - mae: 0.1188 - root_mean_squared_error: 0.1664 - val_loss: 0.4171 - val_mse: 0.4074 - val_mae: 0.4848 - val_root_mean_squared_error: 0.6383\n", "Epoch 637/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0550 - mse: 0.0452 - mae: 0.1521 - root_mean_squared_error: 0.2127\n", "Epoch 637: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 0.0550 - mse: 0.0452 - mae: 0.1521 - root_mean_squared_error: 0.2127 - val_loss: 0.4051 - val_mse: 0.3953 - val_mae: 0.4772 - val_root_mean_squared_error: 0.6288\n", "Epoch 638/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0474 - mse: 0.0376 - mae: 0.1390 - root_mean_squared_error: 0.1940\n", "Epoch 638: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0472 - mse: 0.0374 - mae: 0.1385 - root_mean_squared_error: 0.1935 - val_loss: 0.4136 - val_mse: 0.4039 - val_mae: 0.4865 - val_root_mean_squared_error: 0.6355\n", "Epoch 639/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0382 - mse: 0.0284 - mae: 0.1203 - root_mean_squared_error: 0.1687\n", "Epoch 639: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0391 - mse: 0.0293 - mae: 0.1222 - root_mean_squared_error: 0.1712 - val_loss: 0.4237 - val_mse: 0.4140 - val_mae: 0.4810 - val_root_mean_squared_error: 0.6434\n", "Epoch 640/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0372 - mse: 0.0274 - mae: 0.1199 - root_mean_squared_error: 0.1656\n", "Epoch 640: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0373 - mse: 0.0275 - mae: 0.1202 - root_mean_squared_error: 0.1659 - val_loss: 0.4019 - val_mse: 0.3921 - val_mae: 0.4745 - val_root_mean_squared_error: 0.6262\n", "Epoch 641/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0399 - mse: 0.0301 - mae: 0.1253 - root_mean_squared_error: 0.1735\n", "Epoch 641: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0399 - mse: 0.0301 - mae: 0.1254 - root_mean_squared_error: 0.1734 - val_loss: 0.4079 - val_mse: 0.3981 - val_mae: 0.4770 - val_root_mean_squared_error: 0.6310\n", "Epoch 642/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0436 - mse: 0.0338 - mae: 0.1362 - root_mean_squared_error: 0.1838\n", "Epoch 642: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0436 - mse: 0.0338 - mae: 0.1362 - root_mean_squared_error: 0.1838 - val_loss: 0.4170 - val_mse: 0.4072 - val_mae: 0.4903 - val_root_mean_squared_error: 0.6381\n", "Epoch 643/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0410 - mse: 0.0312 - mae: 0.1272 - root_mean_squared_error: 0.1766\n", "Epoch 643: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0409 - mse: 0.0311 - mae: 0.1271 - root_mean_squared_error: 0.1764 - val_loss: 0.4211 - val_mse: 0.4114 - val_mae: 0.4865 - val_root_mean_squared_error: 0.6414\n", "Epoch 644/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0400 - mse: 0.0302 - mae: 0.1270 - root_mean_squared_error: 0.1739\n", "Epoch 644: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0398 - mse: 0.0301 - mae: 0.1266 - root_mean_squared_error: 0.1734 - val_loss: 0.4354 - val_mse: 0.4257 - val_mae: 0.4890 - val_root_mean_squared_error: 0.6524\n", "Epoch 645/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0372 - mse: 0.0275 - mae: 0.1179 - root_mean_squared_error: 0.1658\n", "Epoch 645: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0372 - mse: 0.0274 - mae: 0.1179 - root_mean_squared_error: 0.1657 - val_loss: 0.4163 - val_mse: 0.4065 - val_mae: 0.4827 - val_root_mean_squared_error: 0.6376\n", "Epoch 646/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0478 - mse: 0.0381 - mae: 0.1408 - root_mean_squared_error: 0.1952\n", "Epoch 646: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 54ms/step - loss: 0.0478 - mse: 0.0381 - mae: 0.1408 - root_mean_squared_error: 0.1952 - val_loss: 0.4257 - val_mse: 0.4159 - val_mae: 0.4935 - val_root_mean_squared_error: 0.6449\n", "Epoch 647/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0599 - mse: 0.0501 - mae: 0.1613 - root_mean_squared_error: 0.2239\n", "Epoch 647: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0599 - mse: 0.0501 - mae: 0.1613 - root_mean_squared_error: 0.2239 - val_loss: 0.4066 - val_mse: 0.3968 - val_mae: 0.4820 - val_root_mean_squared_error: 0.6299\n", "Epoch 648/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0445 - mse: 0.0347 - mae: 0.1327 - root_mean_squared_error: 0.1863\n", "Epoch 648: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 2s 34ms/step - loss: 0.0448 - mse: 0.0349 - mae: 0.1334 - root_mean_squared_error: 0.1869 - val_loss: 0.4066 - val_mse: 0.3968 - val_mae: 0.4813 - val_root_mean_squared_error: 0.6299\n", "Epoch 649/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0384 - mse: 0.0286 - mae: 0.1229 - root_mean_squared_error: 0.1690\n", "Epoch 649: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0380 - mse: 0.0282 - mae: 0.1222 - root_mean_squared_error: 0.1681 - val_loss: 0.4236 - val_mse: 0.4138 - val_mae: 0.4894 - val_root_mean_squared_error: 0.6433\n", "Epoch 650/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0385 - mse: 0.0287 - mae: 0.1195 - root_mean_squared_error: 0.1696\n", "Epoch 650: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0385 - mse: 0.0287 - mae: 0.1195 - root_mean_squared_error: 0.1694 - val_loss: 0.4165 - val_mse: 0.4067 - val_mae: 0.4859 - val_root_mean_squared_error: 0.6377\n", "Epoch 651/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0408 - mse: 0.0310 - mae: 0.1238 - root_mean_squared_error: 0.1761\n", "Epoch 651: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0408 - mse: 0.0310 - mae: 0.1238 - root_mean_squared_error: 0.1761 - val_loss: 0.4209 - val_mse: 0.4111 - val_mae: 0.4838 - val_root_mean_squared_error: 0.6412\n", "Epoch 652/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0363 - mse: 0.0265 - mae: 0.1162 - root_mean_squared_error: 0.1629\n", "Epoch 652: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 53ms/step - loss: 0.0363 - mse: 0.0265 - mae: 0.1162 - root_mean_squared_error: 0.1629 - val_loss: 0.4219 - val_mse: 0.4122 - val_mae: 0.4889 - val_root_mean_squared_error: 0.6420\n", "Epoch 653/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0353 - mse: 0.0256 - mae: 0.1159 - root_mean_squared_error: 0.1600\n", "Epoch 653: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0352 - mse: 0.0255 - mae: 0.1155 - root_mean_squared_error: 0.1598 - val_loss: 0.4033 - val_mse: 0.3936 - val_mae: 0.4792 - val_root_mean_squared_error: 0.6274\n", "Epoch 654/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0383 - mse: 0.0287 - mae: 0.1227 - root_mean_squared_error: 0.1693\n", "Epoch 654: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0383 - mse: 0.0287 - mae: 0.1227 - root_mean_squared_error: 0.1693 - val_loss: 0.4132 - val_mse: 0.4035 - val_mae: 0.4841 - val_root_mean_squared_error: 0.6352\n", "Epoch 655/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0426 - mse: 0.0330 - mae: 0.1302 - root_mean_squared_error: 0.1815\n", "Epoch 655: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0425 - mse: 0.0328 - mae: 0.1299 - root_mean_squared_error: 0.1812 - val_loss: 0.4264 - val_mse: 0.4167 - val_mae: 0.4936 - val_root_mean_squared_error: 0.6455\n", "Epoch 656/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0396 - mse: 0.0299 - mae: 0.1258 - root_mean_squared_error: 0.1730\n", "Epoch 656: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0394 - mse: 0.0297 - mae: 0.1255 - root_mean_squared_error: 0.1724 - val_loss: 0.4265 - val_mse: 0.4168 - val_mae: 0.4883 - val_root_mean_squared_error: 0.6456\n", "Epoch 657/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0399 - mse: 0.0302 - mae: 0.1253 - root_mean_squared_error: 0.1738\n", "Epoch 657: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0399 - mse: 0.0302 - mae: 0.1253 - root_mean_squared_error: 0.1738 - val_loss: 0.4140 - val_mse: 0.4044 - val_mae: 0.4843 - val_root_mean_squared_error: 0.6359\n", "Epoch 658/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0387 - mse: 0.0290 - mae: 0.1242 - root_mean_squared_error: 0.1704\n", "Epoch 658: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0384 - mse: 0.0288 - mae: 0.1237 - root_mean_squared_error: 0.1697 - val_loss: 0.4255 - val_mse: 0.4159 - val_mae: 0.4903 - val_root_mean_squared_error: 0.6449\n", "Epoch 659/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0332 - mse: 0.0236 - mae: 0.1119 - root_mean_squared_error: 0.1537\n", "Epoch 659: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0332 - mse: 0.0236 - mae: 0.1119 - root_mean_squared_error: 0.1537 - val_loss: 0.4246 - val_mse: 0.4150 - val_mae: 0.4899 - val_root_mean_squared_error: 0.6442\n", "Epoch 660/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0372 - mse: 0.0276 - mae: 0.1196 - root_mean_squared_error: 0.1662\n", "Epoch 660: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0371 - mse: 0.0275 - mae: 0.1195 - root_mean_squared_error: 0.1660 - val_loss: 0.4229 - val_mse: 0.4133 - val_mae: 0.4839 - val_root_mean_squared_error: 0.6429\n", "Epoch 661/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0454 - mse: 0.0358 - mae: 0.1352 - root_mean_squared_error: 0.1892\n", "Epoch 661: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0452 - mse: 0.0356 - mae: 0.1349 - root_mean_squared_error: 0.1888 - val_loss: 0.3929 - val_mse: 0.3833 - val_mae: 0.4701 - val_root_mean_squared_error: 0.6191\n", "Epoch 662/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0364 - mse: 0.0268 - mae: 0.1162 - root_mean_squared_error: 0.1637\n", "Epoch 662: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0364 - mse: 0.0268 - mae: 0.1162 - root_mean_squared_error: 0.1637 - val_loss: 0.4158 - val_mse: 0.4062 - val_mae: 0.4813 - val_root_mean_squared_error: 0.6373\n", "Epoch 663/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0399 - mse: 0.0304 - mae: 0.1247 - root_mean_squared_error: 0.1742\n", "Epoch 663: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0402 - mse: 0.0307 - mae: 0.1250 - root_mean_squared_error: 0.1751 - val_loss: 0.3990 - val_mse: 0.3894 - val_mae: 0.4729 - val_root_mean_squared_error: 0.6240\n", "Epoch 664/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0435 - mse: 0.0339 - mae: 0.1338 - root_mean_squared_error: 0.1841\n", "Epoch 664: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0435 - mse: 0.0339 - mae: 0.1338 - root_mean_squared_error: 0.1841 - val_loss: 0.4439 - val_mse: 0.4343 - val_mae: 0.5069 - val_root_mean_squared_error: 0.6590\n", "Epoch 665/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0430 - mse: 0.0334 - mae: 0.1323 - root_mean_squared_error: 0.1827\n", "Epoch 665: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0429 - mse: 0.0333 - mae: 0.1324 - root_mean_squared_error: 0.1825 - val_loss: 0.4070 - val_mse: 0.3974 - val_mae: 0.4769 - val_root_mean_squared_error: 0.6304\n", "Epoch 666/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0378 - mse: 0.0282 - mae: 0.1188 - root_mean_squared_error: 0.1679\n", "Epoch 666: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0377 - mse: 0.0281 - mae: 0.1186 - root_mean_squared_error: 0.1676 - val_loss: 0.4210 - val_mse: 0.4114 - val_mae: 0.4852 - val_root_mean_squared_error: 0.6414\n", "Epoch 667/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0377 - mse: 0.0281 - mae: 0.1195 - root_mean_squared_error: 0.1677\n", "Epoch 667: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0377 - mse: 0.0281 - mae: 0.1195 - root_mean_squared_error: 0.1677 - val_loss: 0.4230 - val_mse: 0.4135 - val_mae: 0.4851 - val_root_mean_squared_error: 0.6430\n", "Epoch 668/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0356 - mse: 0.0261 - mae: 0.1161 - root_mean_squared_error: 0.1614\n", "Epoch 668: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0357 - mse: 0.0261 - mae: 0.1164 - root_mean_squared_error: 0.1617 - val_loss: 0.4105 - val_mse: 0.4010 - val_mae: 0.4849 - val_root_mean_squared_error: 0.6332\n", "Epoch 669/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0362 - mse: 0.0266 - mae: 0.1206 - root_mean_squared_error: 0.1632\n", "Epoch 669: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0363 - mse: 0.0267 - mae: 0.1208 - root_mean_squared_error: 0.1635 - val_loss: 0.4031 - val_mse: 0.3936 - val_mae: 0.4802 - val_root_mean_squared_error: 0.6273\n", "Epoch 670/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0366 - mse: 0.0270 - mae: 0.1142 - root_mean_squared_error: 0.1645\n", "Epoch 670: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0366 - mse: 0.0270 - mae: 0.1142 - root_mean_squared_error: 0.1645 - val_loss: 0.4033 - val_mse: 0.3938 - val_mae: 0.4742 - val_root_mean_squared_error: 0.6275\n", "Epoch 671/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0340 - mse: 0.0245 - mae: 0.1131 - root_mean_squared_error: 0.1565\n", "Epoch 671: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0341 - mse: 0.0246 - mae: 0.1133 - root_mean_squared_error: 0.1570 - val_loss: 0.4159 - val_mse: 0.4065 - val_mae: 0.4793 - val_root_mean_squared_error: 0.6376\n", "Epoch 672/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0420 - mse: 0.0326 - mae: 0.1326 - root_mean_squared_error: 0.1805\n", "Epoch 672: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0419 - mse: 0.0324 - mae: 0.1322 - root_mean_squared_error: 0.1801 - val_loss: 0.4229 - val_mse: 0.4135 - val_mae: 0.4907 - val_root_mean_squared_error: 0.6430\n", "Epoch 673/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0337 - mse: 0.0242 - mae: 0.1129 - root_mean_squared_error: 0.1557\n", "Epoch 673: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0337 - mse: 0.0242 - mae: 0.1130 - root_mean_squared_error: 0.1557 - val_loss: 0.4107 - val_mse: 0.4013 - val_mae: 0.4785 - val_root_mean_squared_error: 0.6335\n", "Epoch 674/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0385 - mse: 0.0290 - mae: 0.1233 - root_mean_squared_error: 0.1704\n", "Epoch 674: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0385 - mse: 0.0290 - mae: 0.1235 - root_mean_squared_error: 0.1704 - val_loss: 0.4493 - val_mse: 0.4399 - val_mae: 0.4957 - val_root_mean_squared_error: 0.6632\n", "Epoch 675/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0411 - mse: 0.0317 - mae: 0.1296 - root_mean_squared_error: 0.1779\n", "Epoch 675: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0410 - mse: 0.0315 - mae: 0.1294 - root_mean_squared_error: 0.1776 - val_loss: 0.4232 - val_mse: 0.4138 - val_mae: 0.4821 - val_root_mean_squared_error: 0.6432\n", "Epoch 676/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0395 - mse: 0.0300 - mae: 0.1236 - root_mean_squared_error: 0.1733\n", "Epoch 676: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0400 - mse: 0.0306 - mae: 0.1245 - root_mean_squared_error: 0.1749 - val_loss: 0.4091 - val_mse: 0.3997 - val_mae: 0.4791 - val_root_mean_squared_error: 0.6322\n", "Epoch 677/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0402 - mse: 0.0308 - mae: 0.1288 - root_mean_squared_error: 0.1754\n", "Epoch 677: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0398 - mse: 0.0303 - mae: 0.1276 - root_mean_squared_error: 0.1741 - val_loss: 0.4330 - val_mse: 0.4235 - val_mae: 0.4962 - val_root_mean_squared_error: 0.6508\n", "Epoch 678/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0419 - mse: 0.0324 - mae: 0.1314 - root_mean_squared_error: 0.1801\n", "Epoch 678: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0418 - mse: 0.0323 - mae: 0.1312 - root_mean_squared_error: 0.1798 - val_loss: 0.4061 - val_mse: 0.3966 - val_mae: 0.4837 - val_root_mean_squared_error: 0.6298\n", "Epoch 679/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0428 - mse: 0.0334 - mae: 0.1331 - root_mean_squared_error: 0.1827\n", "Epoch 679: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0428 - mse: 0.0334 - mae: 0.1333 - root_mean_squared_error: 0.1828 - val_loss: 0.4078 - val_mse: 0.3984 - val_mae: 0.4796 - val_root_mean_squared_error: 0.6312\n", "Epoch 680/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0342 - mse: 0.0248 - mae: 0.1136 - root_mean_squared_error: 0.1575\n", "Epoch 680: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0342 - mse: 0.0248 - mae: 0.1136 - root_mean_squared_error: 0.1575 - val_loss: 0.4147 - val_mse: 0.4053 - val_mae: 0.4784 - val_root_mean_squared_error: 0.6366\n", "Epoch 681/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0368 - mse: 0.0274 - mae: 0.1187 - root_mean_squared_error: 0.1656\n", "Epoch 681: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0367 - mse: 0.0273 - mae: 0.1184 - root_mean_squared_error: 0.1652 - val_loss: 0.4181 - val_mse: 0.4087 - val_mae: 0.4830 - val_root_mean_squared_error: 0.6393\n", "Epoch 682/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0380 - mse: 0.0286 - mae: 0.1195 - root_mean_squared_error: 0.1691\n", "Epoch 682: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 50ms/step - loss: 0.0378 - mse: 0.0284 - mae: 0.1192 - root_mean_squared_error: 0.1686 - val_loss: 0.4214 - val_mse: 0.4120 - val_mae: 0.4934 - val_root_mean_squared_error: 0.6419\n", "Epoch 683/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0415 - mse: 0.0321 - mae: 0.1308 - root_mean_squared_error: 0.1791\n", "Epoch 683: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0413 - mse: 0.0319 - mae: 0.1306 - root_mean_squared_error: 0.1786 - val_loss: 0.4052 - val_mse: 0.3958 - val_mae: 0.4803 - val_root_mean_squared_error: 0.6291\n", "Epoch 684/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0367 - mse: 0.0273 - mae: 0.1162 - root_mean_squared_error: 0.1652\n", "Epoch 684: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0367 - mse: 0.0273 - mae: 0.1164 - root_mean_squared_error: 0.1651 - val_loss: 0.4062 - val_mse: 0.3968 - val_mae: 0.4723 - val_root_mean_squared_error: 0.6299\n", "Epoch 685/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0354 - mse: 0.0261 - mae: 0.1142 - root_mean_squared_error: 0.1615\n", "Epoch 685: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0354 - mse: 0.0261 - mae: 0.1142 - root_mean_squared_error: 0.1615 - val_loss: 0.4053 - val_mse: 0.3960 - val_mae: 0.4809 - val_root_mean_squared_error: 0.6293\n", "Epoch 686/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0368 - mse: 0.0275 - mae: 0.1167 - root_mean_squared_error: 0.1658\n", "Epoch 686: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0368 - mse: 0.0275 - mae: 0.1167 - root_mean_squared_error: 0.1658 - val_loss: 0.4181 - val_mse: 0.4088 - val_mae: 0.4880 - val_root_mean_squared_error: 0.6393\n", "Epoch 687/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0362 - mse: 0.0268 - mae: 0.1193 - root_mean_squared_error: 0.1638\n", "Epoch 687: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0361 - mse: 0.0267 - mae: 0.1191 - root_mean_squared_error: 0.1635 - val_loss: 0.4347 - val_mse: 0.4254 - val_mae: 0.4964 - val_root_mean_squared_error: 0.6522\n", "Epoch 688/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0464 - mse: 0.0370 - mae: 0.1413 - root_mean_squared_error: 0.1924\n", "Epoch 688: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0465 - mse: 0.0371 - mae: 0.1415 - root_mean_squared_error: 0.1926 - val_loss: 0.4110 - val_mse: 0.4016 - val_mae: 0.4816 - val_root_mean_squared_error: 0.6337\n", "Epoch 689/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0362 - mse: 0.0268 - mae: 0.1177 - root_mean_squared_error: 0.1638\n", "Epoch 689: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0362 - mse: 0.0268 - mae: 0.1177 - root_mean_squared_error: 0.1638 - val_loss: 0.4179 - val_mse: 0.4086 - val_mae: 0.4797 - val_root_mean_squared_error: 0.6392\n", "Epoch 690/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0385 - mse: 0.0291 - mae: 0.1225 - root_mean_squared_error: 0.1706\n", "Epoch 690: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0385 - mse: 0.0291 - mae: 0.1225 - root_mean_squared_error: 0.1706 - val_loss: 0.4232 - val_mse: 0.4138 - val_mae: 0.4950 - val_root_mean_squared_error: 0.6433\n", "Epoch 691/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0427 - mse: 0.0334 - mae: 0.1298 - root_mean_squared_error: 0.1826\n", "Epoch 691: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0427 - mse: 0.0334 - mae: 0.1298 - root_mean_squared_error: 0.1826 - val_loss: 0.4120 - val_mse: 0.4027 - val_mae: 0.4808 - val_root_mean_squared_error: 0.6346\n", "Epoch 692/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0438 - mse: 0.0345 - mae: 0.1344 - root_mean_squared_error: 0.1857\n", "Epoch 692: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0441 - mse: 0.0347 - mae: 0.1350 - root_mean_squared_error: 0.1863 - val_loss: 0.4142 - val_mse: 0.4049 - val_mae: 0.4846 - val_root_mean_squared_error: 0.6363\n", "Epoch 693/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0382 - mse: 0.0288 - mae: 0.1237 - root_mean_squared_error: 0.1697\n", "Epoch 693: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0382 - mse: 0.0288 - mae: 0.1240 - root_mean_squared_error: 0.1697 - val_loss: 0.4266 - val_mse: 0.4173 - val_mae: 0.4878 - val_root_mean_squared_error: 0.6459\n", "Epoch 694/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0392 - mse: 0.0298 - mae: 0.1237 - root_mean_squared_error: 0.1727\n", "Epoch 694: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0390 - mse: 0.0297 - mae: 0.1234 - root_mean_squared_error: 0.1723 - val_loss: 0.4114 - val_mse: 0.4020 - val_mae: 0.4779 - val_root_mean_squared_error: 0.6341\n", "Epoch 695/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0409 - mse: 0.0316 - mae: 0.1274 - root_mean_squared_error: 0.1777\n", "Epoch 695: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0409 - mse: 0.0316 - mae: 0.1274 - root_mean_squared_error: 0.1777 - val_loss: 0.4265 - val_mse: 0.4171 - val_mae: 0.5033 - val_root_mean_squared_error: 0.6458\n", "Epoch 696/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0413 - mse: 0.0319 - mae: 0.1273 - root_mean_squared_error: 0.1787\n", "Epoch 696: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0417 - mse: 0.0323 - mae: 0.1280 - root_mean_squared_error: 0.1797 - val_loss: 0.4104 - val_mse: 0.4010 - val_mae: 0.4774 - val_root_mean_squared_error: 0.6333\n", "Epoch 697/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0432 - mse: 0.0338 - mae: 0.1337 - root_mean_squared_error: 0.1840\n", "Epoch 697: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0431 - mse: 0.0338 - mae: 0.1337 - root_mean_squared_error: 0.1837 - val_loss: 0.4330 - val_mse: 0.4236 - val_mae: 0.4888 - val_root_mean_squared_error: 0.6509\n", "Epoch 698/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0427 - mse: 0.0333 - mae: 0.1324 - root_mean_squared_error: 0.1826\n", "Epoch 698: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0427 - mse: 0.0333 - mae: 0.1324 - root_mean_squared_error: 0.1826 - val_loss: 0.4313 - val_mse: 0.4220 - val_mae: 0.4889 - val_root_mean_squared_error: 0.6496\n", "Epoch 699/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0385 - mse: 0.0292 - mae: 0.1220 - root_mean_squared_error: 0.1709\n", "Epoch 699: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0385 - mse: 0.0292 - mae: 0.1220 - root_mean_squared_error: 0.1709 - val_loss: 0.4317 - val_mse: 0.4224 - val_mae: 0.4924 - val_root_mean_squared_error: 0.6499\n", "Epoch 700/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0486 - mse: 0.0393 - mae: 0.1433 - root_mean_squared_error: 0.1981\n", "Epoch 700: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0486 - mse: 0.0393 - mae: 0.1433 - root_mean_squared_error: 0.1981 - val_loss: 0.4443 - val_mse: 0.4350 - val_mae: 0.4988 - val_root_mean_squared_error: 0.6596\n", "Epoch 701/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0390 - mse: 0.0297 - mae: 0.1217 - root_mean_squared_error: 0.1724\n", "Epoch 701: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0391 - mse: 0.0298 - mae: 0.1218 - root_mean_squared_error: 0.1727 - val_loss: 0.4466 - val_mse: 0.4373 - val_mae: 0.5054 - val_root_mean_squared_error: 0.6613\n", "Epoch 702/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0416 - mse: 0.0323 - mae: 0.1303 - root_mean_squared_error: 0.1798\n", "Epoch 702: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0416 - mse: 0.0323 - mae: 0.1303 - root_mean_squared_error: 0.1798 - val_loss: 0.4076 - val_mse: 0.3983 - val_mae: 0.4708 - val_root_mean_squared_error: 0.6311\n", "Epoch 703/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0435 - mse: 0.0342 - mae: 0.1321 - root_mean_squared_error: 0.1849\n", "Epoch 703: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0435 - mse: 0.0342 - mae: 0.1321 - root_mean_squared_error: 0.1849 - val_loss: 0.4068 - val_mse: 0.3975 - val_mae: 0.4807 - val_root_mean_squared_error: 0.6305\n", "Epoch 704/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0345 - mse: 0.0251 - mae: 0.1140 - root_mean_squared_error: 0.1586\n", "Epoch 704: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 48ms/step - loss: 0.0346 - mse: 0.0253 - mae: 0.1144 - root_mean_squared_error: 0.1589 - val_loss: 0.4218 - val_mse: 0.4125 - val_mae: 0.4863 - val_root_mean_squared_error: 0.6423\n", "Epoch 705/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0347 - mse: 0.0254 - mae: 0.1130 - root_mean_squared_error: 0.1595\n", "Epoch 705: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0344 - mse: 0.0251 - mae: 0.1123 - root_mean_squared_error: 0.1585 - val_loss: 0.4076 - val_mse: 0.3983 - val_mae: 0.4763 - val_root_mean_squared_error: 0.6311\n", "Epoch 706/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0334 - mse: 0.0241 - mae: 0.1109 - root_mean_squared_error: 0.1552\n", "Epoch 706: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0333 - mse: 0.0240 - mae: 0.1107 - root_mean_squared_error: 0.1549 - val_loss: 0.4138 - val_mse: 0.4046 - val_mae: 0.4770 - val_root_mean_squared_error: 0.6361\n", "Epoch 707/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0397 - mse: 0.0304 - mae: 0.1302 - root_mean_squared_error: 0.1744\n", "Epoch 707: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0395 - mse: 0.0302 - mae: 0.1298 - root_mean_squared_error: 0.1739 - val_loss: 0.4257 - val_mse: 0.4165 - val_mae: 0.4850 - val_root_mean_squared_error: 0.6453\n", "Epoch 708/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0361 - mse: 0.0269 - mae: 0.1184 - root_mean_squared_error: 0.1640\n", "Epoch 708: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0361 - mse: 0.0268 - mae: 0.1183 - root_mean_squared_error: 0.1638 - val_loss: 0.4207 - val_mse: 0.4115 - val_mae: 0.4909 - val_root_mean_squared_error: 0.6415\n", "Epoch 709/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0363 - mse: 0.0271 - mae: 0.1163 - root_mean_squared_error: 0.1645\n", "Epoch 709: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0363 - mse: 0.0271 - mae: 0.1163 - root_mean_squared_error: 0.1645 - val_loss: 0.4418 - val_mse: 0.4326 - val_mae: 0.5006 - val_root_mean_squared_error: 0.6577\n", "Epoch 710/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0375 - mse: 0.0283 - mae: 0.1189 - root_mean_squared_error: 0.1683\n", "Epoch 710: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0375 - mse: 0.0283 - mae: 0.1189 - root_mean_squared_error: 0.1683 - val_loss: 0.4252 - val_mse: 0.4160 - val_mae: 0.4911 - val_root_mean_squared_error: 0.6450\n", "Epoch 711/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0397 - mse: 0.0305 - mae: 0.1266 - root_mean_squared_error: 0.1746\n", "Epoch 711: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 53ms/step - loss: 0.0396 - mse: 0.0304 - mae: 0.1265 - root_mean_squared_error: 0.1742 - val_loss: 0.3910 - val_mse: 0.3818 - val_mae: 0.4669 - val_root_mean_squared_error: 0.6179\n", "Epoch 712/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0377 - mse: 0.0285 - mae: 0.1191 - root_mean_squared_error: 0.1687\n", "Epoch 712: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0376 - mse: 0.0284 - mae: 0.1192 - root_mean_squared_error: 0.1686 - val_loss: 0.4209 - val_mse: 0.4117 - val_mae: 0.4832 - val_root_mean_squared_error: 0.6417\n", "Epoch 713/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0389 - mse: 0.0297 - mae: 0.1182 - root_mean_squared_error: 0.1722\n", "Epoch 713: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0389 - mse: 0.0297 - mae: 0.1182 - root_mean_squared_error: 0.1722 - val_loss: 0.4200 - val_mse: 0.4108 - val_mae: 0.4907 - val_root_mean_squared_error: 0.6409\n", "Epoch 714/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0468 - mse: 0.0376 - mae: 0.1359 - root_mean_squared_error: 0.1938\n", "Epoch 714: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 59ms/step - loss: 0.0466 - mse: 0.0374 - mae: 0.1357 - root_mean_squared_error: 0.1934 - val_loss: 0.4001 - val_mse: 0.3909 - val_mae: 0.4747 - val_root_mean_squared_error: 0.6252\n", "Epoch 715/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0407 - mse: 0.0315 - mae: 0.1238 - root_mean_squared_error: 0.1774\n", "Epoch 715: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0409 - mse: 0.0317 - mae: 0.1242 - root_mean_squared_error: 0.1782 - val_loss: 0.4306 - val_mse: 0.4213 - val_mae: 0.4968 - val_root_mean_squared_error: 0.6491\n", "Epoch 716/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0354 - mse: 0.0262 - mae: 0.1188 - root_mean_squared_error: 0.1618\n", "Epoch 716: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0358 - mse: 0.0266 - mae: 0.1190 - root_mean_squared_error: 0.1632 - val_loss: 0.4405 - val_mse: 0.4313 - val_mae: 0.4997 - val_root_mean_squared_error: 0.6568\n", "Epoch 717/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0442 - mse: 0.0349 - mae: 0.1372 - root_mean_squared_error: 0.1869\n", "Epoch 717: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0440 - mse: 0.0348 - mae: 0.1370 - root_mean_squared_error: 0.1866 - val_loss: 0.4237 - val_mse: 0.4145 - val_mae: 0.4792 - val_root_mean_squared_error: 0.6438\n", "Epoch 718/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0362 - mse: 0.0270 - mae: 0.1166 - root_mean_squared_error: 0.1642\n", "Epoch 718: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0362 - mse: 0.0270 - mae: 0.1166 - root_mean_squared_error: 0.1642 - val_loss: 0.3977 - val_mse: 0.3884 - val_mae: 0.4708 - val_root_mean_squared_error: 0.6233\n", "Epoch 719/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0356 - mse: 0.0263 - mae: 0.1191 - root_mean_squared_error: 0.1622\n", "Epoch 719: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0355 - mse: 0.0262 - mae: 0.1188 - root_mean_squared_error: 0.1619 - val_loss: 0.4217 - val_mse: 0.4124 - val_mae: 0.4870 - val_root_mean_squared_error: 0.6422\n", "Epoch 720/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0498 - mse: 0.0406 - mae: 0.1416 - root_mean_squared_error: 0.2014\n", "Epoch 720: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0495 - mse: 0.0403 - mae: 0.1411 - root_mean_squared_error: 0.2008 - val_loss: 0.4209 - val_mse: 0.4117 - val_mae: 0.4845 - val_root_mean_squared_error: 0.6416\n", "Epoch 721/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0387 - mse: 0.0295 - mae: 0.1236 - root_mean_squared_error: 0.1716\n", "Epoch 721: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0389 - mse: 0.0297 - mae: 0.1241 - root_mean_squared_error: 0.1723 - val_loss: 0.4038 - val_mse: 0.3946 - val_mae: 0.4726 - val_root_mean_squared_error: 0.6282\n", "Epoch 722/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0364 - mse: 0.0272 - mae: 0.1195 - root_mean_squared_error: 0.1649\n", "Epoch 722: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0364 - mse: 0.0272 - mae: 0.1195 - root_mean_squared_error: 0.1649 - val_loss: 0.3858 - val_mse: 0.3766 - val_mae: 0.4678 - val_root_mean_squared_error: 0.6137\n", "Epoch 723/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0344 - mse: 0.0252 - mae: 0.1155 - root_mean_squared_error: 0.1587\n", "Epoch 723: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0342 - mse: 0.0251 - mae: 0.1151 - root_mean_squared_error: 0.1583 - val_loss: 0.4534 - val_mse: 0.4442 - val_mae: 0.5165 - val_root_mean_squared_error: 0.6665\n", "Epoch 724/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0398 - mse: 0.0306 - mae: 0.1281 - root_mean_squared_error: 0.1750\n", "Epoch 724: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0397 - mse: 0.0305 - mae: 0.1279 - root_mean_squared_error: 0.1746 - val_loss: 0.3940 - val_mse: 0.3848 - val_mae: 0.4718 - val_root_mean_squared_error: 0.6204\n", "Epoch 725/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0352 - mse: 0.0260 - mae: 0.1166 - root_mean_squared_error: 0.1614\n", "Epoch 725: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0353 - mse: 0.0261 - mae: 0.1169 - root_mean_squared_error: 0.1616 - val_loss: 0.3975 - val_mse: 0.3884 - val_mae: 0.4793 - val_root_mean_squared_error: 0.6232\n", "Epoch 726/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0361 - mse: 0.0269 - mae: 0.1188 - root_mean_squared_error: 0.1642\n", "Epoch 726: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0362 - mse: 0.0271 - mae: 0.1191 - root_mean_squared_error: 0.1645 - val_loss: 0.4227 - val_mse: 0.4136 - val_mae: 0.4854 - val_root_mean_squared_error: 0.6431\n", "Epoch 727/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0423 - mse: 0.0332 - mae: 0.1323 - root_mean_squared_error: 0.1822\n", "Epoch 727: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0423 - mse: 0.0332 - mae: 0.1323 - root_mean_squared_error: 0.1822 - val_loss: 0.4021 - val_mse: 0.3930 - val_mae: 0.4790 - val_root_mean_squared_error: 0.6269\n", "Epoch 728/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0450 - mse: 0.0359 - mae: 0.1410 - root_mean_squared_error: 0.1894\n", "Epoch 728: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0450 - mse: 0.0359 - mae: 0.1410 - root_mean_squared_error: 0.1894 - val_loss: 0.4221 - val_mse: 0.4129 - val_mae: 0.4897 - val_root_mean_squared_error: 0.6426\n", "Epoch 729/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0448 - mse: 0.0357 - mae: 0.1363 - root_mean_squared_error: 0.1889\n", "Epoch 729: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0460 - mse: 0.0368 - mae: 0.1370 - root_mean_squared_error: 0.1919 - val_loss: 0.4569 - val_mse: 0.4477 - val_mae: 0.4980 - val_root_mean_squared_error: 0.6691\n", "Epoch 730/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0407 - mse: 0.0316 - mae: 0.1278 - root_mean_squared_error: 0.1777\n", "Epoch 730: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0407 - mse: 0.0316 - mae: 0.1278 - root_mean_squared_error: 0.1777 - val_loss: 0.4078 - val_mse: 0.3986 - val_mae: 0.4775 - val_root_mean_squared_error: 0.6313\n", "Epoch 731/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0395 - mse: 0.0304 - mae: 0.1250 - root_mean_squared_error: 0.1743\n", "Epoch 731: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0394 - mse: 0.0303 - mae: 0.1246 - root_mean_squared_error: 0.1739 - val_loss: 0.3990 - val_mse: 0.3898 - val_mae: 0.4719 - val_root_mean_squared_error: 0.6243\n", "Epoch 732/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0390 - mse: 0.0298 - mae: 0.1278 - root_mean_squared_error: 0.1727\n", "Epoch 732: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0390 - mse: 0.0298 - mae: 0.1278 - root_mean_squared_error: 0.1727 - val_loss: 0.4063 - val_mse: 0.3972 - val_mae: 0.4812 - val_root_mean_squared_error: 0.6302\n", "Epoch 733/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0440 - mse: 0.0348 - mae: 0.1324 - root_mean_squared_error: 0.1866\n", "Epoch 733: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0440 - mse: 0.0348 - mae: 0.1324 - root_mean_squared_error: 0.1866 - val_loss: 0.4097 - val_mse: 0.4006 - val_mae: 0.4851 - val_root_mean_squared_error: 0.6329\n", "Epoch 734/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0368 - mse: 0.0277 - mae: 0.1183 - root_mean_squared_error: 0.1664\n", "Epoch 734: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 56ms/step - loss: 0.0368 - mse: 0.0277 - mae: 0.1183 - root_mean_squared_error: 0.1664 - val_loss: 0.4110 - val_mse: 0.4019 - val_mae: 0.4794 - val_root_mean_squared_error: 0.6339\n", "Epoch 735/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0350 - mse: 0.0259 - mae: 0.1124 - root_mean_squared_error: 0.1609\n", "Epoch 735: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0350 - mse: 0.0259 - mae: 0.1124 - root_mean_squared_error: 0.1609 - val_loss: 0.4038 - val_mse: 0.3947 - val_mae: 0.4745 - val_root_mean_squared_error: 0.6282\n", "Epoch 736/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0534 - mse: 0.0443 - mae: 0.1541 - root_mean_squared_error: 0.2105\n", "Epoch 736: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0532 - mse: 0.0441 - mae: 0.1537 - root_mean_squared_error: 0.2099 - val_loss: 0.4278 - val_mse: 0.4187 - val_mae: 0.4906 - val_root_mean_squared_error: 0.6470\n", "Epoch 737/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0407 - mse: 0.0315 - mae: 0.1290 - root_mean_squared_error: 0.1775\n", "Epoch 737: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0406 - mse: 0.0314 - mae: 0.1289 - root_mean_squared_error: 0.1773 - val_loss: 0.4239 - val_mse: 0.4147 - val_mae: 0.4817 - val_root_mean_squared_error: 0.6440\n", "Epoch 738/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0375 - mse: 0.0284 - mae: 0.1187 - root_mean_squared_error: 0.1684\n", "Epoch 738: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0375 - mse: 0.0284 - mae: 0.1189 - root_mean_squared_error: 0.1685 - val_loss: 0.3830 - val_mse: 0.3739 - val_mae: 0.4658 - val_root_mean_squared_error: 0.6115\n", "Epoch 739/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0411 - mse: 0.0320 - mae: 0.1293 - root_mean_squared_error: 0.1788\n", "Epoch 739: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0412 - mse: 0.0321 - mae: 0.1295 - root_mean_squared_error: 0.1791 - val_loss: 0.4136 - val_mse: 0.4045 - val_mae: 0.4799 - val_root_mean_squared_error: 0.6360\n", "Epoch 740/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0360 - mse: 0.0268 - mae: 0.1168 - root_mean_squared_error: 0.1639\n", "Epoch 740: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0358 - mse: 0.0267 - mae: 0.1166 - root_mean_squared_error: 0.1635 - val_loss: 0.4169 - val_mse: 0.4079 - val_mae: 0.4755 - val_root_mean_squared_error: 0.6386\n", "Epoch 741/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0359 - mse: 0.0269 - mae: 0.1155 - root_mean_squared_error: 0.1639\n", "Epoch 741: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0358 - mse: 0.0267 - mae: 0.1150 - root_mean_squared_error: 0.1633 - val_loss: 0.3921 - val_mse: 0.3830 - val_mae: 0.4652 - val_root_mean_squared_error: 0.6189\n", "Epoch 742/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0352 - mse: 0.0261 - mae: 0.1165 - root_mean_squared_error: 0.1615\n", "Epoch 742: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0352 - mse: 0.0261 - mae: 0.1165 - root_mean_squared_error: 0.1615 - val_loss: 0.4133 - val_mse: 0.4043 - val_mae: 0.4828 - val_root_mean_squared_error: 0.6358\n", "Epoch 743/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0419 - mse: 0.0328 - mae: 0.1295 - root_mean_squared_error: 0.1811\n", "Epoch 743: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0417 - mse: 0.0327 - mae: 0.1292 - root_mean_squared_error: 0.1807 - val_loss: 0.3919 - val_mse: 0.3828 - val_mae: 0.4701 - val_root_mean_squared_error: 0.6187\n", "Epoch 744/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0346 - mse: 0.0256 - mae: 0.1164 - root_mean_squared_error: 0.1599\n", "Epoch 744: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0346 - mse: 0.0256 - mae: 0.1164 - root_mean_squared_error: 0.1599 - val_loss: 0.4172 - val_mse: 0.4082 - val_mae: 0.4809 - val_root_mean_squared_error: 0.6389\n", "Epoch 745/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0407 - mse: 0.0317 - mae: 0.1298 - root_mean_squared_error: 0.1780\n", "Epoch 745: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0403 - mse: 0.0312 - mae: 0.1288 - root_mean_squared_error: 0.1767 - val_loss: 0.4302 - val_mse: 0.4212 - val_mae: 0.4954 - val_root_mean_squared_error: 0.6490\n", "Epoch 746/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0356 - mse: 0.0265 - mae: 0.1164 - root_mean_squared_error: 0.1629\n", "Epoch 746: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0356 - mse: 0.0265 - mae: 0.1164 - root_mean_squared_error: 0.1629 - val_loss: 0.3961 - val_mse: 0.3871 - val_mae: 0.4713 - val_root_mean_squared_error: 0.6222\n", "Epoch 747/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0376 - mse: 0.0285 - mae: 0.1197 - root_mean_squared_error: 0.1689\n", "Epoch 747: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0376 - mse: 0.0285 - mae: 0.1197 - root_mean_squared_error: 0.1689 - val_loss: 0.4032 - val_mse: 0.3942 - val_mae: 0.4722 - val_root_mean_squared_error: 0.6279\n", "Epoch 748/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0314 - mse: 0.0224 - mae: 0.1096 - root_mean_squared_error: 0.1497\n", "Epoch 748: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0314 - mse: 0.0224 - mae: 0.1096 - root_mean_squared_error: 0.1497 - val_loss: 0.3994 - val_mse: 0.3904 - val_mae: 0.4737 - val_root_mean_squared_error: 0.6248\n", "Epoch 749/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0358 - mse: 0.0268 - mae: 0.1172 - root_mean_squared_error: 0.1636\n", "Epoch 749: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0358 - mse: 0.0268 - mae: 0.1172 - root_mean_squared_error: 0.1636 - val_loss: 0.4069 - val_mse: 0.3979 - val_mae: 0.4758 - val_root_mean_squared_error: 0.6308\n", "Epoch 750/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0414 - mse: 0.0323 - mae: 0.1294 - root_mean_squared_error: 0.1798\n", "Epoch 750: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0414 - mse: 0.0323 - mae: 0.1294 - root_mean_squared_error: 0.1798 - val_loss: 0.4125 - val_mse: 0.4035 - val_mae: 0.4878 - val_root_mean_squared_error: 0.6352\n", "Epoch 751/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0355 - mse: 0.0265 - mae: 0.1161 - root_mean_squared_error: 0.1628\n", "Epoch 751: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 54ms/step - loss: 0.0355 - mse: 0.0265 - mae: 0.1161 - root_mean_squared_error: 0.1628 - val_loss: 0.4312 - val_mse: 0.4222 - val_mae: 0.4888 - val_root_mean_squared_error: 0.6498\n", "Epoch 752/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0375 - mse: 0.0285 - mae: 0.1187 - root_mean_squared_error: 0.1688\n", "Epoch 752: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0375 - mse: 0.0285 - mae: 0.1187 - root_mean_squared_error: 0.1688 - val_loss: 0.4058 - val_mse: 0.3968 - val_mae: 0.4723 - val_root_mean_squared_error: 0.6300\n", "Epoch 753/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0444 - mse: 0.0354 - mae: 0.1360 - root_mean_squared_error: 0.1883\n", "Epoch 753: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0443 - mse: 0.0353 - mae: 0.1358 - root_mean_squared_error: 0.1878 - val_loss: 0.4166 - val_mse: 0.4076 - val_mae: 0.4848 - val_root_mean_squared_error: 0.6384\n", "Epoch 754/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0361 - mse: 0.0271 - mae: 0.1196 - root_mean_squared_error: 0.1645\n", "Epoch 754: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0362 - mse: 0.0272 - mae: 0.1201 - root_mean_squared_error: 0.1650 - val_loss: 0.4302 - val_mse: 0.4212 - val_mae: 0.4908 - val_root_mean_squared_error: 0.6490\n", "Epoch 755/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0458 - mse: 0.0368 - mae: 0.1345 - root_mean_squared_error: 0.1919\n", "Epoch 755: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0458 - mse: 0.0368 - mae: 0.1345 - root_mean_squared_error: 0.1919 - val_loss: 0.4123 - val_mse: 0.4033 - val_mae: 0.4917 - val_root_mean_squared_error: 0.6351\n", "Epoch 756/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0410 - mse: 0.0319 - mae: 0.1273 - root_mean_squared_error: 0.1787\n", "Epoch 756: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0410 - mse: 0.0319 - mae: 0.1273 - root_mean_squared_error: 0.1787 - val_loss: 0.4043 - val_mse: 0.3953 - val_mae: 0.4710 - val_root_mean_squared_error: 0.6287\n", "Epoch 757/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0373 - mse: 0.0282 - mae: 0.1218 - root_mean_squared_error: 0.1681\n", "Epoch 757: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0373 - mse: 0.0282 - mae: 0.1218 - root_mean_squared_error: 0.1681 - val_loss: 0.4167 - val_mse: 0.4077 - val_mae: 0.4834 - val_root_mean_squared_error: 0.6385\n", "Epoch 758/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0381 - mse: 0.0291 - mae: 0.1202 - root_mean_squared_error: 0.1705\n", "Epoch 758: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0381 - mse: 0.0291 - mae: 0.1202 - root_mean_squared_error: 0.1705 - val_loss: 0.4065 - val_mse: 0.3975 - val_mae: 0.4767 - val_root_mean_squared_error: 0.6305\n", "Epoch 759/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0433 - mse: 0.0343 - mae: 0.1310 - root_mean_squared_error: 0.1852\n", "Epoch 759: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0431 - mse: 0.0341 - mae: 0.1306 - root_mean_squared_error: 0.1848 - val_loss: 0.4116 - val_mse: 0.4026 - val_mae: 0.4815 - val_root_mean_squared_error: 0.6345\n", "Epoch 760/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0461 - mse: 0.0371 - mae: 0.1357 - root_mean_squared_error: 0.1926\n", "Epoch 760: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0461 - mse: 0.0370 - mae: 0.1357 - root_mean_squared_error: 0.1924 - val_loss: 0.4099 - val_mse: 0.4008 - val_mae: 0.4803 - val_root_mean_squared_error: 0.6331\n", "Epoch 761/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0379 - mse: 0.0288 - mae: 0.1219 - root_mean_squared_error: 0.1698\n", "Epoch 761: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0379 - mse: 0.0289 - mae: 0.1215 - root_mean_squared_error: 0.1700 - val_loss: 0.4060 - val_mse: 0.3969 - val_mae: 0.4727 - val_root_mean_squared_error: 0.6300\n", "Epoch 762/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0381 - mse: 0.0290 - mae: 0.1249 - root_mean_squared_error: 0.1704\n", "Epoch 762: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0381 - mse: 0.0290 - mae: 0.1249 - root_mean_squared_error: 0.1704 - val_loss: 0.4245 - val_mse: 0.4155 - val_mae: 0.4791 - val_root_mean_squared_error: 0.6446\n", "Epoch 763/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0351 - mse: 0.0261 - mae: 0.1171 - root_mean_squared_error: 0.1616\n", "Epoch 763: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0351 - mse: 0.0261 - mae: 0.1171 - root_mean_squared_error: 0.1616 - val_loss: 0.4091 - val_mse: 0.4001 - val_mae: 0.4802 - val_root_mean_squared_error: 0.6325\n", "Epoch 764/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0336 - mse: 0.0246 - mae: 0.1156 - root_mean_squared_error: 0.1568\n", "Epoch 764: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0369 - mse: 0.0279 - mae: 0.1180 - root_mean_squared_error: 0.1670 - val_loss: 0.4005 - val_mse: 0.3915 - val_mae: 0.4689 - val_root_mean_squared_error: 0.6257\n", "Epoch 765/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0471 - mse: 0.0381 - mae: 0.1403 - root_mean_squared_error: 0.1953\n", "Epoch 765: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0469 - mse: 0.0379 - mae: 0.1400 - root_mean_squared_error: 0.1948 - val_loss: 0.4105 - val_mse: 0.4015 - val_mae: 0.4798 - val_root_mean_squared_error: 0.6337\n", "Epoch 766/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0367 - mse: 0.0277 - mae: 0.1185 - root_mean_squared_error: 0.1666\n", "Epoch 766: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0367 - mse: 0.0277 - mae: 0.1185 - root_mean_squared_error: 0.1666 - val_loss: 0.4343 - val_mse: 0.4253 - val_mae: 0.4918 - val_root_mean_squared_error: 0.6522\n", "Epoch 767/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0350 - mse: 0.0260 - mae: 0.1145 - root_mean_squared_error: 0.1613\n", "Epoch 767: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0349 - mse: 0.0259 - mae: 0.1142 - root_mean_squared_error: 0.1609 - val_loss: 0.3986 - val_mse: 0.3897 - val_mae: 0.4716 - val_root_mean_squared_error: 0.6242\n", "Epoch 768/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0337 - mse: 0.0247 - mae: 0.1132 - root_mean_squared_error: 0.1573\n", "Epoch 768: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0337 - mse: 0.0247 - mae: 0.1132 - root_mean_squared_error: 0.1573 - val_loss: 0.4073 - val_mse: 0.3984 - val_mae: 0.4735 - val_root_mean_squared_error: 0.6312\n", "Epoch 769/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0355 - mse: 0.0266 - mae: 0.1189 - root_mean_squared_error: 0.1630\n", "Epoch 769: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0355 - mse: 0.0266 - mae: 0.1189 - root_mean_squared_error: 0.1630 - val_loss: 0.4074 - val_mse: 0.3985 - val_mae: 0.4719 - val_root_mean_squared_error: 0.6312\n", "Epoch 770/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0327 - mse: 0.0238 - mae: 0.1086 - root_mean_squared_error: 0.1541\n", "Epoch 770: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0327 - mse: 0.0238 - mae: 0.1086 - root_mean_squared_error: 0.1541 - val_loss: 0.3988 - val_mse: 0.3899 - val_mae: 0.4723 - val_root_mean_squared_error: 0.6244\n", "Epoch 771/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0332 - mse: 0.0243 - mae: 0.1108 - root_mean_squared_error: 0.1558\n", "Epoch 771: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0332 - mse: 0.0243 - mae: 0.1108 - root_mean_squared_error: 0.1558 - val_loss: 0.4043 - val_mse: 0.3954 - val_mae: 0.4691 - val_root_mean_squared_error: 0.6288\n", "Epoch 772/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0354 - mse: 0.0265 - mae: 0.1170 - root_mean_squared_error: 0.1628\n", "Epoch 772: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0354 - mse: 0.0265 - mae: 0.1170 - root_mean_squared_error: 0.1628 - val_loss: 0.4092 - val_mse: 0.4003 - val_mae: 0.4773 - val_root_mean_squared_error: 0.6327\n", "Epoch 773/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0343 - mse: 0.0254 - mae: 0.1145 - root_mean_squared_error: 0.1594\n", "Epoch 773: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0343 - mse: 0.0254 - mae: 0.1145 - root_mean_squared_error: 0.1594 - val_loss: 0.4006 - val_mse: 0.3918 - val_mae: 0.4679 - val_root_mean_squared_error: 0.6259\n", "Epoch 774/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0438 - mse: 0.0349 - mae: 0.1326 - root_mean_squared_error: 0.1869\n", "Epoch 774: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0438 - mse: 0.0349 - mae: 0.1326 - root_mean_squared_error: 0.1869 - val_loss: 0.4223 - val_mse: 0.4135 - val_mae: 0.4941 - val_root_mean_squared_error: 0.6430\n", "Epoch 775/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0359 - mse: 0.0270 - mae: 0.1190 - root_mean_squared_error: 0.1645\n", "Epoch 775: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0358 - mse: 0.0269 - mae: 0.1189 - root_mean_squared_error: 0.1641 - val_loss: 0.4043 - val_mse: 0.3954 - val_mae: 0.4771 - val_root_mean_squared_error: 0.6288\n", "Epoch 776/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0356 - mse: 0.0267 - mae: 0.1155 - root_mean_squared_error: 0.1635\n", "Epoch 776: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0357 - mse: 0.0268 - mae: 0.1157 - root_mean_squared_error: 0.1637 - val_loss: 0.3911 - val_mse: 0.3823 - val_mae: 0.4730 - val_root_mean_squared_error: 0.6183\n", "Epoch 777/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0356 - mse: 0.0268 - mae: 0.1174 - root_mean_squared_error: 0.1636\n", "Epoch 777: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0356 - mse: 0.0268 - mae: 0.1174 - root_mean_squared_error: 0.1636 - val_loss: 0.4005 - val_mse: 0.3917 - val_mae: 0.4785 - val_root_mean_squared_error: 0.6258\n", "Epoch 778/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0378 - mse: 0.0290 - mae: 0.1226 - root_mean_squared_error: 0.1702\n", "Epoch 778: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0378 - mse: 0.0290 - mae: 0.1226 - root_mean_squared_error: 0.1702 - val_loss: 0.4394 - val_mse: 0.4306 - val_mae: 0.4956 - val_root_mean_squared_error: 0.6562\n", "Epoch 779/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0400 - mse: 0.0311 - mae: 0.1249 - root_mean_squared_error: 0.1765\n", "Epoch 779: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0400 - mse: 0.0311 - mae: 0.1249 - root_mean_squared_error: 0.1765 - val_loss: 0.4360 - val_mse: 0.4272 - val_mae: 0.4992 - val_root_mean_squared_error: 0.6536\n", "Epoch 780/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0427 - mse: 0.0339 - mae: 0.1299 - root_mean_squared_error: 0.1841\n", "Epoch 780: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0426 - mse: 0.0338 - mae: 0.1298 - root_mean_squared_error: 0.1839 - val_loss: 0.4664 - val_mse: 0.4576 - val_mae: 0.5118 - val_root_mean_squared_error: 0.6765\n", "Epoch 781/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0592 - mse: 0.0503 - mae: 0.1642 - root_mean_squared_error: 0.2242\n", "Epoch 781: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 48ms/step - loss: 0.0592 - mse: 0.0503 - mae: 0.1642 - root_mean_squared_error: 0.2242 - val_loss: 0.4231 - val_mse: 0.4142 - val_mae: 0.4842 - val_root_mean_squared_error: 0.6436\n", "Epoch 782/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0382 - mse: 0.0293 - mae: 0.1241 - root_mean_squared_error: 0.1710\n", "Epoch 782: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0382 - mse: 0.0293 - mae: 0.1241 - root_mean_squared_error: 0.1710 - val_loss: 0.4185 - val_mse: 0.4096 - val_mae: 0.4858 - val_root_mean_squared_error: 0.6400\n", "Epoch 783/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0317 - mse: 0.0228 - mae: 0.1079 - root_mean_squared_error: 0.1509\n", "Epoch 783: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0317 - mse: 0.0228 - mae: 0.1081 - root_mean_squared_error: 0.1511 - val_loss: 0.4282 - val_mse: 0.4193 - val_mae: 0.4959 - val_root_mean_squared_error: 0.6475\n", "Epoch 784/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0398 - mse: 0.0309 - mae: 0.1261 - root_mean_squared_error: 0.1757\n", "Epoch 784: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 55ms/step - loss: 0.0396 - mse: 0.0307 - mae: 0.1259 - root_mean_squared_error: 0.1753 - val_loss: 0.4120 - val_mse: 0.4031 - val_mae: 0.4798 - val_root_mean_squared_error: 0.6349\n", "Epoch 785/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0335 - mse: 0.0246 - mae: 0.1142 - root_mean_squared_error: 0.1569\n", "Epoch 785: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 53ms/step - loss: 0.0333 - mse: 0.0244 - mae: 0.1137 - root_mean_squared_error: 0.1563 - val_loss: 0.4260 - val_mse: 0.4171 - val_mae: 0.4804 - val_root_mean_squared_error: 0.6459\n", "Epoch 786/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0320 - mse: 0.0231 - mae: 0.1112 - root_mean_squared_error: 0.1521\n", "Epoch 786: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0320 - mse: 0.0231 - mae: 0.1112 - root_mean_squared_error: 0.1521 - val_loss: 0.4117 - val_mse: 0.4029 - val_mae: 0.4743 - val_root_mean_squared_error: 0.6347\n", "Epoch 787/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0353 - mse: 0.0265 - mae: 0.1169 - root_mean_squared_error: 0.1629\n", "Epoch 787: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 0.0353 - mse: 0.0265 - mae: 0.1169 - root_mean_squared_error: 0.1629 - val_loss: 0.4063 - val_mse: 0.3975 - val_mae: 0.4783 - val_root_mean_squared_error: 0.6305\n", "Epoch 788/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0375 - mse: 0.0287 - mae: 0.1206 - root_mean_squared_error: 0.1693\n", "Epoch 788: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0374 - mse: 0.0286 - mae: 0.1206 - root_mean_squared_error: 0.1692 - val_loss: 0.4213 - val_mse: 0.4125 - val_mae: 0.4777 - val_root_mean_squared_error: 0.6423\n", "Epoch 789/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0377 - mse: 0.0289 - mae: 0.1215 - root_mean_squared_error: 0.1700\n", "Epoch 789: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0376 - mse: 0.0288 - mae: 0.1214 - root_mean_squared_error: 0.1697 - val_loss: 0.4388 - val_mse: 0.4300 - val_mae: 0.4877 - val_root_mean_squared_error: 0.6557\n", "Epoch 790/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0417 - mse: 0.0329 - mae: 0.1287 - root_mean_squared_error: 0.1814\n", "Epoch 790: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0417 - mse: 0.0329 - mae: 0.1287 - root_mean_squared_error: 0.1814 - val_loss: 0.3982 - val_mse: 0.3894 - val_mae: 0.4761 - val_root_mean_squared_error: 0.6240\n", "Epoch 791/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0369 - mse: 0.0282 - mae: 0.1227 - root_mean_squared_error: 0.1678\n", "Epoch 791: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0368 - mse: 0.0280 - mae: 0.1225 - root_mean_squared_error: 0.1675 - val_loss: 0.4167 - val_mse: 0.4079 - val_mae: 0.4835 - val_root_mean_squared_error: 0.6386\n", "Epoch 792/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0351 - mse: 0.0263 - mae: 0.1145 - root_mean_squared_error: 0.1621\n", "Epoch 792: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0351 - mse: 0.0263 - mae: 0.1145 - root_mean_squared_error: 0.1621 - val_loss: 0.4062 - val_mse: 0.3975 - val_mae: 0.4802 - val_root_mean_squared_error: 0.6304\n", "Epoch 793/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0367 - mse: 0.0280 - mae: 0.1188 - root_mean_squared_error: 0.1673\n", "Epoch 793: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0367 - mse: 0.0280 - mae: 0.1188 - root_mean_squared_error: 0.1673 - val_loss: 0.4023 - val_mse: 0.3935 - val_mae: 0.4716 - val_root_mean_squared_error: 0.6273\n", "Epoch 794/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0351 - mse: 0.0263 - mae: 0.1180 - root_mean_squared_error: 0.1622\n", "Epoch 794: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0352 - mse: 0.0264 - mae: 0.1181 - root_mean_squared_error: 0.1625 - val_loss: 0.4224 - val_mse: 0.4136 - val_mae: 0.4836 - val_root_mean_squared_error: 0.6431\n", "Epoch 795/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0350 - mse: 0.0263 - mae: 0.1151 - root_mean_squared_error: 0.1621\n", "Epoch 795: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0350 - mse: 0.0262 - mae: 0.1152 - root_mean_squared_error: 0.1619 - val_loss: 0.4035 - val_mse: 0.3947 - val_mae: 0.4698 - val_root_mean_squared_error: 0.6283\n", "Epoch 796/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0355 - mse: 0.0268 - mae: 0.1161 - root_mean_squared_error: 0.1637\n", "Epoch 796: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0354 - mse: 0.0267 - mae: 0.1160 - root_mean_squared_error: 0.1634 - val_loss: 0.4282 - val_mse: 0.4195 - val_mae: 0.4936 - val_root_mean_squared_error: 0.6477\n", "Epoch 797/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0349 - mse: 0.0262 - mae: 0.1167 - root_mean_squared_error: 0.1619\n", "Epoch 797: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0349 - mse: 0.0262 - mae: 0.1167 - root_mean_squared_error: 0.1619 - val_loss: 0.4176 - val_mse: 0.4089 - val_mae: 0.4914 - val_root_mean_squared_error: 0.6395\n", "Epoch 798/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0378 - mse: 0.0291 - mae: 0.1257 - root_mean_squared_error: 0.1705\n", "Epoch 798: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0378 - mse: 0.0291 - mae: 0.1260 - root_mean_squared_error: 0.1705 - val_loss: 0.4017 - val_mse: 0.3930 - val_mae: 0.4731 - val_root_mean_squared_error: 0.6269\n", "Epoch 799/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0391 - mse: 0.0304 - mae: 0.1232 - root_mean_squared_error: 0.1744\n", "Epoch 799: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0391 - mse: 0.0304 - mae: 0.1232 - root_mean_squared_error: 0.1744 - val_loss: 0.4103 - val_mse: 0.4016 - val_mae: 0.4757 - val_root_mean_squared_error: 0.6337\n", "Epoch 800/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0396 - mse: 0.0309 - mae: 0.1260 - root_mean_squared_error: 0.1757\n", "Epoch 800: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0397 - mse: 0.0310 - mae: 0.1267 - root_mean_squared_error: 0.1760 - val_loss: 0.4057 - val_mse: 0.3970 - val_mae: 0.4693 - val_root_mean_squared_error: 0.6300\n", "Epoch 801/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0411 - mse: 0.0323 - mae: 0.1316 - root_mean_squared_error: 0.1798\n", "Epoch 801: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0410 - mse: 0.0323 - mae: 0.1319 - root_mean_squared_error: 0.1797 - val_loss: 0.4011 - val_mse: 0.3924 - val_mae: 0.4698 - val_root_mean_squared_error: 0.6264\n", "Epoch 802/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0414 - mse: 0.0326 - mae: 0.1324 - root_mean_squared_error: 0.1806\n", "Epoch 802: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0413 - mse: 0.0326 - mae: 0.1323 - root_mean_squared_error: 0.1805 - val_loss: 0.4162 - val_mse: 0.4074 - val_mae: 0.4818 - val_root_mean_squared_error: 0.6383\n", "Epoch 803/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0348 - mse: 0.0260 - mae: 0.1152 - root_mean_squared_error: 0.1613\n", "Epoch 803: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0347 - mse: 0.0260 - mae: 0.1151 - root_mean_squared_error: 0.1612 - val_loss: 0.4196 - val_mse: 0.4108 - val_mae: 0.4776 - val_root_mean_squared_error: 0.6410\n", "Epoch 804/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0476 - mse: 0.0388 - mae: 0.1424 - root_mean_squared_error: 0.1970\n", "Epoch 804: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0475 - mse: 0.0387 - mae: 0.1424 - root_mean_squared_error: 0.1968 - val_loss: 0.4269 - val_mse: 0.4181 - val_mae: 0.4935 - val_root_mean_squared_error: 0.6466\n", "Epoch 805/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0435 - mse: 0.0348 - mae: 0.1326 - root_mean_squared_error: 0.1864\n", "Epoch 805: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0436 - mse: 0.0348 - mae: 0.1326 - root_mean_squared_error: 0.1865 - val_loss: 0.4041 - val_mse: 0.3952 - val_mae: 0.4745 - val_root_mean_squared_error: 0.6287\n", "Epoch 806/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0328 - mse: 0.0241 - mae: 0.1109 - root_mean_squared_error: 0.1551\n", "Epoch 806: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 56ms/step - loss: 0.0328 - mse: 0.0241 - mae: 0.1109 - root_mean_squared_error: 0.1551 - val_loss: 0.4252 - val_mse: 0.4164 - val_mae: 0.4782 - val_root_mean_squared_error: 0.6453\n", "Epoch 807/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0340 - mse: 0.0252 - mae: 0.1151 - root_mean_squared_error: 0.1589\n", "Epoch 807: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0339 - mse: 0.0251 - mae: 0.1148 - root_mean_squared_error: 0.1585 - val_loss: 0.4108 - val_mse: 0.4020 - val_mae: 0.4912 - val_root_mean_squared_error: 0.6341\n", "Epoch 808/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0383 - mse: 0.0296 - mae: 0.1236 - root_mean_squared_error: 0.1719\n", "Epoch 808: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0384 - mse: 0.0297 - mae: 0.1239 - root_mean_squared_error: 0.1724 - val_loss: 0.4252 - val_mse: 0.4165 - val_mae: 0.4873 - val_root_mean_squared_error: 0.6454\n", "Epoch 809/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0442 - mse: 0.0355 - mae: 0.1354 - root_mean_squared_error: 0.1883\n", "Epoch 809: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0442 - mse: 0.0355 - mae: 0.1354 - root_mean_squared_error: 0.1883 - val_loss: 0.4356 - val_mse: 0.4269 - val_mae: 0.4945 - val_root_mean_squared_error: 0.6534\n", "Epoch 810/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0388 - mse: 0.0301 - mae: 0.1266 - root_mean_squared_error: 0.1734\n", "Epoch 810: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0388 - mse: 0.0301 - mae: 0.1268 - root_mean_squared_error: 0.1734 - val_loss: 0.4233 - val_mse: 0.4145 - val_mae: 0.4975 - val_root_mean_squared_error: 0.6438\n", "Epoch 811/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0325 - mse: 0.0238 - mae: 0.1072 - root_mean_squared_error: 0.1543\n", "Epoch 811: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0325 - mse: 0.0238 - mae: 0.1072 - root_mean_squared_error: 0.1543 - val_loss: 0.4063 - val_mse: 0.3976 - val_mae: 0.4760 - val_root_mean_squared_error: 0.6305\n", "Epoch 812/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0333 - mse: 0.0246 - mae: 0.1120 - root_mean_squared_error: 0.1568\n", "Epoch 812: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0333 - mse: 0.0246 - mae: 0.1120 - root_mean_squared_error: 0.1568 - val_loss: 0.4014 - val_mse: 0.3927 - val_mae: 0.4718 - val_root_mean_squared_error: 0.6267\n", "Epoch 813/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0353 - mse: 0.0265 - mae: 0.1183 - root_mean_squared_error: 0.1629\n", "Epoch 813: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0352 - mse: 0.0265 - mae: 0.1182 - root_mean_squared_error: 0.1628 - val_loss: 0.4156 - val_mse: 0.4070 - val_mae: 0.4833 - val_root_mean_squared_error: 0.6379\n", "Epoch 814/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0327 - mse: 0.0240 - mae: 0.1148 - root_mean_squared_error: 0.1548\n", "Epoch 814: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0347 - mse: 0.0260 - mae: 0.1159 - root_mean_squared_error: 0.1613 - val_loss: 0.3984 - val_mse: 0.3897 - val_mae: 0.4800 - val_root_mean_squared_error: 0.6243\n", "Epoch 815/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0364 - mse: 0.0278 - mae: 0.1210 - root_mean_squared_error: 0.1666\n", "Epoch 815: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0364 - mse: 0.0278 - mae: 0.1210 - root_mean_squared_error: 0.1666 - val_loss: 0.4139 - val_mse: 0.4053 - val_mae: 0.4818 - val_root_mean_squared_error: 0.6366\n", "Epoch 816/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0339 - mse: 0.0252 - mae: 0.1104 - root_mean_squared_error: 0.1588\n", "Epoch 816: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0337 - mse: 0.0251 - mae: 0.1100 - root_mean_squared_error: 0.1583 - val_loss: 0.4006 - val_mse: 0.3919 - val_mae: 0.4742 - val_root_mean_squared_error: 0.6260\n", "Epoch 817/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0315 - mse: 0.0228 - mae: 0.1082 - root_mean_squared_error: 0.1512\n", "Epoch 817: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0314 - mse: 0.0228 - mae: 0.1081 - root_mean_squared_error: 0.1510 - val_loss: 0.3986 - val_mse: 0.3899 - val_mae: 0.4748 - val_root_mean_squared_error: 0.6244\n", "Epoch 818/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0357 - mse: 0.0270 - mae: 0.1179 - root_mean_squared_error: 0.1645\n", "Epoch 818: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0357 - mse: 0.0270 - mae: 0.1179 - root_mean_squared_error: 0.1645 - val_loss: 0.4258 - val_mse: 0.4171 - val_mae: 0.4896 - val_root_mean_squared_error: 0.6459\n", "Epoch 819/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0443 - mse: 0.0356 - mae: 0.1349 - root_mean_squared_error: 0.1888\n", "Epoch 819: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0443 - mse: 0.0356 - mae: 0.1352 - root_mean_squared_error: 0.1888 - val_loss: 0.4421 - val_mse: 0.4335 - val_mae: 0.5049 - val_root_mean_squared_error: 0.6584\n", "Epoch 820/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0517 - mse: 0.0430 - mae: 0.1463 - root_mean_squared_error: 0.2074\n", "Epoch 820: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0514 - mse: 0.0427 - mae: 0.1459 - root_mean_squared_error: 0.2065 - val_loss: 0.4109 - val_mse: 0.4022 - val_mae: 0.4806 - val_root_mean_squared_error: 0.6342\n", "Epoch 821/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0475 - mse: 0.0388 - mae: 0.1416 - root_mean_squared_error: 0.1969\n", "Epoch 821: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0474 - mse: 0.0386 - mae: 0.1413 - root_mean_squared_error: 0.1965 - val_loss: 0.4331 - val_mse: 0.4244 - val_mae: 0.4881 - val_root_mean_squared_error: 0.6514\n", "Epoch 822/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0342 - mse: 0.0255 - mae: 0.1148 - root_mean_squared_error: 0.1595\n", "Epoch 822: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0341 - mse: 0.0254 - mae: 0.1148 - root_mean_squared_error: 0.1593 - val_loss: 0.4080 - val_mse: 0.3992 - val_mae: 0.4744 - val_root_mean_squared_error: 0.6319\n", "Epoch 823/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0305 - mse: 0.0218 - mae: 0.1049 - root_mean_squared_error: 0.1475\n", "Epoch 823: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0304 - mse: 0.0217 - mae: 0.1047 - root_mean_squared_error: 0.1472 - val_loss: 0.4285 - val_mse: 0.4198 - val_mae: 0.4858 - val_root_mean_squared_error: 0.6479\n", "Epoch 824/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0319 - mse: 0.0232 - mae: 0.1088 - root_mean_squared_error: 0.1524\n", "Epoch 824: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0318 - mse: 0.0232 - mae: 0.1088 - root_mean_squared_error: 0.1522 - val_loss: 0.4021 - val_mse: 0.3934 - val_mae: 0.4709 - val_root_mean_squared_error: 0.6272\n", "Epoch 825/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0329 - mse: 0.0242 - mae: 0.1118 - root_mean_squared_error: 0.1556\n", "Epoch 825: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0329 - mse: 0.0242 - mae: 0.1118 - root_mean_squared_error: 0.1556 - val_loss: 0.4069 - val_mse: 0.3982 - val_mae: 0.4828 - val_root_mean_squared_error: 0.6310\n", "Epoch 826/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0362 - mse: 0.0275 - mae: 0.1160 - root_mean_squared_error: 0.1659\n", "Epoch 826: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0362 - mse: 0.0275 - mae: 0.1160 - root_mean_squared_error: 0.1659 - val_loss: 0.4672 - val_mse: 0.4586 - val_mae: 0.5158 - val_root_mean_squared_error: 0.6772\n", "Epoch 827/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0342 - mse: 0.0255 - mae: 0.1150 - root_mean_squared_error: 0.1598\n", "Epoch 827: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0342 - mse: 0.0255 - mae: 0.1151 - root_mean_squared_error: 0.1598 - val_loss: 0.4267 - val_mse: 0.4180 - val_mae: 0.4872 - val_root_mean_squared_error: 0.6466\n", "Epoch 828/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0394 - mse: 0.0308 - mae: 0.1251 - root_mean_squared_error: 0.1754\n", "Epoch 828: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0394 - mse: 0.0308 - mae: 0.1250 - root_mean_squared_error: 0.1754 - val_loss: 0.4174 - val_mse: 0.4088 - val_mae: 0.4772 - val_root_mean_squared_error: 0.6394\n", "Epoch 829/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0337 - mse: 0.0251 - mae: 0.1124 - root_mean_squared_error: 0.1583\n", "Epoch 829: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0336 - mse: 0.0250 - mae: 0.1124 - root_mean_squared_error: 0.1581 - val_loss: 0.4226 - val_mse: 0.4140 - val_mae: 0.4853 - val_root_mean_squared_error: 0.6434\n", "Epoch 830/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0409 - mse: 0.0323 - mae: 0.1326 - root_mean_squared_error: 0.1797\n", "Epoch 830: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 50ms/step - loss: 0.0411 - mse: 0.0325 - mae: 0.1330 - root_mean_squared_error: 0.1803 - val_loss: 0.4192 - val_mse: 0.4106 - val_mae: 0.4831 - val_root_mean_squared_error: 0.6408\n", "Epoch 831/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0456 - mse: 0.0370 - mae: 0.1381 - root_mean_squared_error: 0.1924\n", "Epoch 831: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0456 - mse: 0.0370 - mae: 0.1381 - root_mean_squared_error: 0.1924 - val_loss: 0.4088 - val_mse: 0.4001 - val_mae: 0.4786 - val_root_mean_squared_error: 0.6325\n", "Epoch 832/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0384 - mse: 0.0297 - mae: 0.1244 - root_mean_squared_error: 0.1723\n", "Epoch 832: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0384 - mse: 0.0297 - mae: 0.1242 - root_mean_squared_error: 0.1723 - val_loss: 0.4017 - val_mse: 0.3930 - val_mae: 0.4767 - val_root_mean_squared_error: 0.6269\n", "Epoch 833/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0359 - mse: 0.0273 - mae: 0.1169 - root_mean_squared_error: 0.1651\n", "Epoch 833: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 35ms/step - loss: 0.0358 - mse: 0.0271 - mae: 0.1167 - root_mean_squared_error: 0.1648 - val_loss: 0.4169 - val_mse: 0.4082 - val_mae: 0.4831 - val_root_mean_squared_error: 0.6389\n", "Epoch 834/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0511 - mse: 0.0424 - mae: 0.1526 - root_mean_squared_error: 0.2060\n", "Epoch 834: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0512 - mse: 0.0425 - mae: 0.1529 - root_mean_squared_error: 0.2063 - val_loss: 0.3977 - val_mse: 0.3890 - val_mae: 0.4751 - val_root_mean_squared_error: 0.6237\n", "Epoch 835/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0486 - mse: 0.0399 - mae: 0.1450 - root_mean_squared_error: 0.1997\n", "Epoch 835: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0482 - mse: 0.0394 - mae: 0.1443 - root_mean_squared_error: 0.1986 - val_loss: 0.4012 - val_mse: 0.3925 - val_mae: 0.4752 - val_root_mean_squared_error: 0.6265\n", "Epoch 836/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0399 - mse: 0.0312 - mae: 0.1274 - root_mean_squared_error: 0.1766\n", "Epoch 836: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0399 - mse: 0.0312 - mae: 0.1274 - root_mean_squared_error: 0.1766 - val_loss: 0.4212 - val_mse: 0.4125 - val_mae: 0.4794 - val_root_mean_squared_error: 0.6423\n", "Epoch 837/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0379 - mse: 0.0292 - mae: 0.1199 - root_mean_squared_error: 0.1709\n", "Epoch 837: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0379 - mse: 0.0292 - mae: 0.1199 - root_mean_squared_error: 0.1709 - val_loss: 0.4120 - val_mse: 0.4033 - val_mae: 0.4748 - val_root_mean_squared_error: 0.6350\n", "Epoch 838/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0439 - mse: 0.0352 - mae: 0.1320 - root_mean_squared_error: 0.1876\n", "Epoch 838: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0437 - mse: 0.0350 - mae: 0.1316 - root_mean_squared_error: 0.1871 - val_loss: 0.4073 - val_mse: 0.3986 - val_mae: 0.4716 - val_root_mean_squared_error: 0.6313\n", "Epoch 839/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0327 - mse: 0.0240 - mae: 0.1123 - root_mean_squared_error: 0.1550\n", "Epoch 839: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0327 - mse: 0.0240 - mae: 0.1123 - root_mean_squared_error: 0.1550 - val_loss: 0.4036 - val_mse: 0.3949 - val_mae: 0.4703 - val_root_mean_squared_error: 0.6284\n", "Epoch 840/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0320 - mse: 0.0233 - mae: 0.1098 - root_mean_squared_error: 0.1527\n", "Epoch 840: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0319 - mse: 0.0233 - mae: 0.1096 - root_mean_squared_error: 0.1526 - val_loss: 0.4063 - val_mse: 0.3977 - val_mae: 0.4725 - val_root_mean_squared_error: 0.6306\n", "Epoch 841/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0364 - mse: 0.0278 - mae: 0.1205 - root_mean_squared_error: 0.1667\n", "Epoch 841: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0364 - mse: 0.0278 - mae: 0.1205 - root_mean_squared_error: 0.1667 - val_loss: 0.3935 - val_mse: 0.3849 - val_mae: 0.4672 - val_root_mean_squared_error: 0.6204\n", "Epoch 842/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0355 - mse: 0.0269 - mae: 0.1154 - root_mean_squared_error: 0.1639\n", "Epoch 842: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0355 - mse: 0.0269 - mae: 0.1154 - root_mean_squared_error: 0.1639 - val_loss: 0.4223 - val_mse: 0.4137 - val_mae: 0.4874 - val_root_mean_squared_error: 0.6432\n", "Epoch 843/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0368 - mse: 0.0282 - mae: 0.1193 - root_mean_squared_error: 0.1679\n", "Epoch 843: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 57ms/step - loss: 0.0369 - mse: 0.0283 - mae: 0.1194 - root_mean_squared_error: 0.1683 - val_loss: 0.4167 - val_mse: 0.4081 - val_mae: 0.4868 - val_root_mean_squared_error: 0.6388\n", "Epoch 844/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0330 - mse: 0.0243 - mae: 0.1131 - root_mean_squared_error: 0.1560\n", "Epoch 844: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0330 - mse: 0.0243 - mae: 0.1131 - root_mean_squared_error: 0.1560 - val_loss: 0.3986 - val_mse: 0.3900 - val_mae: 0.4788 - val_root_mean_squared_error: 0.6245\n", "Epoch 845/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0361 - mse: 0.0275 - mae: 0.1178 - root_mean_squared_error: 0.1659\n", "Epoch 845: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0360 - mse: 0.0274 - mae: 0.1174 - root_mean_squared_error: 0.1654 - val_loss: 0.4073 - val_mse: 0.3987 - val_mae: 0.4752 - val_root_mean_squared_error: 0.6315\n", "Epoch 846/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0328 - mse: 0.0242 - mae: 0.1122 - root_mean_squared_error: 0.1555\n", "Epoch 846: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0325 - mse: 0.0239 - mae: 0.1116 - root_mean_squared_error: 0.1545 - val_loss: 0.4082 - val_mse: 0.3996 - val_mae: 0.4830 - val_root_mean_squared_error: 0.6322\n", "Epoch 847/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0370 - mse: 0.0284 - mae: 0.1180 - root_mean_squared_error: 0.1685\n", "Epoch 847: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0369 - mse: 0.0284 - mae: 0.1181 - root_mean_squared_error: 0.1684 - val_loss: 0.4096 - val_mse: 0.4010 - val_mae: 0.4790 - val_root_mean_squared_error: 0.6333\n", "Epoch 848/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0342 - mse: 0.0256 - mae: 0.1144 - root_mean_squared_error: 0.1599\n", "Epoch 848: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0342 - mse: 0.0256 - mae: 0.1144 - root_mean_squared_error: 0.1599 - val_loss: 0.4168 - val_mse: 0.4082 - val_mae: 0.4788 - val_root_mean_squared_error: 0.6389\n", "Epoch 849/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0364 - mse: 0.0278 - mae: 0.1168 - root_mean_squared_error: 0.1668\n", "Epoch 849: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0366 - mse: 0.0280 - mae: 0.1174 - root_mean_squared_error: 0.1675 - val_loss: 0.4283 - val_mse: 0.4198 - val_mae: 0.4880 - val_root_mean_squared_error: 0.6479\n", "Epoch 850/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0404 - mse: 0.0319 - mae: 0.1274 - root_mean_squared_error: 0.1785\n", "Epoch 850: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0404 - mse: 0.0319 - mae: 0.1274 - root_mean_squared_error: 0.1785 - val_loss: 0.4177 - val_mse: 0.4092 - val_mae: 0.4873 - val_root_mean_squared_error: 0.6397\n", "Epoch 851/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0406 - mse: 0.0320 - mae: 0.1286 - root_mean_squared_error: 0.1789\n", "Epoch 851: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0404 - mse: 0.0318 - mae: 0.1283 - root_mean_squared_error: 0.1784 - val_loss: 0.4107 - val_mse: 0.4021 - val_mae: 0.4747 - val_root_mean_squared_error: 0.6342\n", "Epoch 852/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0405 - mse: 0.0320 - mae: 0.1323 - root_mean_squared_error: 0.1788\n", "Epoch 852: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0405 - mse: 0.0320 - mae: 0.1323 - root_mean_squared_error: 0.1788 - val_loss: 0.4354 - val_mse: 0.4268 - val_mae: 0.5009 - val_root_mean_squared_error: 0.6533\n", "Epoch 853/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0378 - mse: 0.0292 - mae: 0.1214 - root_mean_squared_error: 0.1710\n", "Epoch 853: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0377 - mse: 0.0291 - mae: 0.1212 - root_mean_squared_error: 0.1707 - val_loss: 0.4049 - val_mse: 0.3963 - val_mae: 0.4797 - val_root_mean_squared_error: 0.6295\n", "Epoch 854/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0357 - mse: 0.0272 - mae: 0.1187 - root_mean_squared_error: 0.1648\n", "Epoch 854: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0357 - mse: 0.0272 - mae: 0.1187 - root_mean_squared_error: 0.1648 - val_loss: 0.4131 - val_mse: 0.4045 - val_mae: 0.4884 - val_root_mean_squared_error: 0.6360\n", "Epoch 855/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0416 - mse: 0.0330 - mae: 0.1337 - root_mean_squared_error: 0.1817\n", "Epoch 855: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0416 - mse: 0.0330 - mae: 0.1337 - root_mean_squared_error: 0.1817 - val_loss: 0.4186 - val_mse: 0.4100 - val_mae: 0.4761 - val_root_mean_squared_error: 0.6403\n", "Epoch 856/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0376 - mse: 0.0290 - mae: 0.1211 - root_mean_squared_error: 0.1703\n", "Epoch 856: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0375 - mse: 0.0289 - mae: 0.1211 - root_mean_squared_error: 0.1701 - val_loss: 0.4194 - val_mse: 0.4108 - val_mae: 0.4910 - val_root_mean_squared_error: 0.6410\n", "Epoch 857/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0359 - mse: 0.0274 - mae: 0.1185 - root_mean_squared_error: 0.1654\n", "Epoch 857: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0360 - mse: 0.0275 - mae: 0.1189 - root_mean_squared_error: 0.1657 - val_loss: 0.4003 - val_mse: 0.3918 - val_mae: 0.4804 - val_root_mean_squared_error: 0.6259\n", "Epoch 858/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0374 - mse: 0.0289 - mae: 0.1233 - root_mean_squared_error: 0.1699\n", "Epoch 858: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0374 - mse: 0.0289 - mae: 0.1233 - root_mean_squared_error: 0.1699 - val_loss: 0.4126 - val_mse: 0.4041 - val_mae: 0.4884 - val_root_mean_squared_error: 0.6357\n", "Epoch 859/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0404 - mse: 0.0318 - mae: 0.1296 - root_mean_squared_error: 0.1784\n", "Epoch 859: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0406 - mse: 0.0320 - mae: 0.1300 - root_mean_squared_error: 0.1789 - val_loss: 0.4152 - val_mse: 0.4065 - val_mae: 0.4879 - val_root_mean_squared_error: 0.6376\n", "Epoch 860/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0401 - mse: 0.0315 - mae: 0.1266 - root_mean_squared_error: 0.1774\n", "Epoch 860: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0402 - mse: 0.0316 - mae: 0.1272 - root_mean_squared_error: 0.1778 - val_loss: 0.4165 - val_mse: 0.4079 - val_mae: 0.4816 - val_root_mean_squared_error: 0.6386\n", "Epoch 861/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0430 - mse: 0.0344 - mae: 0.1326 - root_mean_squared_error: 0.1856\n", "Epoch 861: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0430 - mse: 0.0344 - mae: 0.1326 - root_mean_squared_error: 0.1856 - val_loss: 0.4112 - val_mse: 0.4026 - val_mae: 0.4822 - val_root_mean_squared_error: 0.6345\n", "Epoch 862/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0347 - mse: 0.0261 - mae: 0.1170 - root_mean_squared_error: 0.1615\n", "Epoch 862: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0346 - mse: 0.0260 - mae: 0.1165 - root_mean_squared_error: 0.1612 - val_loss: 0.3980 - val_mse: 0.3894 - val_mae: 0.4735 - val_root_mean_squared_error: 0.6240\n", "Epoch 863/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0359 - mse: 0.0273 - mae: 0.1192 - root_mean_squared_error: 0.1652\n", "Epoch 863: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0358 - mse: 0.0272 - mae: 0.1190 - root_mean_squared_error: 0.1648 - val_loss: 0.4363 - val_mse: 0.4277 - val_mae: 0.4974 - val_root_mean_squared_error: 0.6540\n", "Epoch 864/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0360 - mse: 0.0274 - mae: 0.1183 - root_mean_squared_error: 0.1655\n", "Epoch 864: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 60ms/step - loss: 0.0360 - mse: 0.0274 - mae: 0.1183 - root_mean_squared_error: 0.1655 - val_loss: 0.4101 - val_mse: 0.4015 - val_mae: 0.4775 - val_root_mean_squared_error: 0.6336\n", "Epoch 865/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0367 - mse: 0.0281 - mae: 0.1195 - root_mean_squared_error: 0.1676\n", "Epoch 865: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0367 - mse: 0.0281 - mae: 0.1197 - root_mean_squared_error: 0.1675 - val_loss: 0.4166 - val_mse: 0.4080 - val_mae: 0.4805 - val_root_mean_squared_error: 0.6388\n", "Epoch 866/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0397 - mse: 0.0311 - mae: 0.1264 - root_mean_squared_error: 0.1763\n", "Epoch 866: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0398 - mse: 0.0312 - mae: 0.1270 - root_mean_squared_error: 0.1767 - val_loss: 0.4241 - val_mse: 0.4155 - val_mae: 0.4930 - val_root_mean_squared_error: 0.6446\n", "Epoch 867/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0365 - mse: 0.0279 - mae: 0.1188 - root_mean_squared_error: 0.1672\n", "Epoch 867: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0367 - mse: 0.0281 - mae: 0.1195 - root_mean_squared_error: 0.1677 - val_loss: 0.4154 - val_mse: 0.4068 - val_mae: 0.4877 - val_root_mean_squared_error: 0.6378\n", "Epoch 868/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0364 - mse: 0.0279 - mae: 0.1208 - root_mean_squared_error: 0.1669\n", "Epoch 868: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0368 - mse: 0.0282 - mae: 0.1216 - root_mean_squared_error: 0.1680 - val_loss: 0.4154 - val_mse: 0.4068 - val_mae: 0.4830 - val_root_mean_squared_error: 0.6378\n", "Epoch 869/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0374 - mse: 0.0289 - mae: 0.1264 - root_mean_squared_error: 0.1699\n", "Epoch 869: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0374 - mse: 0.0288 - mae: 0.1263 - root_mean_squared_error: 0.1698 - val_loss: 0.4074 - val_mse: 0.3988 - val_mae: 0.4774 - val_root_mean_squared_error: 0.6315\n", "Epoch 870/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0374 - mse: 0.0288 - mae: 0.1208 - root_mean_squared_error: 0.1696\n", "Epoch 870: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0374 - mse: 0.0288 - mae: 0.1212 - root_mean_squared_error: 0.1698 - val_loss: 0.4256 - val_mse: 0.4170 - val_mae: 0.4860 - val_root_mean_squared_error: 0.6458\n", "Epoch 871/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0345 - mse: 0.0260 - mae: 0.1139 - root_mean_squared_error: 0.1611\n", "Epoch 871: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0345 - mse: 0.0260 - mae: 0.1139 - root_mean_squared_error: 0.1611 - val_loss: 0.4143 - val_mse: 0.4057 - val_mae: 0.4763 - val_root_mean_squared_error: 0.6370\n", "Epoch 872/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0329 - mse: 0.0243 - mae: 0.1122 - root_mean_squared_error: 0.1560\n", "Epoch 872: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0328 - mse: 0.0242 - mae: 0.1119 - root_mean_squared_error: 0.1556 - val_loss: 0.4081 - val_mse: 0.3996 - val_mae: 0.4834 - val_root_mean_squared_error: 0.6321\n", "Epoch 873/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0367 - mse: 0.0282 - mae: 0.1210 - root_mean_squared_error: 0.1679\n", "Epoch 873: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0367 - mse: 0.0281 - mae: 0.1210 - root_mean_squared_error: 0.1678 - val_loss: 0.3945 - val_mse: 0.3860 - val_mae: 0.4726 - val_root_mean_squared_error: 0.6213\n", "Epoch 874/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0412 - mse: 0.0326 - mae: 0.1270 - root_mean_squared_error: 0.1806\n", "Epoch 874: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0414 - mse: 0.0328 - mae: 0.1274 - root_mean_squared_error: 0.1811 - val_loss: 0.3826 - val_mse: 0.3741 - val_mae: 0.4644 - val_root_mean_squared_error: 0.6116\n", "Epoch 875/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0379 - mse: 0.0293 - mae: 0.1231 - root_mean_squared_error: 0.1712\n", "Epoch 875: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0379 - mse: 0.0293 - mae: 0.1231 - root_mean_squared_error: 0.1712 - val_loss: 0.4326 - val_mse: 0.4241 - val_mae: 0.4917 - val_root_mean_squared_error: 0.6512\n", "Epoch 876/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0359 - mse: 0.0274 - mae: 0.1201 - root_mean_squared_error: 0.1655\n", "Epoch 876: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0359 - mse: 0.0274 - mae: 0.1201 - root_mean_squared_error: 0.1655 - val_loss: 0.4107 - val_mse: 0.4021 - val_mae: 0.4866 - val_root_mean_squared_error: 0.6342\n", "Epoch 877/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0335 - mse: 0.0249 - mae: 0.1116 - root_mean_squared_error: 0.1579\n", "Epoch 877: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0335 - mse: 0.0249 - mae: 0.1116 - root_mean_squared_error: 0.1579 - val_loss: 0.3945 - val_mse: 0.3859 - val_mae: 0.4763 - val_root_mean_squared_error: 0.6212\n", "Epoch 878/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0376 - mse: 0.0290 - mae: 0.1227 - root_mean_squared_error: 0.1704\n", "Epoch 878: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0376 - mse: 0.0290 - mae: 0.1226 - root_mean_squared_error: 0.1704 - val_loss: 0.4060 - val_mse: 0.3975 - val_mae: 0.4772 - val_root_mean_squared_error: 0.6305\n", "Epoch 879/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0425 - mse: 0.0339 - mae: 0.1338 - root_mean_squared_error: 0.1842\n", "Epoch 879: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0424 - mse: 0.0339 - mae: 0.1337 - root_mean_squared_error: 0.1840 - val_loss: 0.3948 - val_mse: 0.3863 - val_mae: 0.4738 - val_root_mean_squared_error: 0.6215\n", "Epoch 880/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0389 - mse: 0.0304 - mae: 0.1228 - root_mean_squared_error: 0.1742\n", "Epoch 880: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0389 - mse: 0.0304 - mae: 0.1228 - root_mean_squared_error: 0.1742 - val_loss: 0.4117 - val_mse: 0.4032 - val_mae: 0.4788 - val_root_mean_squared_error: 0.6350\n", "Epoch 881/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0377 - mse: 0.0292 - mae: 0.1210 - root_mean_squared_error: 0.1708\n", "Epoch 881: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0377 - mse: 0.0292 - mae: 0.1213 - root_mean_squared_error: 0.1709 - val_loss: 0.3971 - val_mse: 0.3886 - val_mae: 0.4703 - val_root_mean_squared_error: 0.6234\n", "Epoch 882/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0327 - mse: 0.0242 - mae: 0.1104 - root_mean_squared_error: 0.1555\n", "Epoch 882: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0327 - mse: 0.0242 - mae: 0.1104 - root_mean_squared_error: 0.1555 - val_loss: 0.4017 - val_mse: 0.3932 - val_mae: 0.4717 - val_root_mean_squared_error: 0.6271\n", "Epoch 883/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0419 - mse: 0.0334 - mae: 0.1312 - root_mean_squared_error: 0.1827\n", "Epoch 883: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0419 - mse: 0.0334 - mae: 0.1312 - root_mean_squared_error: 0.1827 - val_loss: 0.4119 - val_mse: 0.4034 - val_mae: 0.4784 - val_root_mean_squared_error: 0.6351\n", "Epoch 884/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0414 - mse: 0.0328 - mae: 0.1327 - root_mean_squared_error: 0.1812\n", "Epoch 884: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0413 - mse: 0.0327 - mae: 0.1326 - root_mean_squared_error: 0.1809 - val_loss: 0.4175 - val_mse: 0.4089 - val_mae: 0.4808 - val_root_mean_squared_error: 0.6395\n", "Epoch 885/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0338 - mse: 0.0252 - mae: 0.1157 - root_mean_squared_error: 0.1588\n", "Epoch 885: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 0.0337 - mse: 0.0251 - mae: 0.1154 - root_mean_squared_error: 0.1584 - val_loss: 0.3969 - val_mse: 0.3883 - val_mae: 0.4718 - val_root_mean_squared_error: 0.6232\n", "Epoch 886/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0350 - mse: 0.0264 - mae: 0.1165 - root_mean_squared_error: 0.1626\n", "Epoch 886: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0349 - mse: 0.0263 - mae: 0.1162 - root_mean_squared_error: 0.1622 - val_loss: 0.3795 - val_mse: 0.3710 - val_mae: 0.4664 - val_root_mean_squared_error: 0.6091\n", "Epoch 887/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0334 - mse: 0.0248 - mae: 0.1134 - root_mean_squared_error: 0.1576\n", "Epoch 887: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0334 - mse: 0.0248 - mae: 0.1134 - root_mean_squared_error: 0.1576 - val_loss: 0.4126 - val_mse: 0.4040 - val_mae: 0.4807 - val_root_mean_squared_error: 0.6356\n", "Epoch 888/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0375 - mse: 0.0289 - mae: 0.1245 - root_mean_squared_error: 0.1701\n", "Epoch 888: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0375 - mse: 0.0289 - mae: 0.1245 - root_mean_squared_error: 0.1701 - val_loss: 0.4004 - val_mse: 0.3919 - val_mae: 0.4668 - val_root_mean_squared_error: 0.6260\n", "Epoch 889/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0316 - mse: 0.0231 - mae: 0.1121 - root_mean_squared_error: 0.1519\n", "Epoch 889: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0315 - mse: 0.0230 - mae: 0.1121 - root_mean_squared_error: 0.1518 - val_loss: 0.4095 - val_mse: 0.4010 - val_mae: 0.4824 - val_root_mean_squared_error: 0.6332\n", "Epoch 890/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0398 - mse: 0.0313 - mae: 0.1230 - root_mean_squared_error: 0.1770\n", "Epoch 890: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0396 - mse: 0.0311 - mae: 0.1225 - root_mean_squared_error: 0.1764 - val_loss: 0.4104 - val_mse: 0.4019 - val_mae: 0.4782 - val_root_mean_squared_error: 0.6339\n", "Epoch 891/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0348 - mse: 0.0263 - mae: 0.1154 - root_mean_squared_error: 0.1622\n", "Epoch 891: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0348 - mse: 0.0263 - mae: 0.1154 - root_mean_squared_error: 0.1622 - val_loss: 0.3870 - val_mse: 0.3786 - val_mae: 0.4660 - val_root_mean_squared_error: 0.6153\n", "Epoch 892/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0369 - mse: 0.0284 - mae: 0.1211 - root_mean_squared_error: 0.1684\n", "Epoch 892: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0369 - mse: 0.0284 - mae: 0.1211 - root_mean_squared_error: 0.1684 - val_loss: 0.4466 - val_mse: 0.4381 - val_mae: 0.5025 - val_root_mean_squared_error: 0.6619\n", "Epoch 893/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0427 - mse: 0.0343 - mae: 0.1349 - root_mean_squared_error: 0.1851\n", "Epoch 893: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0427 - mse: 0.0343 - mae: 0.1349 - root_mean_squared_error: 0.1851 - val_loss: 0.4420 - val_mse: 0.4335 - val_mae: 0.5058 - val_root_mean_squared_error: 0.6584\n", "Epoch 894/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0365 - mse: 0.0279 - mae: 0.1181 - root_mean_squared_error: 0.1672\n", "Epoch 894: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0365 - mse: 0.0279 - mae: 0.1181 - root_mean_squared_error: 0.1672 - val_loss: 0.4085 - val_mse: 0.4000 - val_mae: 0.4793 - val_root_mean_squared_error: 0.6325\n", "Epoch 895/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0357 - mse: 0.0272 - mae: 0.1147 - root_mean_squared_error: 0.1648\n", "Epoch 895: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0354 - mse: 0.0269 - mae: 0.1146 - root_mean_squared_error: 0.1641 - val_loss: 0.4108 - val_mse: 0.4023 - val_mae: 0.4784 - val_root_mean_squared_error: 0.6342\n", "Epoch 896/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0332 - mse: 0.0248 - mae: 0.1122 - root_mean_squared_error: 0.1573\n", "Epoch 896: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0332 - mse: 0.0248 - mae: 0.1122 - root_mean_squared_error: 0.1573 - val_loss: 0.4129 - val_mse: 0.4044 - val_mae: 0.4781 - val_root_mean_squared_error: 0.6359\n", "Epoch 897/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0385 - mse: 0.0300 - mae: 0.1241 - root_mean_squared_error: 0.1733\n", "Epoch 897: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0383 - mse: 0.0299 - mae: 0.1240 - root_mean_squared_error: 0.1728 - val_loss: 0.4150 - val_mse: 0.4065 - val_mae: 0.4893 - val_root_mean_squared_error: 0.6376\n", "Epoch 898/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0373 - mse: 0.0288 - mae: 0.1201 - root_mean_squared_error: 0.1696\n", "Epoch 898: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0373 - mse: 0.0288 - mae: 0.1201 - root_mean_squared_error: 0.1696 - val_loss: 0.4306 - val_mse: 0.4221 - val_mae: 0.4885 - val_root_mean_squared_error: 0.6497\n", "Epoch 899/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0358 - mse: 0.0273 - mae: 0.1191 - root_mean_squared_error: 0.1652\n", "Epoch 899: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0359 - mse: 0.0274 - mae: 0.1195 - root_mean_squared_error: 0.1655 - val_loss: 0.4175 - val_mse: 0.4091 - val_mae: 0.4852 - val_root_mean_squared_error: 0.6396\n", "Epoch 900/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0375 - mse: 0.0291 - mae: 0.1224 - root_mean_squared_error: 0.1705\n", "Epoch 900: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0376 - mse: 0.0291 - mae: 0.1227 - root_mean_squared_error: 0.1706 - val_loss: 0.4075 - val_mse: 0.3990 - val_mae: 0.4821 - val_root_mean_squared_error: 0.6317\n", "Epoch 901/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0437 - mse: 0.0352 - mae: 0.1345 - root_mean_squared_error: 0.1876\n", "Epoch 901: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0437 - mse: 0.0352 - mae: 0.1345 - root_mean_squared_error: 0.1876 - val_loss: 0.4066 - val_mse: 0.3981 - val_mae: 0.4792 - val_root_mean_squared_error: 0.6310\n", "Epoch 902/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0371 - mse: 0.0286 - mae: 0.1211 - root_mean_squared_error: 0.1692\n", "Epoch 902: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 5s 66ms/step - loss: 0.0371 - mse: 0.0286 - mae: 0.1211 - root_mean_squared_error: 0.1692 - val_loss: 0.4134 - val_mse: 0.4049 - val_mae: 0.4786 - val_root_mean_squared_error: 0.6363\n", "Epoch 903/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0445 - mse: 0.0360 - mae: 0.1343 - root_mean_squared_error: 0.1898\n", "Epoch 903: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0445 - mse: 0.0360 - mae: 0.1343 - root_mean_squared_error: 0.1898 - val_loss: 0.4141 - val_mse: 0.4055 - val_mae: 0.4795 - val_root_mean_squared_error: 0.6368\n", "Epoch 904/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0368 - mse: 0.0283 - mae: 0.1201 - root_mean_squared_error: 0.1681\n", "Epoch 904: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0368 - mse: 0.0283 - mae: 0.1201 - root_mean_squared_error: 0.1681 - val_loss: 0.3936 - val_mse: 0.3851 - val_mae: 0.4718 - val_root_mean_squared_error: 0.6205\n", "Epoch 905/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0395 - mse: 0.0310 - mae: 0.1262 - root_mean_squared_error: 0.1762\n", "Epoch 905: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0394 - mse: 0.0309 - mae: 0.1261 - root_mean_squared_error: 0.1758 - val_loss: 0.4036 - val_mse: 0.3951 - val_mae: 0.4734 - val_root_mean_squared_error: 0.6285\n", "Epoch 906/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0349 - mse: 0.0264 - mae: 0.1163 - root_mean_squared_error: 0.1626\n", "Epoch 906: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0349 - mse: 0.0264 - mae: 0.1163 - root_mean_squared_error: 0.1626 - val_loss: 0.4188 - val_mse: 0.4103 - val_mae: 0.4858 - val_root_mean_squared_error: 0.6405\n", "Epoch 907/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0338 - mse: 0.0253 - mae: 0.1170 - root_mean_squared_error: 0.1591\n", "Epoch 907: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0339 - mse: 0.0254 - mae: 0.1173 - root_mean_squared_error: 0.1594 - val_loss: 0.4166 - val_mse: 0.4081 - val_mae: 0.4844 - val_root_mean_squared_error: 0.6388\n", "Epoch 908/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0429 - mse: 0.0344 - mae: 0.1310 - root_mean_squared_error: 0.1853\n", "Epoch 908: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0428 - mse: 0.0343 - mae: 0.1309 - root_mean_squared_error: 0.1851 - val_loss: 0.4060 - val_mse: 0.3975 - val_mae: 0.4765 - val_root_mean_squared_error: 0.6305\n", "Epoch 909/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0325 - mse: 0.0240 - mae: 0.1127 - root_mean_squared_error: 0.1551\n", "Epoch 909: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0325 - mse: 0.0240 - mae: 0.1127 - root_mean_squared_error: 0.1551 - val_loss: 0.4332 - val_mse: 0.4247 - val_mae: 0.4913 - val_root_mean_squared_error: 0.6517\n", "Epoch 910/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0342 - mse: 0.0257 - mae: 0.1145 - root_mean_squared_error: 0.1603\n", "Epoch 910: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0342 - mse: 0.0257 - mae: 0.1145 - root_mean_squared_error: 0.1603 - val_loss: 0.4320 - val_mse: 0.4236 - val_mae: 0.4868 - val_root_mean_squared_error: 0.6508\n", "Epoch 911/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0327 - mse: 0.0242 - mae: 0.1118 - root_mean_squared_error: 0.1555\n", "Epoch 911: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0329 - mse: 0.0244 - mae: 0.1121 - root_mean_squared_error: 0.1561 - val_loss: 0.4137 - val_mse: 0.4052 - val_mae: 0.4784 - val_root_mean_squared_error: 0.6366\n", "Epoch 912/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0481 - mse: 0.0396 - mae: 0.1403 - root_mean_squared_error: 0.1990\n", "Epoch 912: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0481 - mse: 0.0396 - mae: 0.1403 - root_mean_squared_error: 0.1990 - val_loss: 0.4170 - val_mse: 0.4085 - val_mae: 0.4793 - val_root_mean_squared_error: 0.6391\n", "Epoch 913/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0420 - mse: 0.0335 - mae: 0.1313 - root_mean_squared_error: 0.1829\n", "Epoch 913: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0418 - mse: 0.0333 - mae: 0.1310 - root_mean_squared_error: 0.1825 - val_loss: 0.4080 - val_mse: 0.3995 - val_mae: 0.4802 - val_root_mean_squared_error: 0.6321\n", "Epoch 914/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0364 - mse: 0.0279 - mae: 0.1188 - root_mean_squared_error: 0.1671\n", "Epoch 914: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0364 - mse: 0.0279 - mae: 0.1188 - root_mean_squared_error: 0.1671 - val_loss: 0.4072 - val_mse: 0.3987 - val_mae: 0.4836 - val_root_mean_squared_error: 0.6314\n", "Epoch 915/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0373 - mse: 0.0289 - mae: 0.1187 - root_mean_squared_error: 0.1699\n", "Epoch 915: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0373 - mse: 0.0288 - mae: 0.1184 - root_mean_squared_error: 0.1698 - val_loss: 0.4033 - val_mse: 0.3948 - val_mae: 0.4710 - val_root_mean_squared_error: 0.6283\n", "Epoch 916/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0451 - mse: 0.0366 - mae: 0.1355 - root_mean_squared_error: 0.1914\n", "Epoch 916: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0450 - mse: 0.0365 - mae: 0.1355 - root_mean_squared_error: 0.1910 - val_loss: 0.4184 - val_mse: 0.4099 - val_mae: 0.4861 - val_root_mean_squared_error: 0.6403\n", "Epoch 917/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0392 - mse: 0.0307 - mae: 0.1278 - root_mean_squared_error: 0.1753\n", "Epoch 917: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0393 - mse: 0.0308 - mae: 0.1279 - root_mean_squared_error: 0.1754 - val_loss: 0.4313 - val_mse: 0.4227 - val_mae: 0.4900 - val_root_mean_squared_error: 0.6502\n", "Epoch 918/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0379 - mse: 0.0294 - mae: 0.1224 - root_mean_squared_error: 0.1716\n", "Epoch 918: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0379 - mse: 0.0294 - mae: 0.1224 - root_mean_squared_error: 0.1716 - val_loss: 0.4032 - val_mse: 0.3947 - val_mae: 0.4753 - val_root_mean_squared_error: 0.6282\n", "Epoch 919/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0374 - mse: 0.0289 - mae: 0.1241 - root_mean_squared_error: 0.1701\n", "Epoch 919: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0374 - mse: 0.0289 - mae: 0.1241 - root_mean_squared_error: 0.1700 - val_loss: 0.4172 - val_mse: 0.4088 - val_mae: 0.4794 - val_root_mean_squared_error: 0.6393\n", "Epoch 920/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0418 - mse: 0.0333 - mae: 0.1309 - root_mean_squared_error: 0.1825\n", "Epoch 920: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0418 - mse: 0.0333 - mae: 0.1309 - root_mean_squared_error: 0.1825 - val_loss: 0.4081 - val_mse: 0.3996 - val_mae: 0.4790 - val_root_mean_squared_error: 0.6322\n", "Epoch 921/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0325 - mse: 0.0240 - mae: 0.1129 - root_mean_squared_error: 0.1549\n", "Epoch 921: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0325 - mse: 0.0240 - mae: 0.1130 - root_mean_squared_error: 0.1549 - val_loss: 0.4266 - val_mse: 0.4181 - val_mae: 0.4857 - val_root_mean_squared_error: 0.6466\n", "Epoch 922/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0398 - mse: 0.0313 - mae: 0.1278 - root_mean_squared_error: 0.1770\n", "Epoch 922: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 52ms/step - loss: 0.0398 - mse: 0.0313 - mae: 0.1278 - root_mean_squared_error: 0.1770 - val_loss: 0.3883 - val_mse: 0.3799 - val_mae: 0.4676 - val_root_mean_squared_error: 0.6163\n", "Epoch 923/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0373 - mse: 0.0289 - mae: 0.1250 - root_mean_squared_error: 0.1700\n", "Epoch 923: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0372 - mse: 0.0288 - mae: 0.1247 - root_mean_squared_error: 0.1696 - val_loss: 0.4212 - val_mse: 0.4127 - val_mae: 0.4806 - val_root_mean_squared_error: 0.6424\n", "Epoch 924/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0346 - mse: 0.0262 - mae: 0.1194 - root_mean_squared_error: 0.1619\n", "Epoch 924: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0347 - mse: 0.0263 - mae: 0.1197 - root_mean_squared_error: 0.1620 - val_loss: 0.3916 - val_mse: 0.3832 - val_mae: 0.4720 - val_root_mean_squared_error: 0.6190\n", "Epoch 925/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0328 - mse: 0.0244 - mae: 0.1110 - root_mean_squared_error: 0.1561\n", "Epoch 925: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0328 - mse: 0.0244 - mae: 0.1110 - root_mean_squared_error: 0.1561 - val_loss: 0.4127 - val_mse: 0.4043 - val_mae: 0.4772 - val_root_mean_squared_error: 0.6359\n", "Epoch 926/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0398 - mse: 0.0314 - mae: 0.1268 - root_mean_squared_error: 0.1773\n", "Epoch 926: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0398 - mse: 0.0314 - mae: 0.1268 - root_mean_squared_error: 0.1773 - val_loss: 0.4114 - val_mse: 0.4030 - val_mae: 0.4794 - val_root_mean_squared_error: 0.6348\n", "Epoch 927/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0323 - mse: 0.0239 - mae: 0.1098 - root_mean_squared_error: 0.1545\n", "Epoch 927: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0324 - mse: 0.0240 - mae: 0.1101 - root_mean_squared_error: 0.1549 - val_loss: 0.4126 - val_mse: 0.4042 - val_mae: 0.4814 - val_root_mean_squared_error: 0.6358\n", "Epoch 928/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0375 - mse: 0.0291 - mae: 0.1210 - root_mean_squared_error: 0.1706\n", "Epoch 928: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0374 - mse: 0.0290 - mae: 0.1207 - root_mean_squared_error: 0.1702 - val_loss: 0.3995 - val_mse: 0.3911 - val_mae: 0.4754 - val_root_mean_squared_error: 0.6254\n", "Epoch 929/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0340 - mse: 0.0256 - mae: 0.1157 - root_mean_squared_error: 0.1601\n", "Epoch 929: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 50ms/step - loss: 0.0340 - mse: 0.0256 - mae: 0.1157 - root_mean_squared_error: 0.1601 - val_loss: 0.3841 - val_mse: 0.3758 - val_mae: 0.4701 - val_root_mean_squared_error: 0.6130\n", "Epoch 930/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0396 - mse: 0.0312 - mae: 0.1246 - root_mean_squared_error: 0.1766\n", "Epoch 930: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0395 - mse: 0.0312 - mae: 0.1249 - root_mean_squared_error: 0.1766 - val_loss: 0.4130 - val_mse: 0.4047 - val_mae: 0.4806 - val_root_mean_squared_error: 0.6361\n", "Epoch 931/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0330 - mse: 0.0246 - mae: 0.1121 - root_mean_squared_error: 0.1568\n", "Epoch 931: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0330 - mse: 0.0246 - mae: 0.1121 - root_mean_squared_error: 0.1568 - val_loss: 0.4026 - val_mse: 0.3943 - val_mae: 0.4768 - val_root_mean_squared_error: 0.6279\n", "Epoch 932/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0349 - mse: 0.0266 - mae: 0.1137 - root_mean_squared_error: 0.1631\n", "Epoch 932: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0348 - mse: 0.0264 - mae: 0.1133 - root_mean_squared_error: 0.1626 - val_loss: 0.4102 - val_mse: 0.4019 - val_mae: 0.4757 - val_root_mean_squared_error: 0.6339\n", "Epoch 933/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0340 - mse: 0.0256 - mae: 0.1127 - root_mean_squared_error: 0.1601\n", "Epoch 933: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0337 - mse: 0.0253 - mae: 0.1121 - root_mean_squared_error: 0.1592 - val_loss: 0.4157 - val_mse: 0.4074 - val_mae: 0.4816 - val_root_mean_squared_error: 0.6383\n", "Epoch 934/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0390 - mse: 0.0307 - mae: 0.1249 - root_mean_squared_error: 0.1751\n", "Epoch 934: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0390 - mse: 0.0307 - mae: 0.1249 - root_mean_squared_error: 0.1751 - val_loss: 0.4183 - val_mse: 0.4100 - val_mae: 0.4816 - val_root_mean_squared_error: 0.6403\n", "Epoch 935/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0342 - mse: 0.0259 - mae: 0.1132 - root_mean_squared_error: 0.1609\n", "Epoch 935: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0339 - mse: 0.0255 - mae: 0.1122 - root_mean_squared_error: 0.1597 - val_loss: 0.4308 - val_mse: 0.4224 - val_mae: 0.4902 - val_root_mean_squared_error: 0.6499\n", "Epoch 936/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0322 - mse: 0.0239 - mae: 0.1118 - root_mean_squared_error: 0.1545\n", "Epoch 936: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0322 - mse: 0.0238 - mae: 0.1118 - root_mean_squared_error: 0.1543 - val_loss: 0.4079 - val_mse: 0.3996 - val_mae: 0.4845 - val_root_mean_squared_error: 0.6321\n", "Epoch 937/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0337 - mse: 0.0254 - mae: 0.1155 - root_mean_squared_error: 0.1593\n", "Epoch 937: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0336 - mse: 0.0253 - mae: 0.1153 - root_mean_squared_error: 0.1590 - val_loss: 0.4048 - val_mse: 0.3964 - val_mae: 0.4792 - val_root_mean_squared_error: 0.6296\n", "Epoch 938/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0336 - mse: 0.0253 - mae: 0.1173 - root_mean_squared_error: 0.1589\n", "Epoch 938: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0338 - mse: 0.0254 - mae: 0.1174 - root_mean_squared_error: 0.1595 - val_loss: 0.4287 - val_mse: 0.4204 - val_mae: 0.4950 - val_root_mean_squared_error: 0.6484\n", "Epoch 939/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0371 - mse: 0.0288 - mae: 0.1218 - root_mean_squared_error: 0.1697\n", "Epoch 939: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0371 - mse: 0.0288 - mae: 0.1218 - root_mean_squared_error: 0.1697 - val_loss: 0.4239 - val_mse: 0.4156 - val_mae: 0.4955 - val_root_mean_squared_error: 0.6446\n", "Epoch 940/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0419 - mse: 0.0336 - mae: 0.1339 - root_mean_squared_error: 0.1834\n", "Epoch 940: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 0.0423 - mse: 0.0339 - mae: 0.1342 - root_mean_squared_error: 0.1843 - val_loss: 0.4155 - val_mse: 0.4071 - val_mae: 0.4877 - val_root_mean_squared_error: 0.6381\n", "Epoch 941/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0368 - mse: 0.0284 - mae: 0.1209 - root_mean_squared_error: 0.1686\n", "Epoch 941: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0368 - mse: 0.0284 - mae: 0.1209 - root_mean_squared_error: 0.1686 - val_loss: 0.4188 - val_mse: 0.4104 - val_mae: 0.4855 - val_root_mean_squared_error: 0.6406\n", "Epoch 942/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0386 - mse: 0.0303 - mae: 0.1267 - root_mean_squared_error: 0.1740\n", "Epoch 942: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 58ms/step - loss: 0.0386 - mse: 0.0303 - mae: 0.1267 - root_mean_squared_error: 0.1740 - val_loss: 0.4006 - val_mse: 0.3923 - val_mae: 0.4713 - val_root_mean_squared_error: 0.6263\n", "Epoch 943/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0371 - mse: 0.0287 - mae: 0.1229 - root_mean_squared_error: 0.1695\n", "Epoch 943: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0371 - mse: 0.0288 - mae: 0.1232 - root_mean_squared_error: 0.1696 - val_loss: 0.4159 - val_mse: 0.4075 - val_mae: 0.4871 - val_root_mean_squared_error: 0.6384\n", "Epoch 944/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0317 - mse: 0.0233 - mae: 0.1085 - root_mean_squared_error: 0.1527\n", "Epoch 944: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 0.0317 - mse: 0.0233 - mae: 0.1085 - root_mean_squared_error: 0.1527 - val_loss: 0.3988 - val_mse: 0.3904 - val_mae: 0.4736 - val_root_mean_squared_error: 0.6248\n", "Epoch 945/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0333 - mse: 0.0249 - mae: 0.1130 - root_mean_squared_error: 0.1579\n", "Epoch 945: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0333 - mse: 0.0249 - mae: 0.1130 - root_mean_squared_error: 0.1579 - val_loss: 0.4297 - val_mse: 0.4214 - val_mae: 0.4945 - val_root_mean_squared_error: 0.6492\n", "Epoch 946/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0335 - mse: 0.0252 - mae: 0.1141 - root_mean_squared_error: 0.1587\n", "Epoch 946: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0334 - mse: 0.0251 - mae: 0.1140 - root_mean_squared_error: 0.1585 - val_loss: 0.4118 - val_mse: 0.4035 - val_mae: 0.4802 - val_root_mean_squared_error: 0.6352\n", "Epoch 947/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0360 - mse: 0.0277 - mae: 0.1171 - root_mean_squared_error: 0.1666\n", "Epoch 947: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0359 - mse: 0.0276 - mae: 0.1170 - root_mean_squared_error: 0.1663 - val_loss: 0.4186 - val_mse: 0.4103 - val_mae: 0.4921 - val_root_mean_squared_error: 0.6406\n", "Epoch 948/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0334 - mse: 0.0251 - mae: 0.1138 - root_mean_squared_error: 0.1583\n", "Epoch 948: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0334 - mse: 0.0251 - mae: 0.1138 - root_mean_squared_error: 0.1583 - val_loss: 0.4036 - val_mse: 0.3954 - val_mae: 0.4781 - val_root_mean_squared_error: 0.6288\n", "Epoch 949/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0425 - mse: 0.0342 - mae: 0.1318 - root_mean_squared_error: 0.1849\n", "Epoch 949: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0431 - mse: 0.0348 - mae: 0.1332 - root_mean_squared_error: 0.1867 - val_loss: 0.4272 - val_mse: 0.4189 - val_mae: 0.4889 - val_root_mean_squared_error: 0.6473\n", "Epoch 950/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0436 - mse: 0.0353 - mae: 0.1340 - root_mean_squared_error: 0.1878\n", "Epoch 950: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0436 - mse: 0.0353 - mae: 0.1341 - root_mean_squared_error: 0.1878 - val_loss: 0.4200 - val_mse: 0.4117 - val_mae: 0.4847 - val_root_mean_squared_error: 0.6416\n", "Epoch 951/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0352 - mse: 0.0269 - mae: 0.1189 - root_mean_squared_error: 0.1640\n", "Epoch 951: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 47ms/step - loss: 0.0351 - mse: 0.0268 - mae: 0.1187 - root_mean_squared_error: 0.1637 - val_loss: 0.3942 - val_mse: 0.3858 - val_mae: 0.4741 - val_root_mean_squared_error: 0.6212\n", "Epoch 952/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0384 - mse: 0.0301 - mae: 0.1278 - root_mean_squared_error: 0.1734\n", "Epoch 952: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0384 - mse: 0.0301 - mae: 0.1278 - root_mean_squared_error: 0.1734 - val_loss: 0.4200 - val_mse: 0.4116 - val_mae: 0.4844 - val_root_mean_squared_error: 0.6416\n", "Epoch 953/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0367 - mse: 0.0284 - mae: 0.1181 - root_mean_squared_error: 0.1684\n", "Epoch 953: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0367 - mse: 0.0284 - mae: 0.1181 - root_mean_squared_error: 0.1684 - val_loss: 0.4183 - val_mse: 0.4100 - val_mae: 0.4806 - val_root_mean_squared_error: 0.6403\n", "Epoch 954/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0387 - mse: 0.0304 - mae: 0.1245 - root_mean_squared_error: 0.1743\n", "Epoch 954: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0387 - mse: 0.0304 - mae: 0.1249 - root_mean_squared_error: 0.1744 - val_loss: 0.4043 - val_mse: 0.3960 - val_mae: 0.4703 - val_root_mean_squared_error: 0.6293\n", "Epoch 955/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0348 - mse: 0.0265 - mae: 0.1162 - root_mean_squared_error: 0.1629\n", "Epoch 955: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0353 - mse: 0.0270 - mae: 0.1173 - root_mean_squared_error: 0.1643 - val_loss: 0.4140 - val_mse: 0.4057 - val_mae: 0.4872 - val_root_mean_squared_error: 0.6369\n", "Epoch 956/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0364 - mse: 0.0281 - mae: 0.1179 - root_mean_squared_error: 0.1677\n", "Epoch 956: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0364 - mse: 0.0281 - mae: 0.1179 - root_mean_squared_error: 0.1677 - val_loss: 0.3999 - val_mse: 0.3917 - val_mae: 0.4732 - val_root_mean_squared_error: 0.6258\n", "Epoch 957/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0344 - mse: 0.0261 - mae: 0.1160 - root_mean_squared_error: 0.1616\n", "Epoch 957: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0343 - mse: 0.0260 - mae: 0.1158 - root_mean_squared_error: 0.1612 - val_loss: 0.4210 - val_mse: 0.4127 - val_mae: 0.4939 - val_root_mean_squared_error: 0.6424\n", "Epoch 958/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0335 - mse: 0.0252 - mae: 0.1124 - root_mean_squared_error: 0.1587\n", "Epoch 958: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0335 - mse: 0.0252 - mae: 0.1124 - root_mean_squared_error: 0.1587 - val_loss: 0.4231 - val_mse: 0.4148 - val_mae: 0.4797 - val_root_mean_squared_error: 0.6441\n", "Epoch 959/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0389 - mse: 0.0306 - mae: 0.1241 - root_mean_squared_error: 0.1750\n", "Epoch 959: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0387 - mse: 0.0304 - mae: 0.1237 - root_mean_squared_error: 0.1745 - val_loss: 0.4090 - val_mse: 0.4007 - val_mae: 0.4768 - val_root_mean_squared_error: 0.6330\n", "Epoch 960/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0393 - mse: 0.0311 - mae: 0.1296 - root_mean_squared_error: 0.1763\n", "Epoch 960: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 52ms/step - loss: 0.0393 - mse: 0.0311 - mae: 0.1296 - root_mean_squared_error: 0.1763 - val_loss: 0.4297 - val_mse: 0.4214 - val_mae: 0.4807 - val_root_mean_squared_error: 0.6492\n", "Epoch 961/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0440 - mse: 0.0357 - mae: 0.1387 - root_mean_squared_error: 0.1891\n", "Epoch 961: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0440 - mse: 0.0357 - mae: 0.1387 - root_mean_squared_error: 0.1891 - val_loss: 0.4220 - val_mse: 0.4137 - val_mae: 0.4952 - val_root_mean_squared_error: 0.6432\n", "Epoch 962/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0410 - mse: 0.0327 - mae: 0.1276 - root_mean_squared_error: 0.1809\n", "Epoch 962: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0409 - mse: 0.0326 - mae: 0.1275 - root_mean_squared_error: 0.1806 - val_loss: 0.4114 - val_mse: 0.4031 - val_mae: 0.4828 - val_root_mean_squared_error: 0.6349\n", "Epoch 963/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0477 - mse: 0.0394 - mae: 0.1403 - root_mean_squared_error: 0.1986\n", "Epoch 963: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 5s 63ms/step - loss: 0.0475 - mse: 0.0392 - mae: 0.1397 - root_mean_squared_error: 0.1980 - val_loss: 0.4119 - val_mse: 0.4036 - val_mae: 0.4831 - val_root_mean_squared_error: 0.6353\n", "Epoch 964/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0384 - mse: 0.0301 - mae: 0.1268 - root_mean_squared_error: 0.1735\n", "Epoch 964: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0383 - mse: 0.0300 - mae: 0.1267 - root_mean_squared_error: 0.1732 - val_loss: 0.3929 - val_mse: 0.3846 - val_mae: 0.4688 - val_root_mean_squared_error: 0.6201\n", "Epoch 965/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0358 - mse: 0.0275 - mae: 0.1178 - root_mean_squared_error: 0.1659\n", "Epoch 965: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0358 - mse: 0.0275 - mae: 0.1178 - root_mean_squared_error: 0.1659 - val_loss: 0.4160 - val_mse: 0.4076 - val_mae: 0.4784 - val_root_mean_squared_error: 0.6385\n", "Epoch 966/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0381 - mse: 0.0298 - mae: 0.1212 - root_mean_squared_error: 0.1727\n", "Epoch 966: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 46ms/step - loss: 0.0380 - mse: 0.0297 - mae: 0.1211 - root_mean_squared_error: 0.1723 - val_loss: 0.4047 - val_mse: 0.3964 - val_mae: 0.4711 - val_root_mean_squared_error: 0.6296\n", "Epoch 967/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0315 - mse: 0.0232 - mae: 0.1061 - root_mean_squared_error: 0.1523\n", "Epoch 967: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0315 - mse: 0.0232 - mae: 0.1061 - root_mean_squared_error: 0.1523 - val_loss: 0.4300 - val_mse: 0.4217 - val_mae: 0.4894 - val_root_mean_squared_error: 0.6494\n", "Epoch 968/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0343 - mse: 0.0260 - mae: 0.1144 - root_mean_squared_error: 0.1612\n", "Epoch 968: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0342 - mse: 0.0260 - mae: 0.1143 - root_mean_squared_error: 0.1611 - val_loss: 0.3977 - val_mse: 0.3894 - val_mae: 0.4670 - val_root_mean_squared_error: 0.6240\n", "Epoch 969/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0313 - mse: 0.0230 - mae: 0.1082 - root_mean_squared_error: 0.1517\n", "Epoch 969: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0312 - mse: 0.0230 - mae: 0.1082 - root_mean_squared_error: 0.1515 - val_loss: 0.4139 - val_mse: 0.4056 - val_mae: 0.4806 - val_root_mean_squared_error: 0.6369\n", "Epoch 970/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0346 - mse: 0.0264 - mae: 0.1191 - root_mean_squared_error: 0.1623\n", "Epoch 970: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0346 - mse: 0.0264 - mae: 0.1191 - root_mean_squared_error: 0.1623 - val_loss: 0.3940 - val_mse: 0.3858 - val_mae: 0.4725 - val_root_mean_squared_error: 0.6211\n", "Epoch 971/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0358 - mse: 0.0275 - mae: 0.1179 - root_mean_squared_error: 0.1659\n", "Epoch 971: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0359 - mse: 0.0276 - mae: 0.1180 - root_mean_squared_error: 0.1662 - val_loss: 0.4038 - val_mse: 0.3955 - val_mae: 0.4703 - val_root_mean_squared_error: 0.6289\n", "Epoch 972/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0347 - mse: 0.0265 - mae: 0.1176 - root_mean_squared_error: 0.1627\n", "Epoch 972: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0347 - mse: 0.0264 - mae: 0.1175 - root_mean_squared_error: 0.1625 - val_loss: 0.4087 - val_mse: 0.4004 - val_mae: 0.4731 - val_root_mean_squared_error: 0.6328\n", "Epoch 973/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0347 - mse: 0.0264 - mae: 0.1140 - root_mean_squared_error: 0.1626\n", "Epoch 973: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0347 - mse: 0.0264 - mae: 0.1140 - root_mean_squared_error: 0.1626 - val_loss: 0.4000 - val_mse: 0.3917 - val_mae: 0.4731 - val_root_mean_squared_error: 0.6259\n", "Epoch 974/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0423 - mse: 0.0341 - mae: 0.1293 - root_mean_squared_error: 0.1846\n", "Epoch 974: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 48ms/step - loss: 0.0423 - mse: 0.0341 - mae: 0.1293 - root_mean_squared_error: 0.1846 - val_loss: 0.4070 - val_mse: 0.3987 - val_mae: 0.4805 - val_root_mean_squared_error: 0.6315\n", "Epoch 975/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0482 - mse: 0.0399 - mae: 0.1453 - root_mean_squared_error: 0.1998\n", "Epoch 975: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 43ms/step - loss: 0.0482 - mse: 0.0399 - mae: 0.1453 - root_mean_squared_error: 0.1998 - val_loss: 0.4472 - val_mse: 0.4389 - val_mae: 0.4971 - val_root_mean_squared_error: 0.6625\n", "Epoch 976/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0442 - mse: 0.0359 - mae: 0.1352 - root_mean_squared_error: 0.1895\n", "Epoch 976: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 49ms/step - loss: 0.0440 - mse: 0.0357 - mae: 0.1347 - root_mean_squared_error: 0.1889 - val_loss: 0.4319 - val_mse: 0.4236 - val_mae: 0.4895 - val_root_mean_squared_error: 0.6509\n", "Epoch 977/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0325 - mse: 0.0242 - mae: 0.1117 - root_mean_squared_error: 0.1557\n", "Epoch 977: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0324 - mse: 0.0241 - mae: 0.1114 - root_mean_squared_error: 0.1553 - val_loss: 0.3978 - val_mse: 0.3895 - val_mae: 0.4762 - val_root_mean_squared_error: 0.6241\n", "Epoch 978/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0332 - mse: 0.0249 - mae: 0.1115 - root_mean_squared_error: 0.1577\n", "Epoch 978: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0330 - mse: 0.0247 - mae: 0.1111 - root_mean_squared_error: 0.1573 - val_loss: 0.4129 - val_mse: 0.4046 - val_mae: 0.4707 - val_root_mean_squared_error: 0.6361\n", "Epoch 979/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0339 - mse: 0.0256 - mae: 0.1154 - root_mean_squared_error: 0.1600\n", "Epoch 979: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0337 - mse: 0.0254 - mae: 0.1149 - root_mean_squared_error: 0.1594 - val_loss: 0.3969 - val_mse: 0.3887 - val_mae: 0.4738 - val_root_mean_squared_error: 0.6234\n", "Epoch 980/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0316 - mse: 0.0234 - mae: 0.1115 - root_mean_squared_error: 0.1530\n", "Epoch 980: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0316 - mse: 0.0234 - mae: 0.1115 - root_mean_squared_error: 0.1530 - val_loss: 0.4022 - val_mse: 0.3940 - val_mae: 0.4739 - val_root_mean_squared_error: 0.6277\n", "Epoch 981/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0355 - mse: 0.0273 - mae: 0.1146 - root_mean_squared_error: 0.1652\n", "Epoch 981: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 38ms/step - loss: 0.0355 - mse: 0.0273 - mae: 0.1146 - root_mean_squared_error: 0.1652 - val_loss: 0.4355 - val_mse: 0.4272 - val_mae: 0.4889 - val_root_mean_squared_error: 0.6536\n", "Epoch 982/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0298 - mse: 0.0215 - mae: 0.1053 - root_mean_squared_error: 0.1467\n", "Epoch 982: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0300 - mse: 0.0217 - mae: 0.1055 - root_mean_squared_error: 0.1474 - val_loss: 0.4122 - val_mse: 0.4039 - val_mae: 0.4775 - val_root_mean_squared_error: 0.6356\n", "Epoch 983/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0355 - mse: 0.0273 - mae: 0.1166 - root_mean_squared_error: 0.1653\n", "Epoch 983: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 56ms/step - loss: 0.0372 - mse: 0.0289 - mae: 0.1177 - root_mean_squared_error: 0.1701 - val_loss: 0.3994 - val_mse: 0.3912 - val_mae: 0.4678 - val_root_mean_squared_error: 0.6254\n", "Epoch 984/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0372 - mse: 0.0290 - mae: 0.1195 - root_mean_squared_error: 0.1702\n", "Epoch 984: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0372 - mse: 0.0290 - mae: 0.1195 - root_mean_squared_error: 0.1702 - val_loss: 0.4178 - val_mse: 0.4096 - val_mae: 0.4835 - val_root_mean_squared_error: 0.6400\n", "Epoch 985/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0367 - mse: 0.0285 - mae: 0.1215 - root_mean_squared_error: 0.1687\n", "Epoch 985: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0367 - mse: 0.0285 - mae: 0.1215 - root_mean_squared_error: 0.1687 - val_loss: 0.4085 - val_mse: 0.4003 - val_mae: 0.4743 - val_root_mean_squared_error: 0.6327\n", "Epoch 986/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0416 - mse: 0.0333 - mae: 0.1304 - root_mean_squared_error: 0.1826\n", "Epoch 986: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0416 - mse: 0.0333 - mae: 0.1304 - root_mean_squared_error: 0.1826 - val_loss: 0.4201 - val_mse: 0.4118 - val_mae: 0.4778 - val_root_mean_squared_error: 0.6417\n", "Epoch 987/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0392 - mse: 0.0309 - mae: 0.1257 - root_mean_squared_error: 0.1758\n", "Epoch 987: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 36ms/step - loss: 0.0390 - mse: 0.0308 - mae: 0.1254 - root_mean_squared_error: 0.1754 - val_loss: 0.4034 - val_mse: 0.3951 - val_mae: 0.4815 - val_root_mean_squared_error: 0.6286\n", "Epoch 988/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0386 - mse: 0.0303 - mae: 0.1242 - root_mean_squared_error: 0.1741\n", "Epoch 988: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 34ms/step - loss: 0.0386 - mse: 0.0303 - mae: 0.1242 - root_mean_squared_error: 0.1741 - val_loss: 0.4448 - val_mse: 0.4365 - val_mae: 0.4966 - val_root_mean_squared_error: 0.6607\n", "Epoch 989/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0383 - mse: 0.0300 - mae: 0.1269 - root_mean_squared_error: 0.1733\n", "Epoch 989: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0383 - mse: 0.0300 - mae: 0.1269 - root_mean_squared_error: 0.1733 - val_loss: 0.4166 - val_mse: 0.4083 - val_mae: 0.4825 - val_root_mean_squared_error: 0.6390\n", "Epoch 990/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0369 - mse: 0.0286 - mae: 0.1206 - root_mean_squared_error: 0.1691\n", "Epoch 990: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 44ms/step - loss: 0.0372 - mse: 0.0289 - mae: 0.1212 - root_mean_squared_error: 0.1701 - val_loss: 0.3979 - val_mse: 0.3896 - val_mae: 0.4796 - val_root_mean_squared_error: 0.6242\n", "Epoch 991/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0333 - mse: 0.0251 - mae: 0.1133 - root_mean_squared_error: 0.1583\n", "Epoch 991: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0333 - mse: 0.0250 - mae: 0.1132 - root_mean_squared_error: 0.1581 - val_loss: 0.4491 - val_mse: 0.4409 - val_mae: 0.5117 - val_root_mean_squared_error: 0.6640\n", "Epoch 992/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0400 - mse: 0.0318 - mae: 0.1295 - root_mean_squared_error: 0.1782\n", "Epoch 992: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0400 - mse: 0.0318 - mae: 0.1295 - root_mean_squared_error: 0.1782 - val_loss: 0.4116 - val_mse: 0.4033 - val_mae: 0.4816 - val_root_mean_squared_error: 0.6351\n", "Epoch 993/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0337 - mse: 0.0255 - mae: 0.1146 - root_mean_squared_error: 0.1595\n", "Epoch 993: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 39ms/step - loss: 0.0336 - mse: 0.0254 - mae: 0.1146 - root_mean_squared_error: 0.1592 - val_loss: 0.4065 - val_mse: 0.3982 - val_mae: 0.4804 - val_root_mean_squared_error: 0.6311\n", "Epoch 994/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0290 - mse: 0.0208 - mae: 0.1038 - root_mean_squared_error: 0.1443\n", "Epoch 994: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0290 - mse: 0.0208 - mae: 0.1040 - root_mean_squared_error: 0.1443 - val_loss: 0.4035 - val_mse: 0.3953 - val_mae: 0.4717 - val_root_mean_squared_error: 0.6287\n", "Epoch 995/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0417 - mse: 0.0334 - mae: 0.1352 - root_mean_squared_error: 0.1829\n", "Epoch 995: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 41ms/step - loss: 0.0415 - mse: 0.0333 - mae: 0.1349 - root_mean_squared_error: 0.1825 - val_loss: 0.3998 - val_mse: 0.3916 - val_mae: 0.4759 - val_root_mean_squared_error: 0.6258\n", "Epoch 996/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0327 - mse: 0.0244 - mae: 0.1124 - root_mean_squared_error: 0.1563\n", "Epoch 996: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 42ms/step - loss: 0.0325 - mse: 0.0243 - mae: 0.1122 - root_mean_squared_error: 0.1560 - val_loss: 0.4053 - val_mse: 0.3971 - val_mae: 0.4795 - val_root_mean_squared_error: 0.6302\n", "Epoch 997/1000\n", "71/73 [============================>.] - ETA: 0s - loss: 0.0363 - mse: 0.0281 - mae: 0.1216 - root_mean_squared_error: 0.1677\n", "Epoch 997: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 45ms/step - loss: 0.0363 - mse: 0.0281 - mae: 0.1212 - root_mean_squared_error: 0.1677 - val_loss: 0.4275 - val_mse: 0.4193 - val_mae: 0.4828 - val_root_mean_squared_error: 0.6475\n", "Epoch 998/1000\n", "73/73 [==============================] - ETA: 0s - loss: 0.0376 - mse: 0.0294 - mae: 0.1241 - root_mean_squared_error: 0.1714\n", "Epoch 998: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 37ms/step - loss: 0.0376 - mse: 0.0294 - mae: 0.1241 - root_mean_squared_error: 0.1714 - val_loss: 0.4228 - val_mse: 0.4146 - val_mae: 0.4940 - val_root_mean_squared_error: 0.6439\n", "Epoch 999/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0569 - mse: 0.0486 - mae: 0.1598 - root_mean_squared_error: 0.2205\n", "Epoch 999: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 3s 40ms/step - loss: 0.0572 - mse: 0.0489 - mae: 0.1605 - root_mean_squared_error: 0.2212 - val_loss: 0.4133 - val_mse: 0.4050 - val_mae: 0.4799 - val_root_mean_squared_error: 0.6364\n", "Epoch 1000/1000\n", "72/73 [============================>.] - ETA: 0s - loss: 0.0391 - mse: 0.0308 - mae: 0.1258 - root_mean_squared_error: 0.1756\n", "Epoch 1000: saving model to ./save_model\\hu_model_16batch_1000epoch_0.0001lr.h5\n", "73/73 [==============================] - 4s 50ms/step - loss: 0.0389 - mse: 0.0307 - mae: 0.1255 - root_mean_squared_error: 0.1751 - val_loss: 0.4098 - val_mse: 0.4015 - val_mae: 0.4811 - val_root_mean_squared_error: 0.6336\n", "hu r2 score : 0.904941194642747\n" ] }, { "data": { "text/plain": [ "2038" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tf.keras.backend.clear_session()\n", "model_fhu1.fit(xtr_fhu,ytr_fhu,\n", " batch_size=BATCHSIZE,\n", " callbacks=[cp_hu],\n", " # validation_split=0.1,\n", " epochs=EPOCHS,\n", " verbose=1,\n", ")\n", "model_fhu1.save(f'./save_model/hu_manual_save_model_{BATCHSIZE}batch_{lr}lr.h5')\n", "y_pred_search = model_fhu1.predict(xte_fhu, verbose=0)\n", "score = r2_score(yte_fhu, y_pred_search)\n", "print(f\"hu r2 score : {score}\")\n", "gc.collect()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# from sklearn.model_selection import KFold\n", "# split_num=4\n", "# kf = KFold(n_splits=split_num)\n", "# model_fws2 = ws_model()\n", "# score_accum={}\n", "# i=0\n", "\n", "# tf.keras.backend.clear_session()\n", "# for tr, te in kf.split(xtr_fws):\n", "# xtr, xte = xtr_fws[tr], xtr_fws[te]\n", "# ytr, yte = ytr_fws[tr], ytr_fws[te]\n", "# model_fws2.fit(xtr,ytr,\n", "# batch_size=BATCHSIZE,\n", "# validation_split=0.1,\n", "# epochs=EPOCHS,\n", "# verbose=0,\n", "# )\n", "# y_pred_search = model_fws2.predict(xte, verbose=0)\n", "# score = r2_score(yte, y_pred_search)\n", "# score_accum['r2_valid{}'.format(i)]=score\n", "# print(f\"Finishied #{i+1} - {score}\") \n", "# i+=1\n", "# gc.collect()\n", "# model_fws2.save(\"{}_model_cross_validation_{}batch_{}epoch_{}lr.h5\".format('ws',BATCHSIZE,EPOCHS,lr))\n", "# y_pred_search = model_fws2.predict(xte_fws, verbose=0)\n", "# score = r2_score(yte_fws, y_pred_search)\n", "# print(score_accum)\n", "# print(f\"Final {score}\")" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [], "source": [ "# res = 0\n", "# for i,j in score_accum.items():\n", "# res+=j\n", "# res = res/4.0\n", "# res" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": [ "# %tensorboard --logdir logs/gradient_tape" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3.9.12 ('ai')", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.13" }, "orig_nbformat": 4, "vscode": { "interpreter": { "hash": "e5cdae407986fbcf9f40eb4f2caf8136385e94546bed8444298080b1cba2358b" } } }, "nbformat": 4, "nbformat_minor": 2 }