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README.md

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+
+---
+tags:
+- autotrain
+- text-classification
+base_model: google-bert/bert-base-german-cased
+widget:
+- text: "I love AutoTrain"
+---
+
+# Model Trained Using AutoTrain
+
+- Problem type: Text Classification
+
+## Validation Metrics
+loss: 6.8204345703125
+
+f1_macro: 0.009477047596877624
+
+f1_micro: 0.06276134649533156
+
+f1_weighted: 0.03996332128759549
+
+precision_macro: 0.008540631772865619
+
+precision_micro: 0.06276134649533156
+
+precision_weighted: 0.03304113276853252
+
+recall_macro: 0.014575594682055309
+
+recall_micro: 0.06276134649533156
+
+recall_weighted: 0.06276134649533156
+
+accuracy: 0.06276134649533156

checkpoint-245080/model.safetensors

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checkpoint-245080/optimizer.pt

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runs/Dec31_11-34-19_ccc0389.campuscluster.illinois.edu/events.out.tfevents.1735666461.ccc0389.campuscluster.illinois.edu.15807.0

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special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+    "2": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
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+      "normalized": false,
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+      "single_word": false,
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+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_lower_case": false,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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training_params.json

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+{
+    "data_path": "bert-base-german-cased-gnd/autotrain-data",
+    "model": "google-bert/bert-base-german-cased",
+    "lr": 1e-05,
+    "epochs": 100,
+    "max_seq_length": 512,
+    "batch_size": 8,
+    "warmup_ratio": 0.1,
+    "gradient_accumulation": 1,
+    "optimizer": "adamw_torch",
+    "scheduler": "linear",
+    "weight_decay": 0.0,
+    "max_grad_norm": 1.0,
+    "seed": 42,
+    "train_split": "train",
+    "valid_split": "validation",
+    "text_column": "autotrain_text",
+    "target_column": "autotrain_label",
+    "logging_steps": -1,
+    "project_name": "bert-base-german-cased-gnd",
+    "auto_find_batch_size": false,
+    "mixed_precision": "fp16",
+    "save_total_limit": 1,
+    "push_to_hub": true,
+    "eval_strategy": "epoch",
+    "username": "jimfhahn",
+    "log": "tensorboard",
+    "early_stopping_patience": 5,
+    "early_stopping_threshold": 0.01
+}