---
license: mit
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: microsoft/Phi-3-mini-4k-instruct
model-index:
- name: CH-Phi3m4k
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# CH-Phi3m4k

This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an [casehold/casehold](https://huggingface.co/datasets/casehold/casehold) dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5304

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 8
- eval_batch_size: 1
- seed: 342
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Validation F1 |
|:-------------:|:------:|:----:|:---------------:|:-------------:|
| 2.0053        | 0.1422 | 200  | 1.8927          |0.722          |
| 1.6481        | 0.2844 | 400  | 1.6065          |0.732          |
| 1.5653        | 0.4267 | 600  | 1.5864          |0.746          |
| 1.5516        | 0.5689 | 800  | 1.5762          |0.758          |
| 1.537         | 0.7111 | 1000 | 1.5689          |0.768          |
| 1.5318        | 0.8533 | 1200 | 1.5637          |0.772          |
| 1.5249        | 0.9956 | 1400 | 1.5595          |0.774          |
| 1.5208        | 1.1378 | 1600 | 1.5550          |0.768          |
| 1.5234        | 1.28   | 1800 | 1.5511          |0.778          |
| 1.5099        | 1.4222 | 2000 | 1.5480          |0.774          |
| 1.5144        | 1.5644 | 2200 | 1.5448          |0.774          |
| 1.5139        | 1.7067 | 2400 | 1.5424          |0.776          |
| 1.5013        | 1.8489 | 2600 | 1.5395          |0.778          |
| 1.502         | 1.9911 | 2800 | 1.5377          |0.770          |
| 1.4979        | 2.1333 | 3000 | 1.5358          |0.768          |
| 1.491         | 2.2756 | 3200 | 1.5338          |0.768          |
| 1.5025        | 2.4178 | 3400 | 1.5318          |0.772          |
| 1.4933        | 2.56   | 3600 | 1.5304          |0.772          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1