---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: Mistral-7B-v0.1_caselaw
  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. -->

# Mistral-7B-v0.1_caselaw

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1640

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.2324        | 0.07  | 50   | 1.2373          |
| 1.2114        | 0.13  | 100  | 1.2199          |
| 1.1831        | 0.2   | 150  | 1.2111          |
| 1.2027        | 0.26  | 200  | 1.2048          |
| 1.1827        | 0.33  | 250  | 1.2001          |
| 1.1696        | 0.39  | 300  | 1.1973          |
| 1.2186        | 0.46  | 350  | 1.1938          |
| 1.1795        | 0.52  | 400  | 1.1919          |
| 1.2167        | 0.59  | 450  | 1.1884          |
| 1.1992        | 0.66  | 500  | 1.1840          |
| 1.2032        | 0.72  | 550  | 1.1824          |
| 1.1841        | 0.79  | 600  | 1.1798          |
| 1.166         | 0.85  | 650  | 1.1789          |
| 1.1641        | 0.92  | 700  | 1.1761          |
| 1.1859        | 0.98  | 750  | 1.1752          |
| 1.132         | 1.05  | 800  | 1.1736          |
| 1.1461        | 1.12  | 850  | 1.1724          |
| 1.0965        | 1.18  | 900  | 1.1726          |
| 1.1064        | 1.25  | 950  | 1.1724          |
| 1.123         | 1.31  | 1000 | 1.1729          |
| 1.1079        | 1.38  | 1050 | 1.1695          |
| 1.12          | 1.44  | 1100 | 1.1707          |
| 1.1288        | 1.51  | 1150 | 1.1693          |
| 1.133         | 1.57  | 1200 | 1.1676          |
| 1.1647        | 1.64  | 1250 | 1.1693          |
| 1.1269        | 1.71  | 1300 | 1.1658          |
| 1.1332        | 1.77  | 1350 | 1.1657          |
| 1.1276        | 1.84  | 1400 | 1.1681          |
| 1.1361        | 1.9   | 1450 | 1.1633          |
| 1.1205        | 1.97  | 1500 | 1.1640          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.17.1
- Tokenizers 0.15.1