---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
datasets:
- generator
base_model: mistralai/Mistral-7B-Instruct-v0.2
model-index:
- name: mistralai/Mistral-7B-Instruct-v0.2
  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. -->

# mistralai/Mistral-7B-Instruct-v0.2

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5526

## 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: 2.5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.03
- training_steps: 600

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.7925        | 0.22  | 10   | 2.0998          |
| 1.6897        | 0.43  | 20   | 1.3864          |
| 1.3495        | 0.65  | 30   | 1.2622          |
| 1.2144        | 0.87  | 40   | 1.1882          |
| 1.1546        | 1.09  | 50   | 1.1397          |
| 1.1002        | 1.3   | 60   | 1.0843          |
| 1.0023        | 1.52  | 70   | 0.9794          |
| 0.897         | 1.74  | 80   | 0.9370          |
| 0.8625        | 1.96  | 90   | 0.8557          |
| 0.7492        | 2.17  | 100  | 0.7909          |
| 0.7296        | 2.39  | 110  | 0.7455          |
| 0.6738        | 2.61  | 120  | 0.7239          |
| 0.656         | 2.83  | 130  | 0.7071          |
| 0.6289        | 3.04  | 140  | 0.6852          |
| 0.5835        | 3.26  | 150  | 0.6704          |
| 0.5647        | 3.48  | 160  | 0.6481          |
| 0.5416        | 3.7   | 170  | 0.6326          |
| 0.5159        | 3.91  | 180  | 0.6219          |
| 0.475         | 4.13  | 190  | 0.6091          |
| 0.4529        | 4.35  | 200  | 0.5903          |
| 0.4358        | 4.57  | 210  | 0.5769          |
| 0.4124        | 4.78  | 220  | 0.5574          |
| 0.3925        | 5.0   | 230  | 0.5433          |
| 0.3325        | 5.22  | 240  | 0.5396          |
| 0.3307        | 5.43  | 250  | 0.5241          |
| 0.3122        | 5.65  | 260  | 0.5185          |
| 0.2973        | 5.87  | 270  | 0.5042          |
| 0.2695        | 6.09  | 280  | 0.5082          |
| 0.2345        | 6.3   | 290  | 0.5020          |
| 0.2307        | 6.52  | 300  | 0.4859          |
| 0.2226        | 6.74  | 310  | 0.4771          |
| 0.2083        | 6.96  | 320  | 0.4717          |
| 0.1858        | 7.17  | 330  | 0.4881          |
| 0.1677        | 7.39  | 340  | 0.4791          |
| 0.1663        | 7.61  | 350  | 0.4774          |
| 0.1609        | 7.83  | 360  | 0.4780          |
| 0.1493        | 8.04  | 370  | 0.4820          |
| 0.1332        | 8.26  | 380  | 0.4940          |
| 0.1351        | 8.48  | 390  | 0.4898          |
| 0.1251        | 8.7   | 400  | 0.4894          |
| 0.1243        | 8.91  | 410  | 0.4836          |
| 0.1121        | 9.13  | 420  | 0.5108          |
| 0.1059        | 9.35  | 430  | 0.5055          |
| 0.1037        | 9.57  | 440  | 0.4974          |
| 0.102         | 9.78  | 450  | 0.4981          |
| 0.1032        | 10.0  | 460  | 0.5100          |
| 0.0887        | 10.22 | 470  | 0.5267          |
| 0.09          | 10.43 | 480  | 0.5231          |
| 0.084         | 10.65 | 490  | 0.5228          |
| 0.0865        | 10.87 | 500  | 0.5166          |
| 0.0838        | 11.09 | 510  | 0.5337          |
| 0.0762        | 11.3  | 520  | 0.5444          |
| 0.0792        | 11.52 | 530  | 0.5375          |
| 0.0765        | 11.74 | 540  | 0.5397          |
| 0.0747        | 11.96 | 550  | 0.5386          |
| 0.0684        | 12.17 | 560  | 0.5517          |
| 0.0697        | 12.39 | 570  | 0.5547          |
| 0.0701        | 12.61 | 580  | 0.5528          |
| 0.0702        | 12.83 | 590  | 0.5522          |
| 0.0693        | 13.04 | 600  | 0.5526          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0