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

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0554

## 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: 2
- 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: 1
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8941        | 0.05  | 25   | 1.7724          |
| 1.8315        | 0.1   | 50   | 1.7261          |
| 1.7522        | 0.14  | 75   | 1.6971          |
| 1.6974        | 0.19  | 100  | 1.6678          |
| 1.7149        | 0.24  | 125  | 1.6430          |
| 1.6037        | 0.29  | 150  | 1.6201          |
| 1.6611        | 0.34  | 175  | 1.6057          |
| 1.7131        | 0.38  | 200  | 1.5854          |
| 1.7619        | 0.43  | 225  | 1.5696          |
| 1.6062        | 0.48  | 250  | 1.5494          |
| 1.5171        | 0.53  | 275  | 1.5284          |
| 1.6484        | 0.58  | 300  | 1.5091          |
| 1.7207        | 0.62  | 325  | 1.4958          |
| 1.6548        | 0.67  | 350  | 1.4817          |
| 1.6447        | 0.72  | 375  | 1.4746          |
| 1.5294        | 0.77  | 400  | 1.4358          |
| 1.6865        | 0.82  | 425  | 1.4269          |
| 1.4704        | 0.87  | 450  | 1.3963          |
| 1.4935        | 0.91  | 475  | 1.3714          |
| 1.4714        | 0.96  | 500  | 1.3496          |
| 1.4913        | 1.01  | 525  | 1.3327          |
| 1.3627        | 1.06  | 550  | 1.3060          |
| 1.2748        | 1.11  | 575  | 1.2857          |
| 1.1856        | 1.15  | 600  | 1.2624          |
| 1.1102        | 1.2   | 625  | 1.2413          |
| 1.2375        | 1.25  | 650  | 1.2214          |
| 1.2421        | 1.3   | 675  | 1.1989          |
| 1.1946        | 1.35  | 700  | 1.1823          |
| 1.2389        | 1.39  | 725  | 1.1674          |
| 1.2961        | 1.44  | 750  | 1.1567          |
| 1.1831        | 1.49  | 775  | 1.1566          |
| 1.2144        | 1.54  | 800  | 1.1326          |
| 1.2881        | 1.59  | 825  | 1.1279          |
| 1.2584        | 1.63  | 850  | 1.1073          |
| 1.2837        | 1.68  | 875  | 1.0878          |
| 1.1251        | 1.73  | 900  | 1.0812          |
| 1.0938        | 1.78  | 925  | 1.0706          |
| 1.0304        | 1.83  | 950  | 1.0636          |
| 1.313         | 1.88  | 975  | 1.0676          |
| 1.2245        | 1.92  | 1000 | 1.0604          |
| 1.1293        | 1.97  | 1025 | 1.0554          |


### Framework versions

- PEFT 0.8.2
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1