---
license: apache-2.0
library_name: peft
tags:
- unsloth
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.3
model-index:
- name: mistral_7b_v_MetaMathQA_40K_reverse
  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_v_MetaMathQA_40K_reverse

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co./mistralai/Mistral-7B-v0.3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4421

## 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: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.02
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7252        | 0.0211 | 13   | 0.6225          |
| 0.5814        | 0.0421 | 26   | 0.5900          |
| 0.5599        | 0.0632 | 39   | 0.5751          |
| 0.548         | 0.0842 | 52   | 0.5708          |
| 0.5371        | 0.1053 | 65   | 0.5625          |
| 0.5347        | 0.1264 | 78   | 0.5600          |
| 0.5232        | 0.1474 | 91   | 0.5529          |
| 0.5382        | 0.1685 | 104  | 0.5478          |
| 0.5178        | 0.1896 | 117  | 0.5482          |
| 0.5272        | 0.2106 | 130  | 0.5423          |
| 0.5135        | 0.2317 | 143  | 0.5397          |
| 0.4943        | 0.2527 | 156  | 0.5321          |
| 0.5012        | 0.2738 | 169  | 0.5323          |
| 0.5077        | 0.2949 | 182  | 0.5300          |
| 0.5031        | 0.3159 | 195  | 0.5233          |
| 0.506         | 0.3370 | 208  | 0.5238          |
| 0.4851        | 0.3580 | 221  | 0.5180          |
| 0.4915        | 0.3791 | 234  | 0.5146          |
| 0.4826        | 0.4002 | 247  | 0.5150          |
| 0.4964        | 0.4212 | 260  | 0.5096          |
| 0.4989        | 0.4423 | 273  | 0.5050          |
| 0.4846        | 0.4633 | 286  | 0.5021          |
| 0.4776        | 0.4844 | 299  | 0.5006          |
| 0.4725        | 0.5055 | 312  | 0.4927          |
| 0.4752        | 0.5265 | 325  | 0.4898          |
| 0.4719        | 0.5476 | 338  | 0.4862          |
| 0.4689        | 0.5687 | 351  | 0.4817          |
| 0.4573        | 0.5897 | 364  | 0.4772          |
| 0.4536        | 0.6108 | 377  | 0.4754          |
| 0.4536        | 0.6318 | 390  | 0.4700          |
| 0.4519        | 0.6529 | 403  | 0.4664          |
| 0.4448        | 0.6740 | 416  | 0.4633          |
| 0.4327        | 0.6950 | 429  | 0.4618          |
| 0.4528        | 0.7161 | 442  | 0.4586          |
| 0.4379        | 0.7371 | 455  | 0.4557          |
| 0.4504        | 0.7582 | 468  | 0.4537          |
| 0.4436        | 0.7793 | 481  | 0.4525          |
| 0.4451        | 0.8003 | 494  | 0.4497          |
| 0.435         | 0.8214 | 507  | 0.4482          |
| 0.4247        | 0.8424 | 520  | 0.4466          |
| 0.4295        | 0.8635 | 533  | 0.4455          |
| 0.4204        | 0.8846 | 546  | 0.4444          |
| 0.4381        | 0.9056 | 559  | 0.4433          |
| 0.4355        | 0.9267 | 572  | 0.4430          |
| 0.4234        | 0.9478 | 585  | 0.4424          |
| 0.4261        | 0.9688 | 598  | 0.4421          |
| 0.4266        | 0.9899 | 611  | 0.4421          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1