---
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: 0.4730

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.8354        | 0.0211 | 13   | 0.8810          |
| 1.4577        | 0.0421 | 26   | 1.4281          |
| 1.0366        | 0.0632 | 39   | 0.9662          |
| 0.9024        | 0.0842 | 52   | 0.7634          |
| 0.694         | 0.1053 | 65   | 0.7062          |
| 0.665         | 0.1264 | 78   | 0.6924          |
| 0.6381        | 0.1474 | 91   | 0.6665          |
| 0.6481        | 0.1685 | 104  | 0.6725          |
| 0.6394        | 0.1896 | 117  | 0.6697          |
| 0.6486        | 0.2106 | 130  | 0.6728          |
| 0.6381        | 0.2317 | 143  | 0.6631          |
| 0.619         | 0.2527 | 156  | 0.6470          |
| 0.6245        | 0.2738 | 169  | 0.6530          |
| 0.6233        | 0.2949 | 182  | 0.6445          |
| 0.6225        | 0.3159 | 195  | 0.6372          |
| 0.6105        | 0.3370 | 208  | 0.6283          |
| 0.5865        | 0.3580 | 221  | 0.6180          |
| 0.5913        | 0.3791 | 234  | 0.6104          |
| 0.5769        | 0.4002 | 247  | 0.6011          |
| 0.586         | 0.4212 | 260  | 0.6021          |
| 0.5945        | 0.4423 | 273  | 0.5921          |
| 0.57          | 0.4633 | 286  | 0.5869          |
| 0.5636        | 0.4844 | 299  | 0.5772          |
| 0.5563        | 0.5055 | 312  | 0.5713          |
| 0.5516        | 0.5265 | 325  | 0.5655          |
| 0.5505        | 0.5476 | 338  | 0.5615          |
| 0.5421        | 0.5687 | 351  | 0.5520          |
| 0.5225        | 0.5897 | 364  | 0.5431          |
| 0.5207        | 0.6108 | 377  | 0.5374          |
| 0.5163        | 0.6318 | 390  | 0.5351          |
| 0.5169        | 0.6529 | 403  | 0.5262          |
| 0.5023        | 0.6740 | 416  | 0.5203          |
| 0.483         | 0.6950 | 429  | 0.5153          |
| 0.4999        | 0.7161 | 442  | 0.5074          |
| 0.487         | 0.7371 | 455  | 0.5027          |
| 0.4971        | 0.7582 | 468  | 0.4985          |
| 0.4875        | 0.7793 | 481  | 0.4937          |
| 0.4881        | 0.8003 | 494  | 0.4904          |
| 0.4753        | 0.8214 | 507  | 0.4869          |
| 0.4609        | 0.8424 | 520  | 0.4825          |
| 0.4657        | 0.8635 | 533  | 0.4794          |
| 0.4563        | 0.8846 | 546  | 0.4776          |
| 0.4738        | 0.9056 | 559  | 0.4751          |
| 0.4685        | 0.9267 | 572  | 0.4743          |
| 0.4539        | 0.9478 | 585  | 0.4735          |
| 0.4606        | 0.9688 | 598  | 0.4731          |
| 0.457         | 0.9899 | 611  | 0.4730          |


### Framework versions

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