---
base_model: unsloth/mistral-7b-v0.3
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Mistral-7B-v0.3_metamath_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-v0.3_metamath_reverse

This model is a fine-tuned version of [unsloth/mistral-7b-v0.3](https://huggingface.co/unsloth/mistral-7b-v0.3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.4642

## 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: 0.0003
- 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_ratio: 0.02
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7438        | 0.0211 | 13   | 8.7190          |
| 10.0767       | 0.0421 | 26   | 7.4982          |
| 7.2515        | 0.0632 | 39   | 6.8837          |
| 6.576         | 0.0842 | 52   | 6.7953          |
| 6.2957        | 0.1053 | 65   | 6.2733          |
| 6.0661        | 0.1264 | 78   | 6.0673          |
| 5.9255        | 0.1474 | 91   | 5.8718          |
| 5.8505        | 0.1685 | 104  | 5.7501          |
| 5.8001        | 0.1896 | 117  | 5.7454          |
| 5.6299        | 0.2106 | 130  | 5.6950          |
| 5.5865        | 0.2317 | 143  | 5.5759          |
| 5.5062        | 0.2527 | 156  | 5.4837          |
| 5.4305        | 0.2738 | 169  | 5.4409          |
| 5.4209        | 0.2949 | 182  | 5.4429          |
| 5.4976        | 0.3159 | 195  | 5.4370          |
| 5.3972        | 0.3370 | 208  | 5.4192          |
| 5.2896        | 0.3580 | 221  | 5.3299          |
| 5.2499        | 0.3791 | 234  | 5.3241          |
| 5.2422        | 0.4002 | 247  | 5.2642          |
| 5.2269        | 0.4212 | 260  | 5.1857          |
| 5.1564        | 0.4423 | 273  | 5.1017          |
| 5.1019        | 0.4633 | 286  | 5.0316          |
| 5.0642        | 0.4844 | 299  | 5.0160          |
| 4.9382        | 0.5055 | 312  | 4.9836          |
| 4.8985        | 0.5265 | 325  | 4.9845          |
| 4.8274        | 0.5476 | 338  | 4.8632          |
| 4.8791        | 0.5687 | 351  | 4.8729          |
| 4.8399        | 0.5897 | 364  | 4.8246          |
| 4.843         | 0.6108 | 377  | 4.7545          |
| 4.78          | 0.6318 | 390  | 4.7345          |
| 4.6772        | 0.6529 | 403  | 4.7334          |
| 4.6519        | 0.6740 | 416  | 4.6307          |
| 4.6692        | 0.6950 | 429  | 4.6488          |
| 4.6636        | 0.7161 | 442  | 4.6318          |
| 4.5804        | 0.7371 | 455  | 4.5739          |
| 4.566         | 0.7582 | 468  | 4.5556          |
| 4.5466        | 0.7793 | 481  | 4.5450          |
| 4.5555        | 0.8003 | 494  | 4.5170          |
| 4.5352        | 0.8214 | 507  | 4.5036          |
| 4.5827        | 0.8424 | 520  | 4.4868          |
| 4.5218        | 0.8635 | 533  | 4.5077          |
| 4.4692        | 0.8846 | 546  | 4.5098          |
| 4.522         | 0.9056 | 559  | 4.4963          |
| 4.5072        | 0.9267 | 572  | 4.4704          |
| 4.4346        | 0.9478 | 585  | 4.4707          |
| 4.4893        | 0.9688 | 598  | 4.4659          |
| 4.4587        | 0.9899 | 611  | 4.4642          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1