---
base_model: unsloth/mistral-7b-v0.3-bnb-4bit
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Mistral-7B-v0.3_metamath_default
  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_default

This model is a fine-tuned version of [unsloth/mistral-7b-v0.3-bnb-4bit](https://huggingface.co/unsloth/mistral-7b-v0.3-bnb-4bit) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0734

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.7559        | 0.0211 | 13   | 8.3985          |
| 9.4604        | 0.0421 | 26   | 6.8141          |
| 6.7353        | 0.0632 | 39   | 6.4223          |
| 6.4242        | 0.0842 | 52   | 6.2759          |
| 6.1115        | 0.1053 | 65   | 6.0333          |
| 5.9214        | 0.1264 | 78   | 5.8343          |
| 5.6735        | 0.1474 | 91   | 5.5846          |
| 5.557         | 0.1685 | 104  | 5.4916          |
| 5.3297        | 0.1896 | 117  | 5.2345          |
| 5.1963        | 0.2106 | 130  | 5.1310          |
| 5.1252        | 0.2317 | 143  | 5.0674          |
| 4.983         | 0.2527 | 156  | 4.9390          |
| 4.8933        | 0.2738 | 169  | 4.8252          |
| 4.7722        | 0.2949 | 182  | 4.7449          |
| 4.7722        | 0.3159 | 195  | 4.7386          |
| 4.6446        | 0.3370 | 208  | 4.6346          |
| 4.5823        | 0.3580 | 221  | 4.5544          |
| 4.576         | 0.3791 | 234  | 4.5238          |
| 4.5056        | 0.4002 | 247  | 4.6538          |
| 4.5501        | 0.4212 | 260  | 4.4766          |
| 4.5197        | 0.4423 | 273  | 4.4369          |
| 4.6259        | 0.4633 | 286  | 4.4561          |
| 4.546         | 0.4844 | 299  | 4.4278          |
| 4.3478        | 0.5055 | 312  | 4.3790          |
| 4.3754        | 0.5265 | 325  | 4.3635          |
| 4.2714        | 0.5476 | 338  | 4.3611          |
| 4.3724        | 0.5687 | 351  | 4.3629          |
| 4.2961        | 0.5897 | 364  | 4.2578          |
| 4.2806        | 0.6108 | 377  | 4.2863          |
| 4.3088        | 0.6318 | 390  | 4.2221          |
| 4.2165        | 0.6529 | 403  | 4.2158          |
| 4.1776        | 0.6740 | 416  | 4.1896          |
| 4.2615        | 0.6950 | 429  | 4.3146          |
| 4.2536        | 0.7161 | 442  | 4.2153          |
| 4.1308        | 0.7371 | 455  | 4.1701          |
| 4.1749        | 0.7582 | 468  | 4.1346          |
| 4.1219        | 0.7793 | 481  | 4.1276          |
| 4.136         | 0.8003 | 494  | 4.1162          |
| 4.1453        | 0.8214 | 507  | 4.1070          |
| 4.1025        | 0.8424 | 520  | 4.1167          |
| 4.1207        | 0.8635 | 533  | 4.0925          |
| 4.0847        | 0.8846 | 546  | 4.0926          |
| 4.1504        | 0.9056 | 559  | 4.0795          |
| 4.1211        | 0.9267 | 572  | 4.0711          |
| 4.038         | 0.9478 | 585  | 4.0763          |
| 4.0944        | 0.9688 | 598  | 4.0744          |
| 4.0771        | 0.9899 | 611  | 4.0734          |


### Framework versions

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