---
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_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-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: 4.0369

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.7562        | 0.0211 | 13   | 8.8561          |
| 8.5861        | 0.0421 | 26   | 6.7147          |
| 6.683         | 0.0632 | 39   | 6.4347          |
| 6.3623        | 0.0842 | 52   | 6.2959          |
| 6.1966        | 0.1053 | 65   | 6.1023          |
| 5.9253        | 0.1264 | 78   | 5.8562          |
| 5.6996        | 0.1474 | 91   | 5.7402          |
| 5.654         | 0.1685 | 104  | 5.5460          |
| 5.4346        | 0.1896 | 117  | 5.3902          |
| 5.2399        | 0.2106 | 130  | 5.1306          |
| 5.1411        | 0.2317 | 143  | 5.0223          |
| 5.0468        | 0.2527 | 156  | 4.9554          |
| 4.9675        | 0.2738 | 169  | 4.8488          |
| 4.8723        | 0.2949 | 182  | 4.9092          |
| 4.9509        | 0.3159 | 195  | 4.6985          |
| 4.7385        | 0.3370 | 208  | 4.7031          |
| 4.631         | 0.3580 | 221  | 4.6471          |
| 4.6294        | 0.3791 | 234  | 4.6124          |
| 4.5562        | 0.4002 | 247  | 4.5880          |
| 4.5684        | 0.4212 | 260  | 4.5116          |
| 4.5965        | 0.4423 | 273  | 4.5065          |
| 4.594         | 0.4633 | 286  | 4.4330          |
| 4.5223        | 0.4844 | 299  | 4.4393          |
| 4.4033        | 0.5055 | 312  | 4.4070          |
| 4.3706        | 0.5265 | 325  | 4.3485          |
| 4.3595        | 0.5476 | 338  | 4.3587          |
| 4.3865        | 0.5687 | 351  | 4.2940          |
| 4.342         | 0.5897 | 364  | 4.3082          |
| 4.2976        | 0.6108 | 377  | 4.2683          |
| 4.3627        | 0.6318 | 390  | 4.2331          |
| 4.2364        | 0.6529 | 403  | 4.2331          |
| 4.1543        | 0.6740 | 416  | 4.1827          |
| 4.2475        | 0.6950 | 429  | 4.2243          |
| 4.2247        | 0.7161 | 442  | 4.1690          |
| 4.1115        | 0.7371 | 455  | 4.1257          |
| 4.1388        | 0.7582 | 468  | 4.1157          |
| 4.0912        | 0.7793 | 481  | 4.1659          |
| 4.0903        | 0.8003 | 494  | 4.0926          |
| 4.1036        | 0.8214 | 507  | 4.0859          |
| 4.0692        | 0.8424 | 520  | 4.0732          |
| 4.0634        | 0.8635 | 533  | 4.0823          |
| 4.0463        | 0.8846 | 546  | 4.0597          |
| 4.0948        | 0.9056 | 559  | 4.0447          |
| 4.0496        | 0.9267 | 572  | 4.0293          |
| 3.9855        | 0.9478 | 585  | 4.0449          |
| 4.0289        | 0.9688 | 598  | 4.0360          |
| 4.0147        | 0.9899 | 611  | 4.0369          |


### Framework versions

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