---
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_ortho_eye
  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_ortho_eye

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: 0.4403

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.7124        | 0.0211 | 13   | 0.5905          |
| 0.5476        | 0.0421 | 26   | 0.5631          |
| 0.5329        | 0.0632 | 39   | 0.5495          |
| 0.523         | 0.0842 | 52   | 0.5404          |
| 0.5078        | 0.1053 | 65   | 0.5362          |
| 0.5097        | 0.1264 | 78   | 0.5276          |
| 0.494         | 0.1474 | 91   | 0.5230          |
| 0.5066        | 0.1685 | 104  | 0.5173          |
| 0.4881        | 0.1896 | 117  | 0.5167          |
| 0.4963        | 0.2106 | 130  | 0.5138          |
| 0.4841        | 0.2317 | 143  | 0.5092          |
| 0.4676        | 0.2527 | 156  | 0.5046          |
| 0.4722        | 0.2738 | 169  | 0.5045          |
| 0.4791        | 0.2949 | 182  | 0.4997          |
| 0.477         | 0.3159 | 195  | 0.4962          |
| 0.4791        | 0.3370 | 208  | 0.4947          |
| 0.4621        | 0.3580 | 221  | 0.4909          |
| 0.4647        | 0.3791 | 234  | 0.4885          |
| 0.4584        | 0.4002 | 247  | 0.4858          |
| 0.4651        | 0.4212 | 260  | 0.4814          |
| 0.4761        | 0.4423 | 273  | 0.4792          |
| 0.4621        | 0.4633 | 286  | 0.4783          |
| 0.4556        | 0.4844 | 299  | 0.4758          |
| 0.4556        | 0.5055 | 312  | 0.4726          |
| 0.4551        | 0.5265 | 325  | 0.4674          |
| 0.4554        | 0.5476 | 338  | 0.4637          |
| 0.4486        | 0.5687 | 351  | 0.4620          |
| 0.4413        | 0.5897 | 364  | 0.4619          |
| 0.4416        | 0.6108 | 377  | 0.4611          |
| 0.4358        | 0.6318 | 390  | 0.4559          |
| 0.4399        | 0.6529 | 403  | 0.4538          |
| 0.4324        | 0.6740 | 416  | 0.4535          |
| 0.4217        | 0.6950 | 429  | 0.4506          |
| 0.4423        | 0.7161 | 442  | 0.4488          |
| 0.4281        | 0.7371 | 455  | 0.4469          |
| 0.4402        | 0.7582 | 468  | 0.4456          |
| 0.4363        | 0.7793 | 481  | 0.4447          |
| 0.4385        | 0.8003 | 494  | 0.4433          |
| 0.429         | 0.8214 | 507  | 0.4435          |
| 0.4199        | 0.8424 | 520  | 0.4421          |
| 0.4223        | 0.8635 | 533  | 0.4415          |
| 0.4158        | 0.8846 | 546  | 0.4412          |
| 0.4369        | 0.9056 | 559  | 0.4408          |
| 0.432         | 0.9267 | 572  | 0.4407          |
| 0.4202        | 0.9478 | 585  | 0.4403          |
| 0.4239        | 0.9688 | 598  | 0.4403          |
| 0.4228        | 0.9899 | 611  | 0.4403          |


### Framework versions

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