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---
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_ortho
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_ortho
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: 3.7040
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.7777 | 0.0211 | 13 | 0.8341 |
| 7.0293 | 0.0421 | 26 | 6.8513 |
| 6.701 | 0.0632 | 39 | 6.3677 |
| 6.2243 | 0.0842 | 52 | 6.0330 |
| 5.8724 | 0.1053 | 65 | 5.7326 |
| 5.6516 | 0.1264 | 78 | 5.5358 |
| 5.4706 | 0.1474 | 91 | 5.4924 |
| 5.4721 | 0.1685 | 104 | 5.4835 |
| 5.3039 | 0.1896 | 117 | 5.2730 |
| 5.2205 | 0.2106 | 130 | 5.3434 |
| 5.2713 | 0.2317 | 143 | 5.1822 |
| 5.3149 | 0.2527 | 156 | 5.1724 |
| 5.0644 | 0.2738 | 169 | 4.9613 |
| 4.9846 | 0.2949 | 182 | 4.9757 |
| 5.0517 | 0.3159 | 195 | 4.9266 |
| 4.865 | 0.3370 | 208 | 4.8010 |
| 4.7282 | 0.3580 | 221 | 4.6863 |
| 4.7043 | 0.3791 | 234 | 4.8179 |
| 4.625 | 0.4002 | 247 | 4.7745 |
| 4.6588 | 0.4212 | 260 | 4.5501 |
| 4.5945 | 0.4423 | 273 | 4.6777 |
| 4.5486 | 0.4633 | 286 | 4.4474 |
| 4.5306 | 0.4844 | 299 | 4.2966 |
| 4.2913 | 0.5055 | 312 | 4.3590 |
| 4.2849 | 0.5265 | 325 | 4.2581 |
| 4.2128 | 0.5476 | 338 | 4.2430 |
| 4.2097 | 0.5687 | 351 | 4.1542 |
| 4.1464 | 0.5897 | 364 | 4.0493 |
| 4.0945 | 0.6108 | 377 | 4.1035 |
| 4.1179 | 0.6318 | 390 | 4.0137 |
| 3.985 | 0.6529 | 403 | 4.0483 |
| 3.8947 | 0.6740 | 416 | 3.9081 |
| 3.9839 | 0.6950 | 429 | 3.9723 |
| 3.9361 | 0.7161 | 442 | 3.9275 |
| 3.8458 | 0.7371 | 455 | 3.8235 |
| 3.8545 | 0.7582 | 468 | 3.8504 |
| 3.7774 | 0.7793 | 481 | 3.8078 |
| 3.8065 | 0.8003 | 494 | 3.8017 |
| 3.7724 | 0.8214 | 507 | 3.7487 |
| 3.7569 | 0.8424 | 520 | 3.7663 |
| 3.742 | 0.8635 | 533 | 3.7698 |
| 3.7114 | 0.8846 | 546 | 3.7603 |
| 3.7752 | 0.9056 | 559 | 3.7105 |
| 3.6945 | 0.9267 | 572 | 3.7041 |
| 3.6581 | 0.9478 | 585 | 3.7017 |
| 3.6615 | 0.9688 | 598 | 3.7050 |
| 3.6688 | 0.9899 | 611 | 3.7040 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |