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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: 3.8319
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.7761 | 0.0211 | 13 | 0.8475 |
| 5.7285 | 0.0421 | 26 | 7.1242 |
| 6.6463 | 0.0632 | 39 | 6.4624 |
| 6.3183 | 0.0842 | 52 | 6.2700 |
| 6.3056 | 0.1053 | 65 | 6.3511 |
| 6.2849 | 0.1264 | 78 | 6.2801 |
| 6.2952 | 0.1474 | 91 | 6.3205 |
| 6.2939 | 0.1685 | 104 | 6.3566 |
| 6.2779 | 0.1896 | 117 | 6.2580 |
| 6.087 | 0.2106 | 130 | 5.9797 |
| 5.8495 | 0.2317 | 143 | 5.8683 |
| 5.6782 | 0.2527 | 156 | 5.5177 |
| 5.4335 | 0.2738 | 169 | 5.3885 |
| 5.4451 | 0.2949 | 182 | 5.7948 |
| 5.5833 | 0.3159 | 195 | 5.2887 |
| 5.2684 | 0.3370 | 208 | 5.3036 |
| 5.1159 | 0.3580 | 221 | 5.1110 |
| 5.0046 | 0.3791 | 234 | 4.9806 |
| 4.9134 | 0.4002 | 247 | 4.9382 |
| 4.9145 | 0.4212 | 260 | 4.9544 |
| 4.7976 | 0.4423 | 273 | 4.7954 |
| 4.7328 | 0.4633 | 286 | 4.6897 |
| 4.6799 | 0.4844 | 299 | 4.5793 |
| 4.5047 | 0.5055 | 312 | 4.6603 |
| 4.529 | 0.5265 | 325 | 4.4405 |
| 4.3835 | 0.5476 | 338 | 4.3916 |
| 4.4279 | 0.5687 | 351 | 4.2860 |
| 4.3177 | 0.5897 | 364 | 4.3171 |
| 4.39 | 0.6108 | 377 | 4.3272 |
| 4.3138 | 0.6318 | 390 | 4.3753 |
| 4.2269 | 0.6529 | 403 | 4.3339 |
| 4.1075 | 0.6740 | 416 | 4.1693 |
| 4.2285 | 0.6950 | 429 | 4.1187 |
| 4.1297 | 0.7161 | 442 | 4.1251 |
| 4.0021 | 0.7371 | 455 | 4.0365 |
| 4.0089 | 0.7582 | 468 | 4.0025 |
| 3.9458 | 0.7793 | 481 | 3.9924 |
| 3.9405 | 0.8003 | 494 | 3.9254 |
| 3.9594 | 0.8214 | 507 | 3.8890 |
| 3.9056 | 0.8424 | 520 | 3.8774 |
| 3.8639 | 0.8635 | 533 | 3.8758 |
| 3.8543 | 0.8846 | 546 | 3.8680 |
| 3.9097 | 0.9056 | 559 | 3.8502 |
| 3.8503 | 0.9267 | 572 | 3.8287 |
| 3.789 | 0.9478 | 585 | 3.8357 |
| 3.7923 | 0.9688 | 598 | 3.8299 |
| 3.8071 | 0.9899 | 611 | 3.8319 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |