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---
license: llama3
library_name: peft
tags:
- unsloth
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B
model-index:
- name: meta_llama_3_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. -->
# meta_llama_3_MetaMathQA_40K_ortho_eye
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5290
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.8833 | 0.0211 | 13 | 0.6741 |
| 0.6218 | 0.0421 | 26 | 0.6424 |
| 0.6067 | 0.0632 | 39 | 0.6220 |
| 0.5945 | 0.0842 | 52 | 0.6132 |
| 0.5574 | 0.1053 | 65 | 0.6053 |
| 0.5705 | 0.1264 | 78 | 0.5994 |
| 0.5778 | 0.1474 | 91 | 0.5945 |
| 0.5612 | 0.1685 | 104 | 0.5892 |
| 0.5419 | 0.1896 | 117 | 0.5858 |
| 0.5428 | 0.2106 | 130 | 0.5830 |
| 0.5404 | 0.2317 | 143 | 0.5804 |
| 0.549 | 0.2527 | 156 | 0.5767 |
| 0.5448 | 0.2738 | 169 | 0.5722 |
| 0.541 | 0.2949 | 182 | 0.5698 |
| 0.5345 | 0.3159 | 195 | 0.5674 |
| 0.5175 | 0.3370 | 208 | 0.5661 |
| 0.5257 | 0.3580 | 221 | 0.5625 |
| 0.5314 | 0.3791 | 234 | 0.5615 |
| 0.5391 | 0.4002 | 247 | 0.5586 |
| 0.5178 | 0.4212 | 260 | 0.5561 |
| 0.5292 | 0.4423 | 273 | 0.5544 |
| 0.5339 | 0.4633 | 286 | 0.5516 |
| 0.5347 | 0.4844 | 299 | 0.5494 |
| 0.5129 | 0.5055 | 312 | 0.5469 |
| 0.5246 | 0.5265 | 325 | 0.5455 |
| 0.5166 | 0.5476 | 338 | 0.5450 |
| 0.5127 | 0.5687 | 351 | 0.5433 |
| 0.4937 | 0.5897 | 364 | 0.5408 |
| 0.5155 | 0.6108 | 377 | 0.5393 |
| 0.5132 | 0.6318 | 390 | 0.5377 |
| 0.5042 | 0.6529 | 403 | 0.5370 |
| 0.5096 | 0.6740 | 416 | 0.5354 |
| 0.5082 | 0.6950 | 429 | 0.5349 |
| 0.514 | 0.7161 | 442 | 0.5341 |
| 0.5045 | 0.7371 | 455 | 0.5328 |
| 0.4919 | 0.7582 | 468 | 0.5323 |
| 0.4941 | 0.7793 | 481 | 0.5317 |
| 0.4885 | 0.8003 | 494 | 0.5311 |
| 0.5244 | 0.8214 | 507 | 0.5305 |
| 0.5109 | 0.8424 | 520 | 0.5299 |
| 0.4972 | 0.8635 | 533 | 0.5298 |
| 0.5194 | 0.8846 | 546 | 0.5295 |
| 0.4996 | 0.9056 | 559 | 0.5293 |
| 0.4959 | 0.9267 | 572 | 0.5291 |
| 0.5119 | 0.9478 | 585 | 0.5290 |
| 0.5176 | 0.9688 | 598 | 0.5290 |
| 0.5146 | 0.9899 | 611 | 0.5290 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |