metadata
base_model: unsloth/llama-3-8b
library_name: peft
license: llama3
tags:
- unsloth
- generated_from_trainer
model-index:
- name: Meta-Llama-3-8B_metamath_reverse
results: []
Meta-Llama-3-8B_metamath_reverse
This model is a fine-tuned version of unsloth/llama-3-8b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5067
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 |
|---|---|---|---|
| 0.8667 | 0.0211 | 13 | 0.7332 |
| 0.7009 | 0.0421 | 26 | 0.7322 |
| 0.7161 | 0.0632 | 39 | 0.7229 |
| 0.6909 | 0.0842 | 52 | 0.7190 |
| 0.6541 | 0.1053 | 65 | 0.7083 |
| 0.6704 | 0.1264 | 78 | 0.7014 |
| 0.6806 | 0.1474 | 91 | 0.6999 |
| 0.6735 | 0.1685 | 104 | 0.6932 |
| 0.6509 | 0.1896 | 117 | 0.6962 |
| 0.6537 | 0.2106 | 130 | 0.6907 |
| 0.6508 | 0.2317 | 143 | 0.6892 |
| 0.6594 | 0.2527 | 156 | 0.6816 |
| 0.6534 | 0.2738 | 169 | 0.6734 |
| 0.6559 | 0.2949 | 182 | 0.6744 |
| 0.6391 | 0.3159 | 195 | 0.6739 |
| 0.6115 | 0.3370 | 208 | 0.6628 |
| 0.6261 | 0.3580 | 221 | 0.6548 |
| 0.6288 | 0.3791 | 234 | 0.6545 |
| 0.6377 | 0.4002 | 247 | 0.6510 |
| 0.6106 | 0.4212 | 260 | 0.6465 |
| 0.6203 | 0.4423 | 273 | 0.6377 |
| 0.6196 | 0.4633 | 286 | 0.6276 |
| 0.6146 | 0.4844 | 299 | 0.6216 |
| 0.5931 | 0.5055 | 312 | 0.6187 |
| 0.5926 | 0.5265 | 325 | 0.6058 |
| 0.5807 | 0.5476 | 338 | 0.6018 |
| 0.5738 | 0.5687 | 351 | 0.5915 |
| 0.5509 | 0.5897 | 364 | 0.5852 |
| 0.5641 | 0.6108 | 377 | 0.5815 |
| 0.5606 | 0.6318 | 390 | 0.5723 |
| 0.5478 | 0.6529 | 403 | 0.5653 |
| 0.5451 | 0.6740 | 416 | 0.5613 |
| 0.5362 | 0.6950 | 429 | 0.5556 |
| 0.5328 | 0.7161 | 442 | 0.5474 |
| 0.5185 | 0.7371 | 455 | 0.5413 |
| 0.5127 | 0.7582 | 468 | 0.5359 |
| 0.5036 | 0.7793 | 481 | 0.5299 |
| 0.4922 | 0.8003 | 494 | 0.5265 |
| 0.5246 | 0.8214 | 507 | 0.5219 |
| 0.5088 | 0.8424 | 520 | 0.5175 |
| 0.4908 | 0.8635 | 533 | 0.5150 |
| 0.5091 | 0.8846 | 546 | 0.5120 |
| 0.4902 | 0.9056 | 559 | 0.5096 |
| 0.4865 | 0.9267 | 572 | 0.5083 |
| 0.5007 | 0.9478 | 585 | 0.5072 |
| 0.5001 | 0.9688 | 598 | 0.5068 |
| 0.4989 | 0.9899 | 611 | 0.5067 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1