| --- |
| library_name: peft |
| license: llama3 |
| base_model: meta-llama/Meta-Llama-3-8B-Instruct |
| tags: |
| - llama-factory |
| - lntuning |
| - generated_from_trainer |
| model-index: |
| - name: train_codealpacapy_456_1765320135 |
| 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. --> |
|
|
| # train_codealpacapy_456_1765320135 |
| |
| This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the codealpacapy dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4469 |
| - Num Input Tokens Seen: 24973864 |
| |
| ## 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: 5e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 456 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 20 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Input Tokens Seen | |
| |:-------------:|:-----:|:-----:|:---------------:|:-----------------:| |
| | 0.6003 | 1.0 | 1908 | 0.5420 | 1246832 | |
| | 0.562 | 2.0 | 3816 | 0.4901 | 2497936 | |
| | 0.4684 | 3.0 | 5724 | 0.4709 | 3743760 | |
| | 0.4606 | 4.0 | 7632 | 0.4625 | 4991472 | |
| | 1.1977 | 5.0 | 9540 | 0.4581 | 6239608 | |
| | 0.4325 | 6.0 | 11448 | 0.4543 | 7485248 | |
| | 0.6624 | 7.0 | 13356 | 0.4522 | 8733024 | |
| | 0.6294 | 8.0 | 15264 | 0.4506 | 9983720 | |
| | 0.3541 | 9.0 | 17172 | 0.4490 | 11229792 | |
| | 0.3995 | 10.0 | 19080 | 0.4484 | 12476552 | |
| | 0.4189 | 11.0 | 20988 | 0.4486 | 13725560 | |
| | 0.4387 | 12.0 | 22896 | 0.4477 | 14977976 | |
| | 0.4162 | 13.0 | 24804 | 0.4474 | 16225896 | |
| | 0.4816 | 14.0 | 26712 | 0.4473 | 17477224 | |
| | 0.4314 | 15.0 | 28620 | 0.4472 | 18726216 | |
| | 0.316 | 16.0 | 30528 | 0.4469 | 19973408 | |
| | 0.3909 | 17.0 | 32436 | 0.4470 | 21226656 | |
| | 0.4489 | 18.0 | 34344 | 0.4469 | 22472696 | |
| | 0.4458 | 19.0 | 36252 | 0.4472 | 23722376 | |
| | 0.7972 | 20.0 | 38160 | 0.4471 | 24973864 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.15.2 |
| - Transformers 4.51.3 |
| - Pytorch 2.8.0+cu128 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.1 |
