metadata
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_123_1762561812
results: []
train_codealpacapy_123_1762561812
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the codealpacapy dataset. It achieves the following results on the evaluation set:
- Loss: 0.4750
- Num Input Tokens Seen: 24941912
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: 123
- 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 |
|---|---|---|---|---|
| 0.6523 | 1.0 | 1908 | 0.5841 | 1248304 |
| 0.4842 | 2.0 | 3816 | 0.5255 | 2497016 |
| 0.4395 | 3.0 | 5724 | 0.5037 | 3742552 |
| 0.4343 | 4.0 | 7632 | 0.4937 | 4985200 |
| 0.4944 | 5.0 | 9540 | 0.4878 | 6233920 |
| 0.483 | 6.0 | 11448 | 0.4841 | 7478504 |
| 0.4485 | 7.0 | 13356 | 0.4816 | 8722744 |
| 0.7736 | 8.0 | 15264 | 0.4795 | 9977520 |
| 0.471 | 9.0 | 17172 | 0.4779 | 11225416 |
| 0.6523 | 10.0 | 19080 | 0.4767 | 12472912 |
| 0.5687 | 11.0 | 20988 | 0.4762 | 13721824 |
| 0.4424 | 12.0 | 22896 | 0.4755 | 14970528 |
| 0.5622 | 13.0 | 24804 | 0.4754 | 16220808 |
| 0.3655 | 14.0 | 26712 | 0.4759 | 17464792 |
| 0.3788 | 15.0 | 28620 | 0.4752 | 18706976 |
| 0.3818 | 16.0 | 30528 | 0.4753 | 19956544 |
| 0.4117 | 17.0 | 32436 | 0.4751 | 21204416 |
| 0.4239 | 18.0 | 34344 | 0.4751 | 22451928 |
| 0.3768 | 19.0 | 36252 | 0.4752 | 23696296 |
| 0.614 | 20.0 | 38160 | 0.4750 | 24941912 |
Framework versions
- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1