shawgpt-ft
This model is a fine-tuned version of meta-llama/Llama-3.2-1B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.9054
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.0948 | 0.9231 | 3 | 3.5602 |
| 3.989 | 1.8462 | 6 | 3.4689 |
| 3.8695 | 2.7692 | 9 | 3.3643 |
| 2.7993 | 4.0 | 13 | 3.2266 |
| 3.6082 | 4.9231 | 16 | 3.1340 |
| 3.4814 | 5.8462 | 19 | 3.0544 |
| 3.3948 | 6.7692 | 22 | 2.9899 |
| 2.4744 | 8.0 | 26 | 2.9295 |
| 3.2539 | 8.9231 | 29 | 2.9079 |
| 2.2491 | 9.2308 | 30 | 2.9054 |
Framework versions
- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.19.1
- Downloads last month
- 4
Model tree for hj21/shawgpt-ft
Base model
meta-llama/Llama-3.2-1B