Llama-3.2-3B-Danoia
Der er ikke meget at sige andet end at den kan dansk.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 2
- eval_batch_size: 1
- seed: 222
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.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: 0.01
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0895 | 0.2103 | 500 | 1.0488 |
| 1.0893 | 0.4205 | 1000 | 0.9952 |
| 0.864 | 0.6308 | 1500 | 0.9645 |
| 0.9665 | 0.8411 | 2000 | 0.9406 |
| 0.9387 | 1.0514 | 2500 | 0.9242 |
| 0.7996 | 1.2617 | 3000 | 0.9126 |
| 0.7904 | 1.4720 | 3500 | 0.9005 |
| 0.9745 | 1.6822 | 4000 | 0.8926 |
| 1.0152 | 1.8925 | 4500 | 0.8859 |
| 0.7676 | 2.1028 | 5000 | 0.8821 |
| 0.8127 | 2.3131 | 5500 | 0.8791 |
| 0.9498 | 2.5234 | 6000 | 0.8770 |
| 0.795 | 2.7336 | 6500 | 0.8758 |
| 0.8029 | 2.9439 | 7000 | 0.8758 |
Framework versions
- PEFT 0.11.1
- Transformers 4.46.1
- Pytorch 2.5.1
- Datasets 2.20.0
- Tokenizers 0.20.3