Llama-360M
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.3269
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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- num_epochs: 40
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 9.6295 | 0.57 | 1 | 9.6320 |
| 9.4685 | 1.71 | 3 | 9.4277 |
| 8.7308 | 2.86 | 5 | 8.9834 |
| 7.7978 | 4.0 | 7 | 8.3652 |
| 7.4895 | 4.57 | 8 | 8.1048 |
| 6.9772 | 5.71 | 10 | 7.7260 |
| 6.6117 | 6.86 | 12 | 7.4107 |
| 6.2461 | 8.0 | 14 | 7.1384 |
| 6.0376 | 8.57 | 15 | 6.9993 |
| 5.6415 | 9.71 | 17 | 6.7886 |
| 5.3502 | 10.86 | 19 | 6.6009 |
| 5.0627 | 12.0 | 21 | 6.4227 |
| 4.9292 | 12.57 | 22 | 6.3169 |
| 4.5619 | 13.71 | 24 | 6.1217 |
| 4.1745 | 14.86 | 26 | 5.9089 |
| 3.895 | 16.0 | 28 | 5.7244 |
| 3.7108 | 16.57 | 29 | 5.6837 |
| 3.4811 | 17.71 | 31 | 5.5533 |
| 3.3174 | 18.86 | 33 | 5.4525 |
| 3.0011 | 20.0 | 35 | 5.4535 |
| 2.8812 | 20.57 | 36 | 5.4168 |
| 2.6512 | 21.71 | 38 | 5.4168 |
| 2.3009 | 22.86 | 40 | 5.3269 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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