Llama-360M
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.1685
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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 8.4647 | 0.98 | 7 | 8.5154 |
| 7.2112 | 1.96 | 14 | 7.6819 |
| 6.3283 | 2.95 | 21 | 6.9987 |
| 5.5163 | 3.93 | 28 | 6.4019 |
| 4.7022 | 4.91 | 35 | 5.8715 |
| 3.7692 | 5.89 | 42 | 5.4877 |
| 3.2137 | 6.88 | 49 | 5.2686 |
| 2.6388 | 8.0 | 57 | 5.1854 |
| 2.0768 | 8.98 | 64 | 5.1622 |
| 1.715 | 9.82 | 70 | 5.1685 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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