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This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3728
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: inverse sqrt
- lr_scheduler_warmup_steps: 200
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.9439 | 1.5873 | 100 | 1.8720 |
| 1.6612 | 3.1746 | 200 | 1.5883 |
| 1.3495 | 4.7619 | 300 | 1.4520 |
| 1.1756 | 6.3492 | 400 | 1.3990 |
| 1.0634 | 7.9365 | 500 | 1.3749 |
| 0.9705 | 9.5238 | 600 | 1.3654 |
| 0.9153 | 11.1111 | 700 | 1.3603 |
Framework versions
- PEFT 0.11.1
- Transformers 4.42.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
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