full-policy-tldr-llama3.1-1b
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: 0.8639
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 |
|---|---|---|---|
| 0.8779 | 1.0000 | 7295 | 0.8575 |
| 0.8714 | 1.9999 | 14590 | 0.8699 |
| 0.8589 | 2.9999 | 21885 | 0.8682 |
| 0.8574 | 4.0 | 29181 | 0.8669 |
| 0.8565 | 5.0000 | 36476 | 0.8659 |
| 0.8556 | 5.9999 | 43771 | 0.8651 |
| 0.855 | 6.9999 | 51066 | 0.8646 |
| 0.8545 | 8.0 | 58362 | 0.8642 |
| 0.8544 | 9.0000 | 65657 | 0.8640 |
| 0.8542 | 9.9997 | 72950 | 0.8639 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1
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Base model
meta-llama/Llama-3.2-1B