tinyllama_sft_full
This model is a fine-tuned version of TinyLlama/TinyLlama-1.1B-step-50K-105b on the jailbreak_attack_sft_data_12197 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0074
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: 0.0001
- train_batch_size: 14
- eval_batch_size: 10
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 56
- total_eval_batch_size: 40
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 8.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0109 | 1.8692 | 400 | 0.0107 |
| 0.0068 | 3.7383 | 800 | 0.0079 |
| 0.0059 | 5.6075 | 1200 | 0.0075 |
| 0.0053 | 7.4766 | 1600 | 0.0074 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.21.0
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