vicuna-adv-robust-ul15-sft-full
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6864
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 512
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0543 | 0.61 | 15 | 1.0329 |
| 0.9704 | 1.61 | 30 | 1.0141 |
| 0.9103 | 2.61 | 45 | 1.0125 |
| 0.8485 | 3.61 | 60 | 1.0221 |
| 0.785 | 4.61 | 75 | 1.0448 |
| 0.7207 | 5.61 | 90 | 1.0821 |
| 0.6444 | 6.61 | 105 | 1.1344 |
| 0.5673 | 7.61 | 120 | 1.1993 |
| 0.4883 | 8.61 | 135 | 1.2800 |
| 0.4137 | 9.61 | 150 | 1.3778 |
| 0.345 | 10.61 | 165 | 1.4092 |
| 0.3022 | 11.61 | 180 | 1.5371 |
| 0.2649 | 12.61 | 195 | 1.5054 |
| 0.2272 | 13.61 | 210 | 1.5542 |
| 0.1929 | 14.61 | 225 | 1.6869 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0a0+32f93b1
- Datasets 2.14.6
- Tokenizers 0.14.1
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