vicuna-ul15-sft-full
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4380
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 |
|---|---|---|---|
| 1.0541 | 0.68 | 14 | 1.0341 |
| 0.9708 | 1.71 | 29 | 1.0142 |
| 0.9142 | 2.68 | 43 | 1.0111 |
| 0.8637 | 3.71 | 58 | 1.0239 |
| 0.8091 | 4.68 | 72 | 1.0363 |
| 0.7516 | 5.71 | 87 | 1.0780 |
| 0.6884 | 6.68 | 101 | 1.0987 |
| 0.6309 | 7.71 | 116 | 1.1394 |
| 0.5696 | 8.68 | 130 | 1.1820 |
| 0.4752 | 9.71 | 145 | 1.2695 |
| 0.448 | 10.68 | 159 | 1.3109 |
| 0.3955 | 11.71 | 174 | 1.3877 |
| 0.3579 | 12.68 | 188 | 1.3923 |
| 0.3228 | 13.71 | 203 | 1.4064 |
| 0.2914 | 14.68 | 217 | 1.4377 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0a0+32f93b1
- Datasets 2.14.6
- Tokenizers 0.14.1
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