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all-base
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.0367
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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 6.355 | 0.29 | 500 | 5.3170 |
| 5.0354 | 0.58 | 1000 | 4.8924 |
| 4.6989 | 0.87 | 1500 | 4.6507 |
| 4.4441 | 1.16 | 2000 | 4.5047 |
| 4.2822 | 1.45 | 2500 | 4.3873 |
| 4.1851 | 1.74 | 3000 | 4.2815 |
| 4.0807 | 2.02 | 3500 | 4.2026 |
| 3.8813 | 2.31 | 4000 | 4.1635 |
| 3.8547 | 2.6 | 4500 | 4.1118 |
| 3.8136 | 2.89 | 5000 | 4.0571 |
| 3.646 | 3.18 | 5500 | 4.0499 |
| 3.5714 | 3.47 | 6000 | 4.0237 |
| 3.5592 | 3.76 | 6500 | 3.9907 |
| 3.4929 | 4.05 | 7000 | 3.9792 |
| 3.3028 | 4.34 | 7500 | 3.9795 |
| 3.2966 | 4.63 | 8000 | 3.9665 |
| 3.2851 | 4.92 | 8500 | 3.9538 |
| 3.1662 | 5.21 | 9000 | 3.9633 |
| 3.1138 | 5.49 | 9500 | 3.9624 |
| 3.1152 | 5.78 | 10000 | 3.9615 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
