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gpt2-cl-concat-rarity-mod-datasets-6
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.8004
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: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 6.6082 | 0.06 | 500 | 5.8581 |
| 5.3496 | 0.11 | 1000 | 5.4574 |
| 5.0066 | 0.17 | 1500 | 5.2413 |
| 4.7806 | 0.22 | 2000 | 5.1099 |
| 4.6202 | 0.28 | 2500 | 5.0191 |
| 4.4997 | 0.33 | 3000 | 4.9599 |
| 4.3878 | 0.39 | 3500 | 4.9168 |
| 4.2858 | 0.44 | 4000 | 4.8861 |
| 4.1858 | 0.5 | 4500 | 4.8493 |
| 4.0947 | 0.55 | 5000 | 4.8152 |
| 4.0087 | 0.61 | 5500 | 4.8013 |
| 3.9228 | 0.66 | 6000 | 4.7840 |
| 3.8464 | 0.72 | 6500 | 4.7652 |
| 3.7884 | 0.78 | 7000 | 4.7589 |
| 3.7366 | 0.83 | 7500 | 4.7531 |
| 3.7018 | 0.89 | 8000 | 4.7470 |
| 3.6791 | 0.94 | 8500 | 4.7431 |
| 3.6709 | 1.0 | 9000 | 4.7433 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
