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all-base-norm-rarity-neg-log-rarity-rev-no-suffle
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.8432
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 |
|---|---|---|---|
| 6.4792 | 0.31 | 500 | 5.4448 |
| 5.2045 | 0.62 | 1000 | 5.1326 |
| 4.869 | 0.94 | 1500 | 4.9589 |
| 4.609 | 1.25 | 2000 | 4.8813 |
| 4.4917 | 1.56 | 2500 | 4.8666 |
| 4.3983 | 1.87 | 3000 | 4.7773 |
| 4.2308 | 2.19 | 3500 | 4.7778 |
| 4.1415 | 2.5 | 4000 | 4.7483 |
| 4.1044 | 2.81 | 4500 | 4.7172 |
| 3.9833 | 3.12 | 5000 | 4.7315 |
| 3.8538 | 3.44 | 5500 | 4.7307 |
| 3.8318 | 3.75 | 6000 | 4.7327 |
| 3.7639 | 4.06 | 6500 | 4.7452 |
| 3.5741 | 4.37 | 7000 | 4.7630 |
| 3.5673 | 4.68 | 7500 | 4.7671 |
| 3.5521 | 5.0 | 8000 | 4.7598 |
| 3.3868 | 5.31 | 8500 | 4.7824 |
| 3.3779 | 5.62 | 9000 | 4.7886 |
| 3.3821 | 5.93 | 9500 | 4.7884 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
