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all_base_rarity_neg_log_rarity_end_741k
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.8671
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 |
|---|---|---|---|
| 6.4906 | 0.31 | 500 | 5.4669 |
| 5.2076 | 0.63 | 1000 | 5.1437 |
| 4.87 | 0.94 | 1500 | 4.9598 |
| 4.6172 | 1.25 | 2000 | 4.8891 |
| 4.4849 | 1.56 | 2500 | 4.8300 |
| 4.4021 | 1.88 | 3000 | 4.7820 |
| 4.2252 | 2.19 | 3500 | 4.7630 |
| 4.1425 | 2.5 | 4000 | 4.7363 |
| 4.1066 | 2.82 | 4500 | 4.7162 |
| 3.9802 | 3.13 | 5000 | 4.7825 |
| 3.8516 | 3.44 | 5500 | 4.7281 |
| 3.8357 | 3.75 | 6000 | 4.7188 |
| 3.7569 | 4.07 | 6500 | 4.7577 |
| 3.5751 | 4.38 | 7000 | 4.7621 |
| 3.5688 | 4.69 | 7500 | 4.7682 |
| 3.5543 | 5.01 | 8000 | 4.7887 |
| 3.3919 | 5.32 | 8500 | 4.8024 |
| 3.3784 | 5.63 | 9000 | 4.8136 |
| 3.3809 | 5.94 | 9500 | 4.8139 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
