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all-base-rerun-new-loop
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.0966
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 |
|---|---|---|---|
| 6.3514 | 0.29 | 500 | 5.3344 |
| 5.0244 | 0.58 | 1000 | 4.9301 |
| 4.6948 | 0.87 | 1500 | 4.6847 |
| 4.4421 | 1.16 | 2000 | 4.5356 |
| 4.285 | 1.46 | 2500 | 4.4193 |
| 4.1724 | 1.75 | 3000 | 4.3179 |
| 4.0767 | 2.04 | 3500 | 4.2422 |
| 3.883 | 2.33 | 4000 | 4.1998 |
| 3.8483 | 2.62 | 4500 | 4.1495 |
| 3.8125 | 2.91 | 5000 | 4.0986 |
| 3.6378 | 3.2 | 5500 | 4.0910 |
| 3.5732 | 3.49 | 6000 | 4.0640 |
| 3.5575 | 3.78 | 6500 | 4.0288 |
| 3.4696 | 4.07 | 7000 | 4.0250 |
| 3.3036 | 4.37 | 7500 | 4.0232 |
| 3.2977 | 4.66 | 8000 | 4.0094 |
| 3.2899 | 4.95 | 8500 | 3.9977 |
| 3.1442 | 5.24 | 9000 | 4.0094 |
| 3.1227 | 5.53 | 9500 | 4.0079 |
| 3.1169 | 5.82 | 10000 | 4.0071 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
