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all-base-rerun-new-loop2
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.0969
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 |
|---|---|---|---|
| 6.3479 | 0.29 | 500 | 5.3389 |
| 5.0203 | 0.58 | 1000 | 4.9188 |
| 4.6949 | 0.87 | 1500 | 4.6855 |
| 4.4434 | 1.16 | 2000 | 4.5414 |
| 4.2872 | 1.46 | 2500 | 4.4217 |
| 4.1743 | 1.75 | 3000 | 4.3230 |
| 4.0791 | 2.04 | 3500 | 4.2448 |
| 3.8856 | 2.33 | 4000 | 4.2016 |
| 3.8509 | 2.62 | 4500 | 4.1489 |
| 3.8144 | 2.91 | 5000 | 4.0998 |
| 3.6394 | 3.2 | 5500 | 4.0935 |
| 3.5747 | 3.49 | 6000 | 4.0638 |
| 3.5592 | 3.78 | 6500 | 4.0296 |
| 3.4711 | 4.07 | 7000 | 4.0278 |
| 3.3061 | 4.37 | 7500 | 4.0241 |
| 3.2984 | 4.66 | 8000 | 4.0105 |
| 3.2917 | 4.95 | 8500 | 3.9989 |
| 3.1462 | 5.24 | 9000 | 4.0090 |
| 3.1241 | 5.53 | 9500 | 4.0085 |
| 3.1176 | 5.82 | 10000 | 4.0075 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
