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guten-norm-rarity-neg-log-rarity
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.1107
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 |
|---|---|---|---|
| 6.3407 | 0.29 | 500 | 5.3403 |
| 5.0363 | 0.58 | 1000 | 4.9281 |
| 4.7047 | 0.87 | 1500 | 4.6892 |
| 4.456 | 1.16 | 2000 | 4.5421 |
| 4.2921 | 1.46 | 2500 | 4.4253 |
| 4.1945 | 1.75 | 3000 | 4.3302 |
| 4.0814 | 2.04 | 3500 | 4.2597 |
| 3.8936 | 2.33 | 4000 | 4.2144 |
| 3.8707 | 2.62 | 4500 | 4.1569 |
| 3.8311 | 2.91 | 5000 | 4.1047 |
| 3.6493 | 3.2 | 5500 | 4.1017 |
| 3.5826 | 3.49 | 6000 | 4.0733 |
| 3.5726 | 3.79 | 6500 | 4.0444 |
| 3.4853 | 4.08 | 7000 | 4.0363 |
| 3.3169 | 4.37 | 7500 | 4.0333 |
| 3.3077 | 4.66 | 8000 | 4.0194 |
| 3.3047 | 4.95 | 8500 | 4.0076 |
| 3.1635 | 5.24 | 9000 | 4.0197 |
| 3.1267 | 5.53 | 9500 | 4.0199 |
| 3.1356 | 5.82 | 10000 | 4.0187 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
