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gpt2-concat-switch-rarity-all-no-cut
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.3017
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 |
|---|---|---|---|
| 6.6978 | 0.29 | 500 | 5.6405 |
| 5.3376 | 0.58 | 1000 | 5.2066 |
| 4.9908 | 0.87 | 1500 | 4.9450 |
| 4.7046 | 1.17 | 2000 | 4.7918 |
| 4.5548 | 1.46 | 2500 | 4.6719 |
| 4.4413 | 1.75 | 3000 | 4.5626 |
| 4.3192 | 2.04 | 3500 | 4.4831 |
| 4.1174 | 2.33 | 4000 | 4.4399 |
| 4.0953 | 2.62 | 4500 | 4.3793 |
| 4.0531 | 2.91 | 5000 | 4.3275 |
| 3.8566 | 3.21 | 5500 | 4.3240 |
| 3.7887 | 3.5 | 6000 | 4.2905 |
| 3.7792 | 3.79 | 6500 | 4.2619 |
| 3.694 | 4.08 | 7000 | 4.2518 |
| 3.5088 | 4.37 | 7500 | 4.2484 |
| 3.5009 | 4.66 | 8000 | 4.2368 |
| 3.49 | 4.95 | 8500 | 4.2237 |
| 3.3364 | 5.24 | 9000 | 4.2358 |
| 3.3147 | 5.54 | 9500 | 4.2337 |
| 3.3098 | 5.83 | 10000 | 4.2329 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
