gpt2-dp-guten-rarity-all-5k-2p5k
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.3172
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 |
---|---|---|---|
6.6951 | 0.28 | 500 | 5.6610 |
5.3498 | 0.55 | 1000 | 5.2276 |
5.0115 | 0.83 | 1500 | 4.9818 |
4.7688 | 1.1 | 2000 | 4.8256 |
4.5712 | 1.38 | 2500 | 4.7126 |
4.4784 | 1.65 | 3000 | 4.6078 |
4.3906 | 1.93 | 3500 | 4.5226 |
4.1804 | 2.21 | 4000 | 4.4857 |
4.1213 | 2.48 | 4500 | 4.4278 |
4.0805 | 2.76 | 5000 | 4.3689 |
4.0172 | 3.03 | 5500 | 4.3318 |
3.7877 | 3.31 | 6000 | 4.3246 |
3.7896 | 3.58 | 6500 | 4.2902 |
3.7714 | 3.86 | 7000 | 4.2610 |
3.628 | 4.13 | 7500 | 4.2685 |
3.4948 | 4.41 | 8000 | 4.2600 |
3.4897 | 4.69 | 8500 | 4.2447 |
3.4837 | 4.96 | 9000 | 4.2332 |
3.327 | 5.24 | 9500 | 4.2460 |
3.2974 | 5.51 | 10000 | 4.2442 |
3.296 | 5.79 | 10500 | 4.2437 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
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