all-base5
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.0357
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 |
---|---|---|---|
6.3501 | 0.29 | 500 | 5.3140 |
5.0366 | 0.58 | 1000 | 4.8996 |
4.7014 | 0.87 | 1500 | 4.6570 |
4.4484 | 1.16 | 2000 | 4.5100 |
4.2883 | 1.45 | 2500 | 4.3964 |
4.1912 | 1.74 | 3000 | 4.2890 |
4.0845 | 2.02 | 3500 | 4.2065 |
3.8854 | 2.31 | 4000 | 4.1673 |
3.8583 | 2.6 | 4500 | 4.1114 |
3.816 | 2.89 | 5000 | 4.0592 |
3.6485 | 3.18 | 5500 | 4.0531 |
3.5744 | 3.47 | 6000 | 4.0243 |
3.5619 | 3.76 | 6500 | 3.9912 |
3.4959 | 4.05 | 7000 | 3.9799 |
3.3058 | 4.34 | 7500 | 3.9807 |
3.2993 | 4.63 | 8000 | 3.9659 |
3.2879 | 4.92 | 8500 | 3.9544 |
3.1683 | 5.21 | 9000 | 3.9630 |
3.1172 | 5.49 | 9500 | 3.9624 |
3.118 | 5.78 | 10000 | 3.9614 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
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