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gpt2-gpt2-mc-weight1-epoch15
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 7.6876
- Cls loss: 3.7214
- Lm loss: 3.9640
- Cls Accuracy: 0.6040
- Cls F1: 0.5981
- Cls Precision: 0.6050
- Cls Recall: 0.6040
- Perplexity: 52.67
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Cls loss | Lm loss | Cls Accuracy | Cls F1 | Cls Precision | Cls Recall | Perplexity |
|---|---|---|---|---|---|---|---|---|---|---|
| 6.3006 | 1.0 | 3470 | 5.7550 | 1.7137 | 4.0417 | 0.5326 | 0.4990 | 0.4983 | 0.5326 | 56.92 |
| 5.5103 | 2.0 | 6940 | 5.5608 | 1.5450 | 4.0149 | 0.6075 | 0.6009 | 0.6160 | 0.6075 | 55.42 |
| 5.2167 | 3.0 | 10410 | 5.7608 | 1.7609 | 3.9988 | 0.5977 | 0.5917 | 0.6161 | 0.5977 | 54.53 |
| 4.9916 | 4.0 | 13880 | 5.8042 | 1.8106 | 3.9925 | 0.6035 | 0.5979 | 0.6063 | 0.6035 | 54.19 |
| 4.7224 | 5.0 | 17350 | 6.0519 | 2.0699 | 3.9807 | 0.6144 | 0.6100 | 0.6152 | 0.6144 | 53.56 |
| 4.4802 | 6.0 | 20820 | 6.3862 | 2.4050 | 3.9798 | 0.5948 | 0.5883 | 0.6071 | 0.5948 | 53.51 |
| 4.2926 | 7.0 | 24290 | 6.5793 | 2.6045 | 3.9733 | 0.5890 | 0.5819 | 0.5940 | 0.5890 | 53.16 |
| 4.1321 | 8.0 | 27760 | 6.8574 | 2.8865 | 3.9692 | 0.5977 | 0.5937 | 0.6047 | 0.5977 | 52.94 |
| 4.022 | 9.0 | 31230 | 7.1316 | 3.1624 | 3.9673 | 0.5948 | 0.5882 | 0.5980 | 0.5948 | 52.84 |
| 3.9255 | 10.0 | 34700 | 7.1732 | 3.2049 | 3.9664 | 0.6017 | 0.5985 | 0.6009 | 0.6017 | 52.79 |
| 3.8619 | 11.0 | 38170 | 7.3778 | 3.4104 | 3.9653 | 0.5994 | 0.5929 | 0.5994 | 0.5994 | 52.74 |
| 3.8141 | 12.0 | 41640 | 7.5111 | 3.5452 | 3.9638 | 0.5873 | 0.5834 | 0.5916 | 0.5873 | 52.66 |
| 3.7859 | 13.0 | 45110 | 7.6660 | 3.6998 | 3.9640 | 0.5960 | 0.5889 | 0.5976 | 0.5960 | 52.67 |
| 3.7628 | 14.0 | 48580 | 7.6558 | 3.6900 | 3.9636 | 0.5954 | 0.5899 | 0.5969 | 0.5954 | 52.65 |
| 3.7539 | 15.0 | 52050 | 7.6876 | 3.7214 | 3.9640 | 0.6040 | 0.5981 | 0.6050 | 0.6040 | 52.67 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
