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gpt2-gpt2-mc-weight2-epoch15
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 11.3067
- Cls loss: 3.6680
- Lm loss: 3.9663
- Cls Accuracy: 0.6069
- Cls F1: 0.6023
- Cls Precision: 0.6050
- Cls Recall: 0.6069
- Perplexity: 52.79
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 |
|---|---|---|---|---|---|---|---|---|---|---|
| 8.1971 | 1.0 | 3470 | 7.6018 | 1.7777 | 4.0471 | 0.5251 | 0.4892 | 0.5282 | 0.5251 | 57.23 |
| 7.0508 | 2.0 | 6940 | 7.2679 | 1.6195 | 4.0269 | 0.6058 | 0.6001 | 0.6226 | 0.6058 | 56.08 |
| 6.5979 | 3.0 | 10410 | 7.4637 | 1.7253 | 4.0112 | 0.6184 | 0.6109 | 0.6367 | 0.6184 | 55.21 |
| 6.1811 | 4.0 | 13880 | 7.8253 | 1.9084 | 4.0063 | 0.6121 | 0.6074 | 0.6207 | 0.6121 | 54.94 |
| 5.7242 | 5.0 | 17350 | 8.1576 | 2.0824 | 3.9903 | 0.6219 | 0.6166 | 0.6195 | 0.6219 | 54.07 |
| 5.2588 | 6.0 | 20820 | 8.9472 | 2.4785 | 3.9872 | 0.6006 | 0.5942 | 0.6169 | 0.6006 | 53.90 |
| 4.8854 | 7.0 | 24290 | 9.2399 | 2.6264 | 3.9840 | 0.6063 | 0.5988 | 0.6123 | 0.6063 | 53.73 |
| 4.5785 | 8.0 | 27760 | 9.7123 | 2.8660 | 3.9768 | 0.6121 | 0.6076 | 0.6124 | 0.6121 | 53.35 |
| 4.3508 | 9.0 | 31230 | 10.2550 | 3.1400 | 3.9712 | 0.6086 | 0.6017 | 0.6121 | 0.6086 | 53.05 |
| 4.1817 | 10.0 | 34700 | 10.3110 | 3.1681 | 3.9711 | 0.6058 | 0.5990 | 0.6047 | 0.6058 | 53.04 |
| 4.0546 | 11.0 | 38170 | 11.0526 | 3.5396 | 3.9693 | 0.5988 | 0.5929 | 0.5997 | 0.5988 | 52.95 |
| 3.9481 | 12.0 | 41640 | 11.0193 | 3.5238 | 3.9675 | 0.6086 | 0.6038 | 0.6049 | 0.6086 | 52.85 |
| 3.9008 | 13.0 | 45110 | 11.2499 | 3.6394 | 3.9669 | 0.6121 | 0.6073 | 0.6090 | 0.6121 | 52.82 |
| 3.8558 | 14.0 | 48580 | 11.3606 | 3.6948 | 3.9666 | 0.6063 | 0.6000 | 0.6034 | 0.6063 | 52.81 |
| 3.8297 | 15.0 | 52050 | 11.3067 | 3.6680 | 3.9663 | 0.6069 | 0.6023 | 0.6050 | 0.6069 | 52.79 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
