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gpt2_small_summarized
This model is a fine-tuned version of gpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.6935
- Accuracy: 0.79
- Precision: 0.2632
- Recall: 0.1515
- F1: 0.1923
- D-index: 1.4571
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1600
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | D-index |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 200 | 0.9451 | 0.77 | 0.0667 | 0.0303 | 0.0417 | 1.3827 |
| No log | 2.0 | 400 | 0.7625 | 0.81 | 0.0 | 0.0 | 0.0 | 1.4265 |
| 2.1174 | 3.0 | 600 | 0.7145 | 0.835 | 0.0 | 0.0 | 0.0 | 1.4607 |
| 2.1174 | 4.0 | 800 | 1.0087 | 0.835 | 0.0 | 0.0 | 0.0 | 1.4607 |
| 0.6744 | 5.0 | 1000 | 0.6728 | 0.825 | 0.0 | 0.0 | 0.0 | 1.4471 |
| 0.6744 | 6.0 | 1200 | 0.7295 | 0.725 | 0.1944 | 0.2121 | 0.2029 | 1.3899 |
| 0.6744 | 7.0 | 1400 | 2.0423 | 0.825 | 0.3333 | 0.0606 | 0.1026 | 1.4704 |
| 0.3582 | 8.0 | 1600 | 2.5923 | 0.685 | 0.1591 | 0.2121 | 0.1818 | 1.3332 |
| 0.3582 | 9.0 | 1800 | 2.9312 | 0.605 | 0.1974 | 0.4545 | 0.2752 | 1.3098 |
| 0.1089 | 10.0 | 2000 | 3.0778 | 0.81 | 0.0 | 0.0 | 0.0 | 1.4265 |
| 0.1089 | 11.0 | 2200 | 3.0158 | 0.785 | 0.25 | 0.1515 | 0.1887 | 1.4503 |
| 0.1089 | 12.0 | 2400 | 3.0195 | 0.8 | 0.3333 | 0.2121 | 0.2593 | 1.4934 |
| 0.0376 | 13.0 | 2600 | 3.3198 | 0.77 | 0.2593 | 0.2121 | 0.2333 | 1.4525 |
| 0.0376 | 14.0 | 2800 | 3.4092 | 0.77 | 0.2593 | 0.2121 | 0.2333 | 1.4525 |
| 0.0012 | 15.0 | 3000 | 3.5722 | 0.76 | 0.2 | 0.1515 | 0.1724 | 1.4157 |
| 0.0012 | 16.0 | 3200 | 3.5919 | 0.775 | 0.25 | 0.1818 | 0.2105 | 1.4480 |
| 0.0012 | 17.0 | 3400 | 3.5835 | 0.795 | 0.2778 | 0.1515 | 0.1961 | 1.4639 |
| 0.0045 | 18.0 | 3600 | 3.6829 | 0.785 | 0.25 | 0.1515 | 0.1887 | 1.4503 |
| 0.0045 | 19.0 | 3800 | 3.6905 | 0.785 | 0.25 | 0.1515 | 0.1887 | 1.4503 |
| 0.0008 | 20.0 | 4000 | 3.6935 | 0.79 | 0.2632 | 0.1515 | 0.1923 | 1.4571 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
