gpt-2-10000
This model is a fine-tuned version of gpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2551
- Precision: 0.1523
- Recall: 0.2608
- F1: 0.1923
- Accuracy: 0.9175
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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.4502 | 1.0 | 477 | 0.3178 | 0.1351 | 0.2289 | 0.1699 | 0.8953 |
| 0.3283 | 2.0 | 954 | 0.3014 | 0.1227 | 0.2220 | 0.1581 | 0.8985 |
| 0.3016 | 3.0 | 1431 | 0.2768 | 0.1441 | 0.2379 | 0.1795 | 0.9077 |
| 0.2824 | 4.0 | 1908 | 0.2687 | 0.1442 | 0.2415 | 0.1806 | 0.9103 |
| 0.2686 | 5.0 | 2385 | 0.2697 | 0.1374 | 0.2383 | 0.1743 | 0.9086 |
| 0.2568 | 6.0 | 2862 | 0.2573 | 0.1450 | 0.2525 | 0.1842 | 0.9140 |
| 0.2472 | 7.0 | 3339 | 0.2534 | 0.1492 | 0.2574 | 0.1889 | 0.9166 |
| 0.2405 | 8.0 | 3816 | 0.2548 | 0.1413 | 0.2515 | 0.1809 | 0.9153 |
| 0.2345 | 9.0 | 4293 | 0.2545 | 0.1489 | 0.2564 | 0.1884 | 0.9163 |
| 0.2299 | 10.0 | 4770 | 0.2551 | 0.1523 | 0.2608 | 0.1923 | 0.9175 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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