mongolian-gpt2-ner
This model is a fine-tuned version of gpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2599
- Precision: 0.1483
- Recall: 0.2561
- F1: 0.1878
- Accuracy: 0.9149
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 |
|---|---|---|---|---|---|---|---|
| 0.4822 | 1.0 | 477 | 0.3452 | 0.1156 | 0.2072 | 0.1484 | 0.8876 |
| 0.3376 | 2.0 | 954 | 0.3196 | 0.1369 | 0.2304 | 0.1717 | 0.8975 |
| 0.3084 | 3.0 | 1431 | 0.2915 | 0.1242 | 0.2257 | 0.1603 | 0.9015 |
| 0.2889 | 4.0 | 1908 | 0.2800 | 0.1328 | 0.2375 | 0.1704 | 0.9063 |
| 0.275 | 5.0 | 2385 | 0.2734 | 0.1439 | 0.2452 | 0.1814 | 0.9099 |
| 0.264 | 6.0 | 2862 | 0.2691 | 0.1426 | 0.2420 | 0.1795 | 0.9115 |
| 0.256 | 7.0 | 3339 | 0.2639 | 0.1411 | 0.2442 | 0.1789 | 0.9129 |
| 0.2498 | 8.0 | 3816 | 0.2628 | 0.1482 | 0.2511 | 0.1864 | 0.9135 |
| 0.2438 | 9.0 | 4293 | 0.2603 | 0.1483 | 0.2548 | 0.1875 | 0.9143 |
| 0.2388 | 10.0 | 4770 | 0.2599 | 0.1483 | 0.2561 | 0.1878 | 0.9149 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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