massive_indo
This model is a fine-tuned version of xxxxxxxxx on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.6572
- F1: 0.9265
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss | F1 |
---|---|---|---|---|
4.6759 | 0.7 | 100 | 4.5686 | 0.0756 |
4.1696 | 1.41 | 200 | 4.1337 | 0.1459 |
3.7162 | 2.11 | 300 | 3.7519 | 0.2513 |
3.3933 | 2.82 | 400 | 3.4123 | 0.3291 |
3.0368 | 3.52 | 500 | 3.0874 | 0.4287 |
2.7163 | 4.23 | 600 | 2.7851 | 0.5446 |
2.4295 | 4.93 | 700 | 2.5342 | 0.5967 |
2.192 | 5.63 | 800 | 2.2814 | 0.6738 |
1.9818 | 6.34 | 900 | 2.0643 | 0.7221 |
1.7487 | 7.04 | 1000 | 1.8860 | 0.7589 |
1.6227 | 7.75 | 1100 | 1.7132 | 0.8021 |
1.4186 | 8.45 | 1200 | 1.5550 | 0.8249 |
1.2316 | 9.15 | 1300 | 1.4266 | 0.8378 |
1.1508 | 9.86 | 1400 | 1.3024 | 0.8547 |
1.0137 | 10.56 | 1500 | 1.1962 | 0.8708 |
0.9242 | 11.27 | 1600 | 1.1050 | 0.8807 |
0.877 | 11.97 | 1700 | 1.0273 | 0.8908 |
0.7244 | 12.68 | 1800 | 0.9580 | 0.8946 |
0.7141 | 13.38 | 1900 | 0.8928 | 0.9016 |
0.6071 | 14.08 | 2000 | 0.8448 | 0.9128 |
0.6166 | 14.79 | 2100 | 0.7980 | 0.9112 |
0.6017 | 15.49 | 2200 | 0.7613 | 0.9175 |
0.5192 | 16.2 | 2300 | 0.7300 | 0.9204 |
0.4669 | 16.9 | 2400 | 0.7112 | 0.9172 |
0.4539 | 17.61 | 2500 | 0.6872 | 0.9247 |
0.438 | 18.31 | 2600 | 0.6698 | 0.9248 |
0.4435 | 19.01 | 2700 | 0.6612 | 0.9256 |
0.4141 | 19.72 | 2800 | 0.6572 | 0.9265 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Tokenizers 0.13.3
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