nerugm-ia3
This model is a fine-tuned version of indolem/indobert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1662
- Precision: 0.6732
- Recall: 0.7937
- F1: 0.7285
- Accuracy: 0.9450
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: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.8173 | 1.0 | 528 | 0.5014 | 0.2653 | 0.0302 | 0.0543 | 0.8480 |
0.4808 | 2.0 | 1056 | 0.3565 | 0.5217 | 0.3068 | 0.3864 | 0.8941 |
0.3767 | 3.0 | 1584 | 0.2893 | 0.5761 | 0.5520 | 0.5638 | 0.9194 |
0.3159 | 4.0 | 2112 | 0.2479 | 0.6181 | 0.6612 | 0.6390 | 0.9279 |
0.2785 | 5.0 | 2640 | 0.2236 | 0.6304 | 0.7008 | 0.6637 | 0.9331 |
0.2527 | 6.0 | 3168 | 0.2097 | 0.6449 | 0.7333 | 0.6862 | 0.9361 |
0.2365 | 7.0 | 3696 | 0.1997 | 0.6415 | 0.7519 | 0.6923 | 0.9376 |
0.2243 | 8.0 | 4224 | 0.1905 | 0.6534 | 0.7612 | 0.7032 | 0.9394 |
0.2134 | 9.0 | 4752 | 0.1857 | 0.6522 | 0.7705 | 0.7064 | 0.9398 |
0.2072 | 10.0 | 5280 | 0.1814 | 0.6562 | 0.7798 | 0.7127 | 0.9418 |
0.2009 | 11.0 | 5808 | 0.1756 | 0.6601 | 0.7798 | 0.7150 | 0.9426 |
0.1962 | 12.0 | 6336 | 0.1738 | 0.6589 | 0.7844 | 0.7162 | 0.9436 |
0.1921 | 13.0 | 6864 | 0.1720 | 0.6621 | 0.7914 | 0.7210 | 0.9442 |
0.1887 | 14.0 | 7392 | 0.1705 | 0.6621 | 0.7914 | 0.7210 | 0.9442 |
0.1857 | 15.0 | 7920 | 0.1688 | 0.6680 | 0.7937 | 0.7254 | 0.9448 |
0.1846 | 16.0 | 8448 | 0.1684 | 0.6712 | 0.7960 | 0.7283 | 0.9450 |
0.1833 | 17.0 | 8976 | 0.1676 | 0.6706 | 0.7937 | 0.7270 | 0.9446 |
0.1804 | 18.0 | 9504 | 0.1667 | 0.6719 | 0.7937 | 0.7278 | 0.9446 |
0.1816 | 19.0 | 10032 | 0.1664 | 0.6719 | 0.7937 | 0.7278 | 0.9448 |
0.1801 | 20.0 | 10560 | 0.1662 | 0.6732 | 0.7937 | 0.7285 | 0.9450 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.15.2
Model tree for apwic/nerugm-ia3
Base model
indolem/indobert-base-uncased