belajarner
This model is a fine-tuned version of cahya/bert-base-indonesian-NER on the indonlu_nergrit dataset. It achieves the following results on the evaluation set:
- Loss: 0.2621
- Precision: 0.7716
- Recall: 0.8218
- F1: 0.7959
- Accuracy: 0.9477
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 209 | 0.1633 | 0.7678 | 0.8142 | 0.7903 | 0.9476 |
No log | 2.0 | 418 | 0.1623 | 0.7631 | 0.8127 | 0.7871 | 0.9462 |
0.1633 | 3.0 | 627 | 0.1978 | 0.7535 | 0.8172 | 0.7841 | 0.9459 |
0.1633 | 4.0 | 836 | 0.2103 | 0.7573 | 0.8202 | 0.7875 | 0.9460 |
0.0423 | 5.0 | 1045 | 0.2236 | 0.7757 | 0.8097 | 0.7923 | 0.9487 |
0.0423 | 6.0 | 1254 | 0.2529 | 0.7843 | 0.8293 | 0.8062 | 0.9474 |
0.0423 | 7.0 | 1463 | 0.2559 | 0.77 | 0.8142 | 0.7915 | 0.9467 |
0.0136 | 8.0 | 1672 | 0.2621 | 0.7716 | 0.8218 | 0.7959 | 0.9477 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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Model tree for AptaArkana/indonesian_bert_base_NER_indoNLU
Base model
cahya/bert-base-indonesian-NEREvaluation results
- Precision on indonlu_nergritvalidation set self-reported0.772
- Recall on indonlu_nergritvalidation set self-reported0.822
- F1 on indonlu_nergritvalidation set self-reported0.796
- Accuracy on indonlu_nergritvalidation set self-reported0.948