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--- |
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license: mit |
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base_model: cahya/bert-base-indonesian-NER |
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tags: |
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- generated_from_trainer |
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datasets: |
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- indonlu_nergrit |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: belajarner |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: indonlu_nergrit |
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type: indonlu_nergrit |
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config: indonlu_nergrit_source |
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split: validation |
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args: indonlu_nergrit_source |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.7716312056737589 |
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- name: Recall |
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type: recall |
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value: 0.8217522658610272 |
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- name: F1 |
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type: f1 |
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value: 0.7959034381858083 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9477048970719857 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# belajarner |
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This model is a fine-tuned version of [cahya/bert-base-indonesian-NER](https://huggingface.co/cahya/bert-base-indonesian-NER) on the indonlu_nergrit dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2621 |
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- Precision: 0.7716 |
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- Recall: 0.8218 |
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- F1: 0.7959 |
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- Accuracy: 0.9477 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 209 | 0.1633 | 0.7678 | 0.8142 | 0.7903 | 0.9476 | |
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| No log | 2.0 | 418 | 0.1623 | 0.7631 | 0.8127 | 0.7871 | 0.9462 | |
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| 0.1633 | 3.0 | 627 | 0.1978 | 0.7535 | 0.8172 | 0.7841 | 0.9459 | |
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| 0.1633 | 4.0 | 836 | 0.2103 | 0.7573 | 0.8202 | 0.7875 | 0.9460 | |
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| 0.0423 | 5.0 | 1045 | 0.2236 | 0.7757 | 0.8097 | 0.7923 | 0.9487 | |
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| 0.0423 | 6.0 | 1254 | 0.2529 | 0.7843 | 0.8293 | 0.8062 | 0.9474 | |
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| 0.0423 | 7.0 | 1463 | 0.2559 | 0.77 | 0.8142 | 0.7915 | 0.9467 | |
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| 0.0136 | 8.0 | 1672 | 0.2621 | 0.7716 | 0.8218 | 0.7959 | 0.9477 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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