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--- |
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license: mit |
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base_model: LazarusNLP/NusaBERT-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- indonlu |
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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: NusaBERT-base-POSP |
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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 |
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type: indonlu |
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config: posp |
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split: validation |
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args: posp |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.9577443609022557 |
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- name: Recall |
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type: recall |
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value: 0.9577443609022557 |
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- name: F1 |
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type: f1 |
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value: 0.9577443609022557 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9577443609022557 |
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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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# NusaBERT-base-POSP |
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This model is a fine-tuned version of [LazarusNLP/NusaBERT-base](https://huggingface.co./LazarusNLP/NusaBERT-base) on the indonlu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1472 |
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- Precision: 0.9577 |
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- Recall: 0.9577 |
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- F1: 0.9577 |
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- Accuracy: 0.9577 |
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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: 16 |
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- eval_batch_size: 64 |
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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: 10 |
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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 | 420 | 0.2680 | 0.9203 | 0.9203 | 0.9203 | 0.9203 | |
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| 0.6283 | 2.0 | 840 | 0.2017 | 0.9379 | 0.9379 | 0.9379 | 0.9379 | |
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| 0.218 | 3.0 | 1260 | 0.1785 | 0.9449 | 0.9449 | 0.9449 | 0.9449 | |
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| 0.1612 | 4.0 | 1680 | 0.1692 | 0.9490 | 0.9490 | 0.9490 | 0.9490 | |
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| 0.1393 | 5.0 | 2100 | 0.1577 | 0.9511 | 0.9511 | 0.9511 | 0.9511 | |
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| 0.1119 | 6.0 | 2520 | 0.1503 | 0.9539 | 0.9539 | 0.9539 | 0.9539 | |
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| 0.1119 | 7.0 | 2940 | 0.1499 | 0.9549 | 0.9549 | 0.9549 | 0.9549 | |
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| 0.0943 | 8.0 | 3360 | 0.1542 | 0.9547 | 0.9547 | 0.9547 | 0.9547 | |
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| 0.0824 | 9.0 | 3780 | 0.1517 | 0.9558 | 0.9558 | 0.9558 | 0.9558 | |
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| 0.0785 | 10.0 | 4200 | 0.1519 | 0.9557 | 0.9557 | 0.9557 | 0.9557 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu118 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.1 |
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