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--- |
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language: |
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- id |
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license: mit |
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base_model: indolem/indobert-base-uncased |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: nerui-base-2 |
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results: [] |
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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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# nerui-base-2 |
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This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co./indolem/indobert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0571 |
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- Location Precision: 0.8812 |
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- Location Recall: 0.9570 |
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- Location F1: 0.9175 |
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- Location Number: 93 |
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- Organization Precision: 0.9130 |
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- Organization Recall: 0.8855 |
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- Organization F1: 0.8991 |
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- Organization Number: 166 |
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- Person Precision: 0.9786 |
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- Person Recall: 0.9648 |
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- Person F1: 0.9716 |
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- Person Number: 142 |
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- Overall Precision: 0.9279 |
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- Overall Recall: 0.9302 |
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- Overall F1: 0.9290 |
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- Overall Accuracy: 0.9857 |
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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: 5e-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: 5.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Location Precision | Location Recall | Location F1 | Location Number | Organization Precision | Organization Recall | Organization F1 | Organization Number | Person Precision | Person Recall | Person F1 | Person Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------------------:|:---------------:|:-----------:|:---------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:----------------:|:-------------:|:---------:|:-------------:|:-----------------:|:--------------:|:----------:|:----------------:| |
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| 0.2624 | 1.0 | 96 | 0.0635 | 0.7857 | 0.9462 | 0.8585 | 93 | 0.8545 | 0.8494 | 0.8520 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.8804 | 0.9177 | 0.8987 | 0.9802 | |
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| 0.054 | 2.0 | 192 | 0.0530 | 0.8318 | 0.9570 | 0.89 | 93 | 0.8580 | 0.9096 | 0.8830 | 166 | 0.9787 | 0.9718 | 0.9753 | 142 | 0.8915 | 0.9426 | 0.9164 | 0.9841 | |
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| 0.0268 | 3.0 | 288 | 0.0673 | 0.8257 | 0.9677 | 0.8911 | 93 | 0.8869 | 0.8976 | 0.8922 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9041 | 0.9401 | 0.9218 | 0.9833 | |
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| 0.0159 | 4.0 | 384 | 0.0546 | 0.9167 | 0.9462 | 0.9312 | 93 | 0.8743 | 0.9217 | 0.8974 | 166 | 0.9786 | 0.9648 | 0.9716 | 142 | 0.9197 | 0.9426 | 0.9310 | 0.9868 | |
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| 0.0108 | 5.0 | 480 | 0.0571 | 0.8812 | 0.9570 | 0.9175 | 93 | 0.9130 | 0.8855 | 0.8991 | 166 | 0.9786 | 0.9648 | 0.9716 | 142 | 0.9279 | 0.9302 | 0.9290 | 0.9857 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.15.2 |
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