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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: Sultannn/bert-base-ft-ner-xtreme-id |
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results: [] |
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widget: |
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- text: Nama saya Tono, saya bekerja di Gotot dan tinggal di Mars. |
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language: id |
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datasets: |
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- xtreme |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# Sultannn/bert-base-ft-ner-xtreme-id |
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This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an [xtreme PAN-X.id](https://huggingface.co/datasets/xtreme/viewer/PAN-X.id/test) for **NER** downstream task. |
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## Details of the downstream task (NER) - Dataset |
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| Dataset | # Examples | |
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| ---------------------- | ----- | |
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| Train | 35 K | |
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| Validation | 5 K | |
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## Metrics on evaluation set |
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| Metrics | Score | |
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| ---------------------- | ----- | |
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| Accuracy | **97.18** | |
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| F1 | **93.26** | |
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| Precision | **92.36** | |
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| Recall | **94.18** | |
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## Training hyperparameters |
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- Optimizer = AdamW |
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- LearningRate = 4e-5 |
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- WeightDecay = 1e-2 |
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- Warmup = 500 |
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## Example of usage |
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```python |
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# pipeline example |
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from transformers import pipeline |
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model_checkpoint = "Sultannn/bert-base-ft-ner-xtreme-id" |
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token_classifier = pipeline( |
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"token-classification", model=model_checkpoint, aggregation_strategy="simple") |
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text = "nama saya Tono saya bekerja di Facebook dan tinggal di Jawa" |
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token_classifier(text) |
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``` |
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## Framework versions |
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- Transformers 4.18.0 |
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- TensorFlow 2.8.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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> [Fine-tune on NER script provided by @Sultan](https://github.com/sultanbst123) |
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> Made with <span style="color: #e25555;">♥</span> in 🌏 |
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