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