readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: Sultannn/bert-base-ft-ner-xtreme-id
    results: []
    
  widget:
  - text: Nama saya Tono, saya bekerja di Gotot dan tinggal di Mars. 
      
  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;">&hearts;</span> in 🌏
  