    
    
<!-- 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 🌏

{"language": "id", "license": "apache-2.0", "tags": ["generated_from_keras_callback"], "datasets": ["xtreme"], "widget": [{"text": "Nama saya Tono, saya bekerja di Gotot dan tinggal di Mars."}], "model-index": [{"name": "Sultannn/bert-base-ft-ner-xtreme-id", "results": []}]}
transformers tf bert token-classification generated_from_keras_callback id dataset:xtreme license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #bert #token-classification #generated_from_keras_callback #id #dataset-xtreme #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

Sultannn/bert-base-ft-ner-xtreme-id
===================================


This model is a fine-tuned version of bert-base-multilingual-uncased on an xtreme URL for NER downstream task.


Details of the downstream task (NER) - Dataset
----------------------------------------------



Metrics on evaluation set
-------------------------



Training hyperparameters
------------------------


* Optimizer = AdamW
* LearningRate = 4e-5
* WeightDecay = 1e-2
* Warmup = 500


Example of usage
----------------


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
> 
> 
> 



> 
> Made with ♥ in
> 
> 
> 



TAGS
#transformers #tf #bert #token-classification #generated_from_keras_callback #id #dataset-xtreme #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

passage: TAGS
#transformers #tf #bert #token-classification #generated_from_keras_callback #id #dataset-xtreme #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
