Instructions to use 0xcynyx/ner-roberta-large-bahasa-indonesia-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 0xcynyx/ner-roberta-large-bahasa-indonesia-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="0xcynyx/ner-roberta-large-bahasa-indonesia-finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("0xcynyx/ner-roberta-large-bahasa-indonesia-finetuned") model = AutoModelForTokenClassification.from_pretrained("0xcynyx/ner-roberta-large-bahasa-indonesia-finetuned") - Notebooks
- Google Colab
- Kaggle
Model Card for Model ID
This model is a fine-tuned version of FacebookAI/xlm-roberta-large-finetuned-conll03-english on a synthetic Named Entity Recognition (NER) dataset in Bahasa Indonesia. The dataset contains 25,000 samples in BIO format with annotations for various entity types.
Model Details
Model Description
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Base Model: Roberta
- Model type: Token Classification
- Language(s) (NLP): Bahasa Indonesia
- Finetuned from model [optional]: xlm-roberta-large-finetuned-conll03-english
Training Performance
| Epoch | Training Loss | Training Accuracy |
|---|---|---|
| 1 | 0.012390273481311305 | 0.9912830868740373 |
| 2 | 0.002953063364330592 | 0.9979232802183077 |
Performance
Validation Loss: 0.0009539824152059737
Validation Accuracy: 0.999389430961554
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