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--- |
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language: id |
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tags: |
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- indonesian-roberta-base-posp-tagger |
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license: mit |
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datasets: |
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- indonlu |
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widget: |
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- text: "Budi sedang pergi ke pasar." |
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--- |
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## Indonesian RoBERTa Base POSP Tagger |
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Indonesian RoBERTa Base POSP Tagger is a part-of-speech token-classification model based on the [RoBERTa](https://arxiv.org/abs/1907.11692) model. The model was originally the pre-trained [Indonesian RoBERTa Base](https://hf.co/flax-community/indonesian-roberta-base) model, which is then fine-tuned on [`indonlu`](https://hf.co/datasets/indonlu)'s `POSP` dataset consisting of tag-labelled news. |
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After training, the model achieved an evaluation F1-macro of 95.34%. On the benchmark test set, the model achieved an accuracy of 93.99% and F1-macro of 88.93%. |
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Hugging Face's `Trainer` class from the [Transformers](https://huggingface.co/transformers) library was used to train the model. PyTorch was used as the backend framework during training, but the model remains compatible with other frameworks nonetheless. |
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## Model |
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| Model | #params | Arch. | Training/Validation data (text) | |
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| ------------------------------------- | ------- | ------------ | ------------------------------- | |
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| `indonesian-roberta-base-posp-tagger` | 124M | RoBERTa Base | `POSP` | |
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## Evaluation Results |
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The model was trained for 10 epochs and the best model was loaded at the end. |
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| Epoch | Training Loss | Validation Loss | Precision | Recall | F1 | Accuracy | |
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| ----- | ------------- | --------------- | --------- | -------- | -------- | -------- | |
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| 1 | 0.898400 | 0.343731 | 0.894324 | 0.894324 | 0.894324 | 0.894324 | |
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| 2 | 0.294700 | 0.236619 | 0.929620 | 0.929620 | 0.929620 | 0.929620 | |
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| 3 | 0.214100 | 0.202723 | 0.938349 | 0.938349 | 0.938349 | 0.938349 | |
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| 4 | 0.171100 | 0.183630 | 0.945264 | 0.945264 | 0.945264 | 0.945264 | |
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| 5 | 0.143300 | 0.169744 | 0.948469 | 0.948469 | 0.948469 | 0.948469 | |
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| 6 | 0.124700 | 0.174946 | 0.947963 | 0.947963 | 0.947963 | 0.947963 | |
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| 7 | 0.109800 | 0.167450 | 0.951590 | 0.951590 | 0.951590 | 0.951590 | |
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| 8 | 0.101300 | 0.163191 | 0.952475 | 0.952475 | 0.952475 | 0.952475 | |
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| 9 | 0.093500 | 0.163255 | 0.953361 | 0.953361 | 0.953361 | 0.953361 | |
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| 10 | 0.089000 | 0.164673 | 0.953445 | 0.953445 | 0.953445 | 0.953445 | |
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## How to Use |
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### As Token Classifier |
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```python |
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from transformers import pipeline |
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pretrained_name = "w11wo/indonesian-roberta-base-posp-tagger" |
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nlp = pipeline( |
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"token-classification", |
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model=pretrained_name, |
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tokenizer=pretrained_name |
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) |
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nlp("Budi sedang pergi ke pasar.") |
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``` |
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## Disclaimer |
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Do consider the biases which come from both the pre-trained RoBERTa model and the `POSP` dataset that may be carried over into the results of this model. |
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## Author |
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Indonesian RoBERTa Base POSP Tagger was trained and evaluated by [Wilson Wongso](https://w11wo.github.io/). All computation and development are done on Google Colaboratory using their free GPU access. |
