Create README.md

README.md

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+---
+language: jv
+tags:
+- javanese-roberta-small-imdb
+license: mit
+datasets:
+- w11wo/imdb-javanese
+widget:
+- text: "Aku bakal menehi rating film iki 5 <mask>."
+---
+
+## Javanese RoBERTa Small IMDB
+Javanese RoBERTa Small IMDB is a masked language model based on the [RoBERTa model](https://arxiv.org/abs/1907.11692). It was trained on Javanese IMDB movie reviews.
+
+The model was originally the pretrained [Javanese RoBERTa Small model](https://huggingface.co/w11wo/javanese-roberta-small) and is later fine-tuned on the Javanese IMDB movie review dataset. It achieved a perplexity of 20.83 on the validation dataset. Many of the techniques used are based on a Hugging Face tutorial [notebook](https://github.com/huggingface/notebooks/blob/master/examples/language_modeling.ipynb) written by [Sylvain Gugger](https://github.com/sgugger).
+
+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 TensorFlow nonetheless.
+
+## Model
+| Model                         | #params  | Arch.             | Training/Validation data (text) |
+|-------------------------------|----------|-------------------|---------------------------------|
+| `javanese-roberta-small-imdb` |   124M   |   RoBERTa Small   | Javanese IMDB (47.5 MB of text) |
+
+## Evaluation Results
+The model was trained for 5 epochs and the following is the final result once the training ended.
+
+| train loss | valid loss | perplexity | total time  |
+|------------|------------|------------|-------------|
+|    3.140   |    3.036   |   20.83    |   2:59:28   |
+
+## How to Use
+### As Masked Language Model
+```python
+from transformers import pipeline
+
+pretrained_name = "w11wo/javanese-roberta-small-imdb"
+
+fill_mask = pipeline(
+    "fill-mask",
+    model=pretrained_name,
+    tokenizer=pretrained_name
+)
+
+fill_mask("Aku mangan sate ing <mask> bareng konco-konco")
+```
+### Feature Extraction in PyTorch
+```python
+from transformers import RobertaModel, RobertaTokenizerFast
+
+pretrained_name = "w11wo/javanese-roberta-small-imdb"
+model = RobertaModel.from_pretrained(pretrained_name)
+tokenizer = RobertaTokenizerFast.from_pretrained(pretrained_name)
+
+prompt = "Indonesia minangka negara gedhe."
+encoded_input = tokenizer(prompt, return_tensors='pt')
+output = model(**encoded_input)
+```
+
+## Disclaimer
+Do consider the biases which came from the IMDB review that may be carried over into the results of this model.
+
+## Author
+Javanese RoBERTa Small 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.