Created README; included essential model information

README.md

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+---
+language: jv
+tags:
+- javanese-bert-small-imdb-classifier
+license: mit
+datasets:
+- w11wo/imdb-javanese
+widget:
+- text: "Dhuh Gusti, film iki elek banget. Aku getun ndelok !!!"
+---
+
+## Javanese BERT Small IMDB Classifier
+Javanese BERT Small IMDB Classifier is a movie-classification model based on the [BERT model](https://arxiv.org/abs/1810.04805). It was trained on  Javanese IMDB movie reviews.
+
+The model was originally [`w11wo/javanese-bert-small-imdb`](https://huggingface.co/w11wo/javanese-bert-small-imdb) which is then fine-tuned on the [`w11wo/imdb-javanese`](https://huggingface.co/datasets/w11wo/imdb-javanese) dataset consisting of Javanese IMDB movie reviews. It achieved an accuracy of 76.37% 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/text_classification.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 models. 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-bert-small-imdb-classifier` |   110M   |   BERT 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 |  accuracy  | total time |
+|------------|------------|------------|------------|
+|    0.131   |    1.113   |   0.763    |    59:16   |
+
+## How to Use
+### As Text Classifier
+```python
+from transformers import pipeline
+
+pretrained_name = "w11wo/javanese-bert-small-imdb-classifier"
+
+nlp = pipeline(
+    "sentiment-analysis",
+    model=pretrained_name,
+    tokenizer=pretrained_name
+)
+
+nlp("Film sing apik banget!")
+```
+
+## Disclaimer
+Do consider the biases which came from the IMDB review that may be carried over into the results of this model.
+
+## Author
+Javanese BERT Small IMDB Classifier 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.