
## 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.

## Citation

If you use any of our models in your research, please cite:

```bib
@inproceedings{wongso2021causal,
    title={Causal and Masked Language Modeling of Javanese Language using Transformer-based Architectures},
    author={Wongso, Wilson and Setiawan, David Samuel and Suhartono, Derwin},
    booktitle={2021 International Conference on Advanced Computer Science and Information Systems (ICACSIS)},
    pages={1--7},
    year={2021},
    organization={IEEE}
}
```

{"language": "jv", "license": "mit", "tags": ["javanese-roberta-small-imdb"], "datasets": ["w11wo/imdb-javanese"], "widget": [{"text": "Aku bakal menehi rating film iki 5 <mask>."}]}
transformers pytorch tf jax roberta fill-mask javanese-roberta-small-imdb jv dataset:w11wo/imdb-javanese arxiv:1907.11692 license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tf #jax #roberta #fill-mask #javanese-roberta-small-imdb #jv #dataset-w11wo/imdb-javanese #arxiv-1907.11692 #license-mit #autotrain_compatible #endpoints_compatible #region-us 

Javanese RoBERTa Small IMDB
---------------------------


Javanese RoBERTa Small IMDB is a masked language model based on the RoBERTa model. It was trained on Javanese IMDB movie reviews.


The model was originally the pretrained Javanese RoBERTa Small model 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 written by Sylvain Gugger.


Hugging Face's 'Trainer' class from the 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
-----



Evaluation Results
------------------


The model was trained for 5 epochs and the following is the final result once the training ended.



How to Use
----------


### As Masked Language Model


### Feature Extraction in PyTorch


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. All computation and development are done on Google Colaboratory using their free GPU access.


If you use any of our models in your research, please cite:



### As Masked Language Model ### Feature Extraction in PyTorch


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. All computation and development are done on Google Colaboratory using their free GPU access.


If you use any of our models in your research, please cite:
TAGS
#transformers #pytorch #tf #jax #roberta #fill-mask #javanese-roberta-small-imdb #jv #dataset-w11wo/imdb-javanese #arxiv-1907.11692 #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### As Masked Language Model ### Feature Extraction in PyTorch


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. All computation and development are done on Google Colaboratory using their free GPU access.


If you use any of our models in your research, please cite:
passage: TAGS
#transformers #pytorch #tf #jax #roberta #fill-mask #javanese-roberta-small-imdb #jv #dataset-w11wo/imdb-javanese #arxiv-1907.11692 #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### As Masked Language Model### Feature Extraction in PyTorch


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. All computation and development are done on Google Colaboratory using their free GPU access.


If you use any of our models in your research, please cite: