Text Classification
Transformers
PyTorch
TensorFlow
Safetensors
Javanese
distilbert
javanese-distilbert-small-imdb-classifier
Instructions to use w11wo/javanese-distilbert-small-imdb-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use w11wo/javanese-distilbert-small-imdb-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="w11wo/javanese-distilbert-small-imdb-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("w11wo/javanese-distilbert-small-imdb-classifier") model = AutoModelForSequenceClassification.from_pretrained("w11wo/javanese-distilbert-small-imdb-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from w11wo/javanese-distilbert-small-imdb-classifier: direct link, hf CLI and curl.
- Browser
- Download file 2.96 kB
-
https://huggingface.co/w11wo/javanese-distilbert-small-imdb-classifier/resolve/main/README.md
- Command line
-
hf download hf://w11wo/javanese-distilbert-small-imdb-classifier/README.md
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curl -L -o README.md https://huggingface.co/w11wo/javanese-distilbert-small-imdb-classifier/resolve/main/README.md
2.96 kB
| language: jv | |
| tags: | |
| - javanese-distilbert-small-imdb-classifier | |
| license: mit | |
| datasets: | |
| - w11wo/imdb-javanese | |
| widget: | |
| - text: "Aku babar pisan ora nikmati film iki." | |
| ## Javanese DistilBERT Small IMDB Classifier | |
| Javanese DistilBERT Small IMDB Classifier is a movie-classification model based on the [DistilBERT model](https://arxiv.org/abs/1910.01108). It was trained on Javanese IMDB movie reviews. | |
| The model was originally [`w11wo/javanese-distilbert-small-imdb`](https://huggingface.co/w11wo/javanese-distilbert-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 76.04% 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 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-distilbert-small-imdb-classifier` | 66M | DistilBERT 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 | 0.760 | 1:26:4 | | |
| ## How to Use | |
| ### As Text Classifier | |
| ```python | |
| from transformers import pipeline | |
| pretrained_name = "w11wo/javanese-distilbert-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 DistilBERT 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. | |
| ## 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} | |
| } | |
| ``` | |