--- language: id tags: - roberta license: mit datasets: - indonlu widget: - text: "Hal-hal baik akan datang." --- # Indo RoBERTa Emotion Classifier Indo RoBERTa Emotion Classifier is emotion classifier based on [Indo-roberta](https://huggingface.co/flax-community/indonesian-roberta-base) model. It was trained on the trained on [IndoNLU EmoT](https://huggingface.co/datasets/indonlu) dataset. The model used was [Indo-roberta](https://huggingface.co/flax-community/indonesian-roberta-base) and was transfer-learned to an emotion classifier model. Based from the [IndoNLU bencmark](https://www.indobenchmark.com/), the model achieve an f1-macro of 72.05%, accuracy of 71.81%, precision of 72.47% and recall of 71.94%. ## Model The model was trained on 7 epochs with learning rate 2e-5. Achieved different metrics as shown below. | Epoch | Training Loss | Validation Loss | Accuracy | F1 | Precision | Recall | |-------|---------------|-----------------|----------|----------|-----------|----------| | 1 | 1.300700 | 1.005149 | 0.622727 | 0.601846 | 0.640845 | 0.611144 | | 2 | 0.806300 | 0.841953 | 0.686364 | 0.694096 | 0.701984 | 0.696657 | | 3 | 0.591900 | 0.796794 | 0.686364 | 0.696573 | 0.707520 | 0.691671 | | 4 | 0.441200 | 0.782094 | 0.722727 | 0.724359 | 0.725985 | 0.730229 | | 5 | 0.334700 | 0.809931 | 0.711364 | 0.720550 | 0.718318 | 0.724608 | | 6 | 0.268400 | 0.812771 | 0.718182 | 0.724192 | 0.721222 | 0.729195 | | 7 | 0.226000 | 0.828461 | 0.725000 | 0.733625 | 0.731709 | 0.735800 | ## How to Use ### As Text Classifier ```python from transformers import pipeline pretrained_name = "StevenLimcorn/indonesian-roberta-base-emotion-classifier" nlp = pipeline( "sentiment-analysis", model=pretrained_name, tokenizer=pretrained_name ) nlp("Hal-hal baik akan datang.") ``` ## Disclaimer Do consider the biases which come from both the pre-trained RoBERTa model and the `EmoT` dataset that may be carried over into the results of this model. ## Author Indonesian RoBERTa Base Emotion Classifier was trained and evaluated by [Steven Limcorn](https://github.com/stevenlimcorn). All computation and development are done on Google Colaboratory using their free GPU access. If used, please cite ```bibtex @misc {steven_limcorn_2023, author = { {Steven Limcorn} }, title = { indonesian-roberta-base-emotion-classifier (Revision e8a9cb9) }, year = 2023, url = { https://huggingface.co/StevenLimcorn/indonesian-roberta-base-emotion-classifier }, doi = { 10.57967/hf/0681 }, publisher = { Hugging Face } } ```