readme: ---
  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.