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StevenLimcorn/indonesian-roberta-base-emotion-classifier

sourceHugging Facemitupdated 3y agoView on Hugging Face
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Model Card

Indo RoBERTa Emotion Classifier

Indo RoBERTa Emotion Classifier is emotion classifier based on Indo-roberta model. It was trained on the trained on IndoNLU EmoT dataset. The model used was Indo-roberta and was transfer-learned to an emotion classifier model. Based from the IndoNLU bencmark, 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.

EpochTraining LossValidation LossAccuracyF1PrecisionRecall
11.3007001.0051490.6227270.6018460.6408450.611144
20.8063000.8419530.6863640.6940960.7019840.696657
30.5919000.7967940.6863640.6965730.7075200.691671
40.4412000.7820940.7227270.7243590.7259850.730229
50.3347000.8099310.7113640.7205500.7183180.724608
60.2684000.8127710.7181820.7241920.7212220.729195
70.2260000.8284610.7250000.7336250.7317090.735800

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. 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 }
}