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--- |
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language: en |
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tags: |
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- go-emotion |
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- text-classification |
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- pytorch |
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datasets: |
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- go_emotions |
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metrics: |
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- f1 |
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widget: |
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- text: "Thanks for giving advice to the people who need it! 👌🙏" |
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license: mit |
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--- |
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## Model Description |
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1. Based on the uncased BERT pretrained model with a linear output layer. |
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2. Added several commonly-used emoji and tokens to the special token list of the tokenizer. |
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3. Did label smoothing while training. |
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4. Used weighted loss and focal loss to help the cases which trained badly. |
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## Results |
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Best Result of `Macro F1` - 53% |
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## Tutorial Link |
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- [GitHub](https://github.com/justin871030/GoEmotions) |
