language: en | |
tags: | |
- go-emotion | |
- text-classification | |
- pytorch | |
datasets: | |
- go_emotions | |
metrics: | |
- f1 | |
widget: | |
- text: "Thanks for giving advice to the people who need it! ππ" | |
license: mit | |
## Model Description | |
1. Based on the uncased BERT pretrained model with a linear output layer. | |
2. Added several commonly-used emoji and tokens to the special token list of the tokenizer. | |
3. Did label smoothing while training. | |
4. Used weighted loss and focal loss to help the cases which trained badly. | |