---
language: en
tags:
- text-classification
- tensorflow
- roberta
datasets:
- go_emotions
license: mit
---

## What is the GoEmotions Dataset?

The dataset is comprised of 58000 Reddit comments with 28 emotions.

- admiration, amusement, anger, annoyance, approval, caring, confusion, curiosity, desire, disappointment, disapproval, disgust, embarrassment, excitement, fear, gratitude, grief, joy, love, nervousness, optimism, pride, realization, relief, remorse, sadness, surprise
## Usage

```python

from transformers import RobertaTokenizerFast, TFRobertaForSequenceClassification, pipeline

tokenizer = RobertaTokenizerFast.from_pretrained("cappuch/EmoRoBERTa_Retrain")
model = TFRobertaForSequenceClassification.from_pretrained("cappuch/EmoRoBERTa_Retrain")

emotion = pipeline('sentiment-analysis', 
                    model='cappuch/EmoRoBERTa_Retrain')

emotion_labels = emotion("Hello!")
print(emotion_labels)

#[{'label': 'neutral', 'score': 0.9964383244514465}]
```