| 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}] | |
| ``` | |