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roberta_goEmotion
bsingh/roberta_goEmotion
roberta_goEmotion is a text classification model from bsingh. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
- admiration, amusement, anger, annoyance, approval, caring, confusion, curiosity, desire, disappointment, disapproval, disgust, embarrassment, excitement, fear, gratitude, grief, joy, love, nervousness, optimism, pri…
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Oct 11, 2021
- SHA
- af498dcb
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Datasets
Model card
From the Hugging Face model README
This model is trained for GoEmotions dataset which contains labeled 58k 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 + neutral
Training details:
- The training script is provided here: https://github.com/bsinghpratap/roberta_train_goEmotion
- Please feel free to start an issue in the repo if you have trouble running the model and I would try to respond as soon as possible.
- The model works well on most of the emotions except: 'desire', 'disgust', 'embarrassment', 'excitement', 'fear', 'grief', 'nervousness', 'pride', 'relief', 'remorse', 'surprise']
- I'll try to fine-tune the model further and update here if RoBERTa achieves a better performance.
- Each text datapoint can have more than 1 label. Most of the training set had 1 label: Counter({1: 36308, 2: 6541, 3: 532, 4: 28, 5: 1}). So currently I just used the first label for each of the datapoint. Not ideal but it does a decent job.
Model Performance
============================================================<br> Emotion: admiration<br> ============================================================<br> GoEmotions Paper: 0.65<br> RoBERTa: 0.62<br> Support: 504<br> ============================================================<br> Emotion: amusement<br> ============================================================<br> GoEmotions Paper: 0.80<br> RoBERTa: 0.78<br> Support: 252<br> ============================================================<br> Emotion: anger<br> ============================================================<br> GoEmotions Paper: 0.47<br> RoBERTa: 0.44<br> Support: 197<br> ============================================================<br> Emotion: annoyance<br> ============================================================<br> GoEmotions Paper: 0.34<br> RoBERTa: 0.22<br> Support: 286<br> ============================================================<br> Emotion: approval<br> ============================================================<br> GoEmotions Paper: 0.36<br> RoBERTa: 0.31<br> Support: 318<br> ============================================================<br> Emotion: caring<br> ============================================================<br> GoEmotions Paper: 0.39<br> RoBERTa: 0.24<br> Support: 114<br> ============================================================<br> Emotion: confusion<br> ============================================================<br> GoEmotions Paper: 0.37<br> RoBERTa: 0.29<br> Support: 139<br> ============================================================<br> Emotion: curiosity<br> ============================================================<br> GoEmotions Paper: 0.54<br> RoBERTa: 0.48<br> Support: 233<br> ============================================================<br> Emotion: disappointment<br> ============================================================<br> GoEmotions Paper: 0.28<br> RoBERTa: 0.18<br> Support: 127<br> ============================================================<br> Emotion: disapproval<br> ============================================================<br> GoEmotions Paper: 0.39<br> RoBERTa: 0.26<br> Support: 220<br> ============================================================<br> Emotion: gratitude<br> ============================================================<br> GoEmotions Paper: 0.86<br> RoBERTa: 0.84<br> Support: 288<br> ============================================================<br> Emotion: joy<br> ============================================================<br> GoEmotions Paper: 0.51<br> RoBERTa: 0.47<br> Support: 116<br> ============================================================<br> Emotion: love<br> ============================================================<br> GoEmotions Paper: 0.78<br> RoBERTa: 0.68<br> Support: 169<br> ============================================================<br> Emotion: neutral<br> ============================================================<br> GoEmotions Paper: 0.68<br> RoBERTa: 0.61<br> Support: 1606<br> ============================================================<br> Emotion: optimism<br> ============================================================<br> GoEmotions Paper: 0.51<br> RoBERTa: 0.52<br> Support: 120<br> ============================================================<br> Emotion: realization<br> ============================================================<br> GoEmotions Paper: 0.21<br> RoBERTa: 0.15<br> Support: 109<br> ============================================================<br> Emotion: sadness<br> ============================================================<br> GoEmotions Paper: 0.49<br> RoBERTa: 0.42<br> Support: 108
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Languages
- en
- Created
- Mar 2, 2022
- Updated
- Oct 11, 2021