Emotion Classification - MiniLM (v1)
This is the v1 model for our MLOps Group Project (Group 2, IIT Jodhpur).
Model Details
- Architecture: microsoft/MiniLM-L12-H384-uncased
- Task: Text emotion classification (6 classes)
- Dataset: dair-ai/emotion
- Classes: sadness, joy, love, anger, fear, surprise
Training
- Platform: Kaggle GPU T4
- Epochs: 3
- Batch size: 16
- Learning rate: 3e-5
- Test Accuracy: 90.7%
- Test F1: 90.7%
Links
- GitHub Repo: https://github.com/nikhilsaini-iitj/MLOps_GroupProject
- Kaggle Notebook: https://www.kaggle.com/code/nikhilg25ait2067/kaggle-minilm
- W&B Dashboard: https://wandb.ai/g25ait2067-prom-iit-rajasthan/mlops-groupproject-v2
- Winning Model (v2): https://huggingface.co/Nikhil-iitj/emotion-electra
Team
- Nikhil Saini (G25AIT2067)
- Y Sharathchandrika (G25AIT2132)
- Sarthak Kapoor (G25AIT2098)
- Aryaveer Rathi (G25AIT2021)
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Base model
microsoft/MiniLM-L12-H384-uncased