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emotion-electra – AI Model by Nikhil-iitj | AlphaNeural AI

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Nikhil-iitj/
emotion-electra

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text-classification

replaced-token-detection

google/electra-small-discriminator

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Emotion Classification - ELECTRA-small (v2) - WINNING MODEL

This is the winning v2 model for our MLOps Group Project (Group 2, IIT Jodhpur).

Model Details

Architecture: google/electra-small-discriminator
Task: Text emotion classification (6 classes)
Dataset: dair-ai/emotion
Classes: sadness, joy, love, anger, fear, surprise

Training

Platform: Kaggle GPU T4
Epochs: 4
Batch size: 16
Learning rate: 5e-5
Test Accuracy: 92.65%
Test F1: 92.69%
Model Size: 54.2 MB

Why This Won

Higher accuracy, lower loss, 2.5× smaller than v1 (MiniLM), and faster inference. The RTD pretraining objective produces more efficient representations.

Links

GitHub Repo: https://github.com/nikhilsaini-iitj/MLOps_GroupProject
Kaggle Notebook: https://www.kaggle.com/code/nikhilg25ait2067/kaggle-electra
W&B Dashboard: https://wandb.ai/g25ait2067-prom-iit-rajasthan/mlops-groupproject-v2
Docker Image: https://hub.docker.com/r/nikhilsainiiitj/mlops-groupproject-inference

Team

Nikhil Saini (G25AIT2067)
Y Sharathchandrika (G25AIT2132)
Sarthak Kapoor (G25AIT2098)
Aryaveer Rathi (G25AIT2021)