nicknamezz00 / semantic-imdb-analysis Goto Github PK

Basic idea: word2vec embedding + CNN, here's the paper

This model (trained for 3 epochs) yields AUC = 0.96823 (on test data).

Ensemble of three convolutional networks (having different number of convolutional layers and feature maps) gives AUC = 0.97310.

• 3million * 300-dimension word2vec

• labeledTrainData
• testData
• unlabeledTrainData

• Create a clean environment

conda create --name env python=3.9
conda activate env

• Install dependencies

pip3 install -r requirements.txt

• Download data
• Prepare data

python3 ./code/process.py

• Train

python3 ./code/train.py