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Official codebase for the paper "Structural Contrastive Representation Learning for Zero-shot Multi-label Text Classification" in Findings of EMNLP 2022

Code tested with Python 3.7 on Ubuntu 20.04.

To run, please first install the packages in requirements.txt and follow the instructions in dataset/README.md to download datasets.

Commands for Reproducing Results from Paper

# LF-Amazon-131K
python train.py --dataset dataset/LF-Amazon-131K --min-len 40 --max-len 80 --batch-size 384 --experiment a131k

# LF-Amazon-1M
python train.py --dataset dataset/LF-Amazon-1M --min-len 40 --max-len 80 --batch-size 384 --lr 5e-6 --min-lr 5e-7 --experiment a1m

# LF-WikiSeeAlso-320K
python train.py --dataset dataset/LF-WikiSeeAlso-320K --min-len 80 --max-len 160 --batch-size 256 --lr 5e-8 --min-lr 5e-9 --epochs 5 --experiment wsa320k

# LF-Wikipedia-500K
python train.py --dataset dataset/LF-Wikipedia-500K --min-len 80 --max-len 160 --batch-size 256 --lr 5e-8 --min-lr 5e-9 --epochs 5 --experiment w500k

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Official codebase for the paper "Structural Contrastive Representation Learning for Zero-shot Multi-label Text Classification" in Findings of EMNLP 2022

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