OTSeq2Set

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OTSeq2Set: An Optimal Transport Enhanced Sequence-to-Set Model for Extreme Multi-label Text Classification

Dependency

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torch==1.9.0

torchtext==0.10.0

Datasets

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OTSeq2set uses the same dataset as AttentionXML, please download each dataset from the following links.

• EUR-Lex
• Wiki10-31K
• AmazonCat-13K
• Amazon-670K

The gensim format GloVe embedding (840B,300d) is provided by AttentionXML here.

For Wiki10-31K,AmazonCat-13K, the label vocabulary is downloaded from The Extreme Classification Repository

or

We compress four datasets with label vocabulary and Glove embedding here.

The structure of the dataset should be:

OTSeq2Set
 |-- config
 |-- data                          
 |    |-- Eurlex              
 |    |-- AmazonCat-13K
 |    |-- Amazon-670K
 |    |-- Wiki10-31K       
 |    |-- glove.840B.300d.gensim
 |    |-- glove.840B.300d.gensim.vectors.npy
 |-- OTSet2Set.ipynb       

Config

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File config/OTSeq2Set.json contains the configuration of OTSeq2Set which the results are shown in the paper.

config/baselines.json contains the configuration of baseline models.

Description of configuration:

• dl_conv : use light weight convolution or not
• lambda_embedding: The parameter lambda of semantic optimal transport distance
• finish : whether the model is trained or not, needs set to true if you don't want to train this model

Train

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Run OTSeq2Set.ipynb