POP-CEE: Position-oriented Prompt-tuning Model for Causal Emotion Entailment

The code for our paper was modified based on the code for RECCON, which is available at https://github.com/declare-lab/RECCON.

Dependencies

• numpy==1.18.2
• pandas==1.0.1
• scikit-learn==0.23.1
• torch==1.6.0
• transformers==4.0.0
• tokenizers==0.9.4
• tqdm==4.48.0
• simpletransformers==0.50.0

Usage

1. Run the data/process_data.py file to generate the prompt processed data, which is stored in data/processed_data.

   python data/process_data.py

2. Run the train_classification.py file to train the model.

   python train_classification.py

3. Run the eval_classification.py file to evaluate the model.

   python eval_classification.py