Which Side Are You On? A Multi-task Dataset for End-to-End Argument Summarisation and Evaluation (ACL2024)
This work followed the paper publised on ACL 2024
This work has received ethical review from the institution under the license number 2024-16577-36845
Due to the suggestion, we will consider release task 1 and task 2's data in a more safety ways. It will be release very soon!
- python
- pytorch
- sentence-transformers
- Classification models
XXX
- Contrastive Learning models
# roberta-large
python train.py --model_name roberta-large \
--train_dataset_file PATH/TO/train_convincingness.csv \
--dev_dataset_file PATH/TO/dev_convincingness.csv \
--test_dataset_file PATH/TO/test_convincingness.csv \
--output_path PATH/TO/OUTPUT \
--num_epochs 10 \
--train_batch_size 32 \
--eval_batch_size 64 \
--max_input_length 256 \
--add_special_tokens "<SEP>" \
--learning_rate 3e-5 \
--task_name 'task2'
# sentence-t5-large or sentence-t5-xl
python train.py --model_name sentence-transformers/sentence-t5-large \
--train_dataset_file PATH/TO/train_convincingness.csv \
--dev_dataset_file PATH/TO/dev_convincingness.csv \
--test_dataset_file PATH/TO/test_convincingness.csv \
--output_path PATH/TO/OUTPUT \
--num_epochs 10 \
--train_batch_size 32 \
--eval_batch_size 64 \
--max_input_length 256 \
--add_special_tokens "</s>" \
--learning_rate 3e-5 \
--sentence_transformer \
--task_name 'task2'
# roberta-large
python train.py --model_name roberta-large \
--train_dataset_file PATH/TO/task3_trainset.csv \
--dev_dataset_file PATH/TO/task3_devset.csv \
--test_dataset_file PATH/TO/task3_testset.csv \
--output_path PATH/TO/OUTPUT \
--num_epochs 10 \
--train_batch_size 32 \
--eval_batch_size 64 \
--max_input_length 512 \
--learning_rate 3e-5 \
--task_name 'task3'
# sentence-t5-large or sentence-t5-xl
python train.py --model_name sentence-transformers/sentence-t5-large \
--train_dataset_file PATH/TO/task3_trainset.csv \
--dev_dataset_file PATH/TO/task3_devset.csv \
--test_dataset_file PATH/TO/task3_testset.csv \
--output_path PATH/TO/OUTPUT \
--num_epochs 10 \
--train_batch_size 32 \
--eval_batch_size 64 \
--max_input_length 512 \
--learning_rate 3e-5 \
--sentence_transformer \
--task_name 'task3'
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