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ProtoQA-GPT2 Baseline

This repo contains the GPT2 baselines in the ProtoQA paper.

• The dataset is here: https://github.com/iesl/protoqa-data
• The proposed evaluation is here: https://github.com/iesl/protoqa-evaluator

Requirments

• Pytorch: 1.4.0
• Huggingface transformer: 2.1.1

Following the install.sh in the repo will create a conda environment named protoqa, with corresponding libraries installed. Note: protoqa-evaluater is included.

Download fine-tuned GPT2 model and generate answers

Colab notebook demo:

• Fine-tuned model can be downloaded here
• Generate answers using the fine-tuned GPT2 model:

python run_generation.py \
--model_type=gpt2 \
--model_name_or_path='./models/large_outputb_1e_1gu_8' \
--length=10 \
--num_samples=300 \
--temperature=0.69 \
--input_file='./data/dev/dev.crowdsourced.jsonl \
--output='./'

This will generate ranked_answer.jsonl under the same directionary.

• Run protoqa-evaluator to evaluate against ground truth answers, for example:

protoqa_evaluator evaluate --similarity_function exact_match ./data/dev/dev.crowdsourced.jsonl ranked_list.jsonl

• For detail usage of protoqa-evaluator, please refer to https://github.com/iesl/protoqa-evaluator

Fine tune GPT2

• Use the train/dev in the data directory. The train/dev data are from ProtoQA scrapped data.
• Run finetune.sh to fine tune the GPT2.