When training models such as UniXcoder and CoCoSoDa, the sampling data need to be converted into fixed-format training data using convertGen2Jsonl\convertGen2Jsonl.py.

1. The first step is to perform data preprocessing.

2. In the second step, execute python 2_generation\qgen.py --lang SQL --prefix qgen --ques_per_passage 3 to generate pseudo labels.

3. The third step is to execute python 3_negative\mine.py--lang=SQL --prefix=qgen --train_type gen --retrievers bm25 msmarco-distilbert-base-v3 msmarco-MiniLM-L-6-v3 -- retriever_score_functions none cos_sim cos_sim hard negative sampling.

4. Finally train the model python 4_retriever\training_1stage.py --lang SQL --train_type rel --prefix qgen --retrievers bm25 msmarco-distilbert-base-v3 msmarco-MiniLM-L-6-v3.