Text-code/text-to-code/code/train.sh

LANG=java
DATADIR=../dataset
OUTPUTDIR=../model
PRETRAINDIR=microsoft/CodeGPT-small-java-adaptedGPT2    # will download pre-trained CodeGPT model
LOGFILE=text2code_concode.log
PER_NODE_GPU=2       # modify YOUR_GPU_NUM

CUDA_VISIBLE_DEVICES=2,3 python run.py \
        --data_dir=$DATADIR \
        --langs=$LANG \
        --output_dir=$OUTPUTDIR \
        --pretrain_dir=$PRETRAINDIR \
        --log_file=$LOGFILE \
        --model_type=gpt2 \
        --block_size=512 \
        --do_train \
        --node_index 0 \
        --gpu_per_node $PER_NODE_GPU \
        --learning_rate=5e-5 \
        --weight_decay=0.01 \
        --evaluate_during_training \
        --per_gpu_train_batch_size=6 \
        --per_gpu_eval_batch_size=12 \
        --gradient_accumulation_steps=2 \
        --num_train_epochs=30 \
        --logging_steps=100 \
        --save_steps=5000 \
        --overwrite_output_dir \
        --seed=42