Hyper-parameters

The hyper-parmeters for edit-propagation file locator

lang = java

lr = 5e-5

batch_size = 20

source_length = 512

target_length = 512

data_dir = /dataset

output_dir = model/$lang

train_file = $data_dir/$lang/train.jsonl

dev_file = $data_dir/$lang/dev.jsonl

test_file = $data_dir/$lang/test.jsonl

epochs = 2

pretrained_model = microsoft/codebert-base

CUDA_VISIBLE_DEVICES=0,1 nohup python run.py --do_train --do_eval --do_test --model_type roberta --model_name_or_path $pretrained_model --train_filename $train_file --dev_filename $dev_file --test_filename $test_file --output_dir $output_dir --max_source_length $source_length --max_target_length $target_length --train_batch_size $batch_size --eval_batch_size $batch_size --learning_rate $lr --num_train_epochs $epochs &

lang = java

lr = 5e-5

batch_size = 20

source_length = 512

target_length = 128

data_dir = /dataset

output_dir = model/$lang

train_file = $data_dir/$lang/train.jsonl

dev_file = $data_dir/$lang/dev.jsonl

test_file = $data_dir/$lang/test.jsonl

epochs = 4

pretrained_model = microsoft/codebert-base

beam_size = 10

CUDA_VISIBLE_DEVICES=0,1 nohup python run.py --do_train --do_eval --do_test --model_type roberta --model_name_or_path $pretrained_model --train_filename $train_file --dev_filename $dev_file --test_filename $test_file --output_dir $output_dir --max_source_length $source_length --max_target_length $target_length --beam_size $beam_size --train_batch_size $batch_size --eval_batch_size $batch_size --learning_rate $lr --num_train_epochs $epochs &