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lang=python |
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lr=5e-5 |
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batch_size=32 |
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beam_size=10 |
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source_length=256 |
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target_length=128 |
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data_dir=../dataset |
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output_dir=../model/$lang |
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train_file=$data_dir/$lang/train.jsonl |
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dev_file=$data_dir/$lang/valid.jsonl |
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epochs=10 |
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pretrained_model=microsoft/codebert-base |
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CUDA_VISIBLE_DEVICES=2,3 python run.py \ |
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--do_train \ |
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--do_eval \ |
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--model_type roberta \ |
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--model_name_or_path $pretrained_model \ |
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--train_filename $train_file \ |
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--dev_filename $dev_file \ |
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--output_dir $output_dir \ |
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--max_source_length $source_length \ |
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--max_target_length $target_length \ |
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--beam_size $beam_size \ |
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--train_batch_size $batch_size \ |
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--eval_batch_size $batch_size \ |
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--learning_rate $lr \ |
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--num_train_epochs $epochs |