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run_classifier_relation.sh
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run_classifier_relation.sh
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# bert model
CUDA_VISIBLE_DEVICES=0 python3 run_classifier_relation.py \
--model_type=bert \
--model_name_or_path=./prev_trained_model/bert-base-chinese/pytorch_model.bin \
--vocab_file=./prev_trained_model/bert-base-chinese/bert-base-chinese-vocab.txt \
--config_name=./prev_trained_model/bert-base-chinese/bert_config.json \
--task_name=relation \
--do_train \
--do_eval \
--do_predict \
--predict_all_checkpoints \
--do_lower_case \
--data_dir=./dataset/relation/ \
--max_seq_length=512 \
--per_gpu_train_batch_size=2 \
--per_gpu_eval_batch_size=2 \
--learning_rate=1e-5 \
--num_train_epochs=5.0 \
--logging_steps=1192 \
--save_steps=1192 \
--output_dir=./outputs/relation_output/ \
--overwrite_output_dir \
--seed=42
# albert_model
CUDA_VISIBLE_DEVICES=0 python3 run_classifier_relation.py \
--model_type=albert \
--model_name_or_path=./prev_trained_model/albert_base_zh/pytorch_model.bin \
--vocab_file=./prev_trained_model/albert_base_zh/vocab.txt \
--config_name=./prev_trained_model/albert_base_zh/config.json \
--task_name=relation \
--do_train \
--do_eval \
--do_predict \
--predict_all_checkpoints \
--do_lower_case \
--data_dir=./dataset/relation/ \
--max_seq_length=512 \
--per_gpu_train_batch_size=2 \
--per_gpu_eval_batch_size=2 \
--learning_rate=1e-5 \
--num_train_epochs=5.0 \
--logging_steps=1192 \
--save_steps=1192 \
--output_dir=./outputs/relation_output/ \
--overwrite_output_dir \
--seed=42