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1.text_classification/run_train.sh 2.text_generation/run_train_mt5.sh, run_train_palm.sh 3.token_classification/finetune_token_classification.py, run_train_mgeo.sh, run_train_structbert.sh above files were modified to adapt to improved trainer Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/12629010
23 lines
765 B
Bash
23 lines
765 B
Bash
PYTHONPATH=. python examples/pytorch/token_classification/finetune_token_classification.py \
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--task 'token-classification' \
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--trainer 'nlp-base-trainer' \
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--work_dir './tmp' \
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--model 'damo/nlp_structbert_backbone_base_std' \
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--train_dataset_name 'GeoGLUE' \
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--train_subset_name 'GeoETA' \
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--train_dataset_namespace 'damo' \
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--first_sequence 'tokens' \
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--eval_strategy by_step \
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--eval_interval 20 \
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--label 'ner_tags' \
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--sequence_length 128 \
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--preprocessor 'token-cls-tokenizer' \
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--preprocessor_padding 'max_length' \
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--max_epochs 2 \
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--mode 'inference' \
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--use_model_config True \
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--per_device_train_batch_size 32 \
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--train_data_worker 0 \
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--eval_data_worker 0 \
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--lr 3e-5 \
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