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1.add parameter model_revision in training_args.py. 2.add parameter model_revision in kwargs for finetune_text_classification.py and finetune_text_generation.py. 3.modify dataset loading in finetune_text_classification.py for flex training. Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/12869552 * add model revision in training_args and modify dataset loading in finetune text classification
26 lines
858 B
Bash
26 lines
858 B
Bash
PYTHONPATH=. python examples/pytorch/text_classification/finetune_text_classification.py \
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--task 'text-classification' \
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--model 'damo/nlp_structbert_backbone_base_std' \
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--train_dataset_name 'clue' \
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--val_dataset_name 'clue' \
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--train_subset_name 'tnews' \
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--val_subset_name 'tnews' \
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--train_split 'train' \
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--val_split 'validation' \
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--first_sequence 'sentence' \
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--label label \
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--num_labels 15 \
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--labels '0,1,2,3,4,5,6,7,8,9,10,11,12,13,14' \
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--preprocessor 'sen-cls-tokenizer' \
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--use_model_config True \
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--max_epochs 1 \
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--per_device_train_batch_size 16 \
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--per_device_eval_batch_size 16 \
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--eval_interval 100 \
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--eval_strategy by_step \
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--work_dir './tmp' \
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--train_data_worker 0 \
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--eval_data_worker 0 \
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--lr 1e-5 \
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--eval_metrics 'seq-cls-metric' \
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