wehub-resource-sync
31 lines
1010 B
Bash
31 lines
1010 B
Bash
# If `num_labels` is provided, it will be considered a classification task,
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# and AutoModelForSequenceClassification will be used to load the model.
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# The BERT model does not require templates, so it can usually be used without registration.
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CUDA_VISIBLE_DEVICES=0 \
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swift sft \
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--model AI-ModelScope/bert-base-chinese \
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--tuner_type lora \
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--dataset 'DAMO_NLP/jd:cls#2000' \
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--load_from_cache_file true \
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--split_dataset_ratio 0.01 \
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--torch_dtype bfloat16 \
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--num_train_epochs 1 \
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--per_device_train_batch_size 1 \
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--per_device_eval_batch_size 1 \
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--learning_rate 1e-4 \
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--lora_rank 8 \
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--lora_alpha 32 \
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--target_modules all-linear \
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--gradient_accumulation_steps 16 \
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--eval_steps 50 \
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--save_steps 50 \
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--save_total_limit 2 \
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--logging_steps 5 \
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--max_length 512 \
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--truncation_strategy right \
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--output_dir output \
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--warmup_ratio 0.05 \
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--dataloader_num_workers 4 \
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--num_labels 2 \
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--task_type seq_cls
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