Comments (4)
python run_classifier.py --task_name=MRPC --do_train=true --do_eval=true --data_dir=data/ --vocab_file=uncased_L-12_H-768_A-12/vocab.txt --bert_config_file=uncased_L-12_H-768_A-12/bert_config.json --init_checkpoint=uncased_L-12_H-768_A-12/bert_model.ckpt --train_batch_size=32 --learning_rate=2e-5 --num_train_epochs=100.0 --output_dir=mrpc_output/
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确实是训练步数,调整epoch,立马提升精度!谢谢!
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确实是训练步数,调整epoch,立马提升精度!谢谢!
请问你将epoch调整到了多少,我设置num_train_epochs=50
,ACC还是0.1,是还需要调整其他参数吗? @zy486at189cn
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和楼上一样的参数,但acc仍然为0.1
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Related Issues (20)
- 关于预处理的问题 HOT 3
- 关于预测准确率 HOT 29
- issues about new data which 7 classification HOT 8
- 怎么使用GPU模式的 HOT 7
- 保存训练过程dev set准确率
- do_eval的问题 HOT 1
- 中文乱码 HOT 1
- 请问, 哪里可以看到损失函数?
- max_seq_length的最大值不超过512
- 用模型预测最终生成的文件问题 HOT 4
- mrpc的训练数据在哪里下载
- emmm 这里的classification 好像不止改了一点点
- 能导出环境配置文件?跑了你的项目报错了
- eval_drop_remainder = True if FLAGS.use_tpu else Falsed HOT 2
- 关于多文本分类任务 HOT 1
- Tokens difference between bert project and yours. Is run_classifier.py the only changed file? HOT 2
- 问题 HOT 5
- 关于中文二分类问题 HOT 5
- 关于显卡显存 HOT 1
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