Open humengzi opened 2 weeks ago
opt/conda/lib/python3.8/site-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use zero_division
parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
/opt/conda/lib/python3.8/site-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 due to no predicted samples. Use zero_division
parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
[2024-10-22 03:07:42,471][main][INFO] -
precision recall f1-score support
LOC 0.00 0.00 0.00 1799
ORG 0.00 0.00 0.00 976
PER 0.00 0.00 0.00 882
micro avg 0.00 0.00 0.00 3657 macro avg 0.00 0.00 0.00 3657 weighted avg 0.00 0.00 0.00 3657
[2024-10-22 03:07:42,472][main][INFO] - Eval results [2024-10-22 03:07:42,472][main][INFO] - precision recall f1-score support
LOC 0.00 0.00 0.00 1799
ORG 0.00 0.00 0.00 976
PER 0.00 0.00 0.00 882
micro avg 0.00 0.00 0.00 3657 macro avg 0.00 0.00 0.00 3657 weighted avg 0.00 0.00 0.00 3657
我也发现了,怎么训练都毫无效果。
我现在已经自己解决了: 1、要么你不要使用bert模型训练,可以使用lstmcrf去做,效果还可以 2、如果坚持使用bert模型训练的话,可以设置use_wandb为True,然后监控一下模型的loss曲线,找到最佳的epoch 同时,自建数据集可以适当降低学习率
------------------ 原始邮件 ------------------ 发件人: "zjunlp/DeepKE" @.>; 发送时间: 2024年11月1日(星期五) 下午2:51 @.>; @.**@.>; 主题: Re: [zjunlp/DeepKE] deepke训练模型,训练完成精度始终为0 (Issue #595)
我也发现了,怎么训练都毫无效果。
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抱歉,可能我们readme没写清楚导致您训练遇到一些不便。如果您还有其他问题欢迎随时交流
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