ljynlp / W2NER

Source code for AAAI 2022 paper: Unified Named Entity Recognition as Word-Word Relation Classification
MIT License
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训练模型时entity的precision,recall和F1 都是0 #78

Open Yuning-J opened 1 year ago

Yuning-J commented 1 year ago

您好,我使用resume-zh的数据集,然后只改动了.cuda为.cpu,其他按照instruction直接run了main.py。结果所有epoch生成的entity的precision,recall和F1 都是0: /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/transformers/optimization.py:310: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set no_deprecation_warning=True to disable this warning FutureWarning, 2022-11-28 22:58:59 - INFO: Epoch: 0 2022-11-29 00:53:08 - INFO: +---------+--------+--------+-----------+--------+ | Train 0 | Loss | F1 | Precision | Recall | +---------+--------+--------+-----------+--------+ | Label | 0.3232 | 0.0985 | 0.0999 | 0.0998 | +---------+--------+--------+-----------+--------+ /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/sklearn/metrics/_classification.py:1318: 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)) 2022-11-29 00:56:13 - INFO: EVAL Label F1 [0.99353707 0. 0. 0. 0. 0.

        1. ] 2022-11-29 00:56:13 - INFO: +--------+--------+-----------+--------+ | EVAL 0 | F1 | Precision | Recall | +--------+--------+-----------+--------+ | Label | 0.0994 | 0.0987 | 0.1000 | | Entity | 0.0000 | 0.0000 | 0.0000 | +--------+--------+-----------+--------+ /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/sklearn/metrics/_classification.py:1318: 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)) 2022-11-29 00:59:45 - INFO: TEST Label F1 [0.9937789 0. 0. 0. 0. 0. 0.
      1. ] 2022-11-29 00:59:45 - INFO: +--------+--------+-----------+--------+ | TEST 0 | F1 | Precision | Recall | +--------+--------+-----------+--------+ | Label | 0.0994 | 0.0988 | 0.1000 | | Entity | 0.0000 | 0.0000 | 0.0000 | +--------+--------+-----------+--------+
missyoudaisy commented 1 year ago

请问你解决这个问题了吗?

songxian1129 commented 5 months ago

请问你解决这个问题了吗?

请问你解决这个问题了吗

songxian1129 commented 5 months ago

您好,我使用resume-zh的数据集,然后只改动了.cuda为.cpu,其他按照指令直接run了 main.py。结果所有epoch生成的entity的precision,recall和F1 都是0: /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/transformers/optimization.py:310: FutureWarning: 此 AdamW 实现已弃用,并将在将来的版本中删除。请改用 PyTorch 实现 torch.optim.AdamW,或设置为禁用此警告 未来警告, 2022-11-28 22:58:59 - 信息: 纪元: 0 2022-11-29 00:53:08 - 信息: +---------+--------+--------+-----------+--------+ |火车 0 |损失 |F1 |精密 |召回 | +---------+--------+--------+-----------+--------+ |标签 |0.3232 |0.0985 |0.0999 |0.0998 | +---------+--------+--------+-----------+--------+ /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/sklearn/metrics/_classification.py:1318:UndefinedMetricWarning:精度和 F 分数定义不明确,在没有预测样本的标签中设置为 0.0。使用参数来控制此行为。 _warn_prf(平均, 修饰符, msg_start, len(result)) 2022-11-29 00:56:13 - 信息: EVAL Label F1 [0.99353707 0.0. 0.0. 0. 0. 0.0. 0.] 2022-11-29 00:56:13 - 信息:+--------+--------+-----------+--------+ |评估 0 |F1 |精密 |召回 | +--------+--------+-----------+--------+ |标签 |0.0994 |0.0987 |0.1000 | |实体 |0.0000 |0.0000 |0.0000 | +--------+--------+-----------+--------+ /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/sklearn/metrics/_classification.py:1318:UndefinedMetricWarning:精度和 F 分数定义不明确,在没有预测样本的标签中设置为 0.0。使用参数来控制此行为。 _warn_prf(平均, 修饰符, msg_start, len(结果)) 2022-11-29 00:59:45 - 信息:测试标签 F1 [0.9937789 0.0. 0.0. 0.0. 0.0. 0.] 2022-11-29 00:59:45 - 信息:+--------+--------+-----------+--------+ |测试 0 |F1 |精密 |召回 | +--------+--------+-----------+--------+ |标签 |0.0994 |0.0988 |0.1000 | |实体 |0.0000 |0.0000 |0.0000 |no_deprecation_warning=True``zero_division``zero_division +--------+--------+-----------+--------+

请问您是否解决了