Comments (3)
可以参考下面的log
![image](https://private-user-images.githubusercontent.com/17582080/258977190-39edd1a7-522e-457f-ab79-4cd15a849629.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.vC1Acsukwy7-lobQ1kwZ-tlVCSnengfhNrn66o6t308)
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感谢您的回复,我看了这个只有72个Epoch的log信息;不知道您是否尝试过训练更多epoch,比如128个甚至更多,如果有,那么在72个Epoch后的训练中检测性能还会有明显提升吗
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我们训练过 7x 从曲线上看是不涨点了
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Related Issues (20)
- Accuracy Ultralytics RT-DETR vs Pytorch models. HOT 1
- VFL Loss Won't Converge. HOT 2
- 本项目中paddle版本环境问题 HOT 1
- Validation loss larger/has different scale than training loss
- Paper Figure Confusion HOT 2
- 论文中的AIFI是只有一层的的encoder吗? HOT 2
- multi-gpu distributed and LR HOT 2
- how to run Pytorch version using multinode
- 模型参数修改问题 HOT 1
- Runtime error after 1 epoch train HOT 5
- 计算量和参数量 HOT 13
- Multi-gpu training error, [E ProcessGroupNCCL.cpp:828]
- 解码器层数
- 更改主干 HOT 1
- Is there any inference code?? HOT 1
- How many epoch does 6x mean? HOT 1
- 请问如果在训练时关掉前5个decoder和encoder编码器的辅助损失会降低模型检测时的性能吗 HOT 1
- 能否实现C++版本的tensorrt推理? HOT 2
- About validation of pytorch HOT 1
- 关于pytorch版本的DT-DETR在评估时的FPS HOT 1
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