Comments (2)
@with-him777 hello,为了排查问题,我想确认一下以下几件事:
1、是否follow了README里数据格式的转换步骤
2、发一下你所使用的config
3、打印338维的weight,看是否全都小于0
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1、我按照了您的转换步骤
2、使用的gfl_r50_fpn_1x_coco.py,因为您的gfl_s101_fpn_2x_coco.py我训练一直精度为0,不知道是什么原因
3、他是随机性出现这个维度的问题,有时候是可以运行的,但有时候就会报错,在运行不同的epoch报错,比如第一次是第2个epoch报错,第二次在第4个,第三次可能就运行完毕了没报错。
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Related Issues (20)
- After 24 epoches trained, its loss still can't reach convergence HOT 6
- 文档里面的这个检测结果是mAP@50的吗 HOT 11
- 采用预训练模型推理结果差异较大 HOT 1
- when inference:RuntimeError: indices should be either on cpu or on the same device as the indexed tensor (cpu)
- AssertionError: Default process group is not initialized
- Inference怎么用?
- Inference怎么用? HOT 3
- Error while calculating inference with CPU HOT 1
- IBME的label的x_rel, y_rel, width, height为什么是浮点数 HOT 1
- 有pth模型文件吗 HOT 1
- Failed building wheel for mmpycocotools during requirements installation HOT 1
- 预训练权重
- __missing__ raise Keyerror (name) HOT 15
- 是否考虑深圳的机会
- what is the validation set? HOT 1
- 用ResNeSt101多卡训练时梯度爆炸 HOT 2
- 请问用resnest50训练后效果很差怎么办? HOT 1
- Output Quality Focal Loss
- RuntimeError: CUDA OOM / Bad Training Performance after reducing crop_size HOT 2
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