Comments (2)
Thank you for your interest in our work and your feedback.
- It seems that you only trained for 51 epochs. We recommend that you consider increasing the training time.
For your reference, we have included our last two training records below.Please note that slight performance variances of about 1% may occur between our repeated attempts, particularly when using different environments and devices.# 1 [4 * 3090 GPUs] epoch 51: 51.87 epoch 57: 54.05 epoch 75: 54.22 # 2 [4 * 3090 GPUs] epoch 51: 51.35 epoch 57: 53.99 epoch 66: 54.44
- The trend of the verification loss appears to be normal, which is consistent with our experiments.
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Close it since no response. Feel free to re-open it if problems still exist.
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Related Issues (20)
- when will the code be released? HOT 1
- Data processing for VG-w/o-ON HOT 1
- Problem of Text-Decoupling. HOT 1
- What dose “choices” and “new_pts” mean? HOT 1
- problem of evaluation HOT 1
- Question about "point_instance_label" HOT 2
- Problem of text label
- About the visualization code HOT 2
- Ask for visualization code HOT 2
- ImportError: Could not import _ext module. HOT 1
- Question about Table 1 and the joint_det setting HOT 5
- How can --use_contrastive_align be disabled?
- Validattion code for Overall Performance? HOT 3
- Question of visualization HOT 2
- Problem of learning rate HOT 1
- I am confused about the log.txt file HOT 2
- group_free_pred_bboxes HOT 1
- The pretrained PointNet++ backbone HOT 2
- should we add `self.text_encoder.eval()` ? HOT 2
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