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Some questions about the results of the MARVTT with `sim_header seqTransf`.

See original GitHub issue

When I use the following configuration to train the model on MSRVTT Training-9K, the best result I got is 07/27/2021 13:11:01 - INFO - sim matrix size: 1000, 1000 07/27/2021 13:11:01 - INFO - Length-T: 1000, Length-V:1000 07/27/2021 13:11:01 - INFO - Text-to-Video: 07/27/2021 13:11:01 - INFO - >>> R@1: 43.2 - R@5: 71.0 - R@10: 79.4 - Median R: 2.0 - Mean R: 15.4 07/27/2021 13:11:01 - INFO - Video-to-Text: 07/27/2021 13:11:01 - INFO - >>> V2T$R@1: 43.1 - V2T$R@5: 71.2 - V2T$R@10: 80.7 - V2T$Median R: 2.0 - V2T$Mean R: 11.9. It’s worse than the results R@1: 44.5 listed in the paper. Did i miss some details? Here is the configuration. CUDA_VISIBLE_DEVICES=0,1 python -m torch.distributed.launch --nproc_per_node=2 --master_addr=127.0.0.2 --master_port 29552 main_ta sk_retrieval.py --num_thread_reader=4 --epochs=5 --batch_size=128 --n_display=20 --train_csv /home/hadoop-vacv/cephfs/data/caoshuqia ng/data/jobs/MSRVTT/csv/msrvtt_data/MSRVTT_train.9k.csv --val_csv /home/hadoop-vacv/cephfs/data/caoshuqiang/data/jobs/MSRVTT/csv/msr vtt_data/MSRVTT_JSFUSION_test.csv --data_path /home/hadoop-vacv/cephfs/data/caoshuqiang/data/jobs/MSRVTT/csv/msrvtt_data/MSRVTT_data .json --features_path /home/hadoop-vacv/cephfs/data/caoshuqiang/data/jobs/MSRVTT/MSRVTT_Videos --output_dir /home/hadoop-vacv/cephfs /data/caoshuqiang/code/vicab/newexp/hope/clip_raw --lr 1e-4 --max_words 32 --max_frames 12 --batch_size_val 12 --datatype msrvtt -- expand_msrvtt_sentences --feature_framerate 1 --coef_lr 1e-3 --freeze_layer_num 0 --slice_framepos 2 --loose_type --linear_patch 2d --sim_header seqTransf --do_train.

Issue Analytics

  • State:closed
  • Created 2 years ago
  • Comments:10 (4 by maintainers)

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1reaction
ArrowLuocommented, Jul 28, 2021

Oh, it is not totally the same as ours. I do not know whether the gap is normal for this reproduction now. It is strange if you did not change any code on ours, and I have no more idea about this problem now.

If you want to compare your results with ours in your research, an idea I think is that you can report your implementation because they are got in the same environment and dataset. Thanks for your sharing and discussion.

0reactions
starmemdacommented, Aug 19, 2021

Thank you so much for helping me. I have learned a lot.

It’s strange that I can’t reproduce the result, too. Maybe we can get a connection and discuss that where is the problem. My QQ number is 1471659527.

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