Some questions about the results of the MARVTT with `sim_header seqTransf`.
See original GitHub issueWhen 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
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- State:
- Created 2 years ago
- Comments:10 (4 by maintainers)
Top GitHub Comments
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.
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.