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I3D accuracy when finetuning on UCF-101 is very low #10

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ziqi-zhang opened this issue May 8, 2019 · 1 comment
Open

I3D accuracy when finetuning on UCF-101 is very low #10

ziqi-zhang opened this issue May 8, 2019 · 1 comment

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@ziqi-zhang
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Hi, I tried to finetune i3d on ucf-101 using pretrained models in checkpoint. But the accuracy after 10 epochs is very low (30%) on validation set. I replaced logits layer of i3d and freeze other layers. Here is my script:
python -u train.py
--dataset ucf101
--model i3d
--video_path $DATASET_ROOT/jpg
--annotation_path $DATASET_ROOT/ucfTrainTestlist/ucf101_02.json
--batch_size 6
--num_classes 400
--finetune_num_classes 101
--spatial_size 224
--sample_duration 64
--learning_rate 1e-2
--save_dir $OUTPUT_DIR
--dropout_keep_prob 0.5
--checkpoint_path checkpoints/I3D/rgb_imagenet.pth
--finetune_prefixes logits
--num_scales 1 \

Can you please give me some advice on finetuning on ucf-101?
Thanks!
@MKowal2
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MKowal2 commented Jul 22, 2019

What other layers are you freezing? I replaced the logits layer but did not freeze any layers and fine tuning for 10 epochs gives about 90% accuracy on the training set and test set of UCF101_01. I have a similar batch size / learning rate too and I used rgb_imagenet.pth as my checkpoint.

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@ziqi-zhang @MKowal2