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Thank you for your great work!
I downloaded the finetuned model provided in your model zoo: https://huggingface.co/OpenGVLab/InternVideo2-Stage1-1B-224p-f8-thSth/blob/main/1B_ft_ssv2_f8.pth (with 77.1% topp-1 accuracy reported on SthV2) and prepared the dataset SthV2 according to your instructions (though may be a bit vague).
And I evaluated the model using most of the parameters provided in the script: https://github.com/OpenGVLab/InternVideo/blob/main/InternVideo2/single_modality/scripts/finetuning/full_tuning/ssv2/1B_ft_ssv2_f8.sh as below:
python run_finetuning.py --model internvideo2_1B_patch14_224 --data_path [our data path] --prefix [our data path] --data_set SSV2 --filename_tmpl img_{:05}.jpg --no_use_decord --nb_classes 174 --finetune [our path]/OpenGVLab--InternVideo2-Stage1-1B-224p-f8-SthSth/1B_ft_ssv2_f8.pth --log_dir [our path]/logs/1B_ft_ssv2_f8 --output_dir [our path]/1B_ft_ssv2_f8 --batch_size 8 --num_sample 2 --input_size 224 --short_side_size 224 --save_ckpt_freq 100 --num_frames 8 --num_workers 12 --warmup_epochs 3 --tubelet_size 1 --epochs 8 --lr 1e-4 --drop_path 0.3 --layer_decay 0.915 --use_checkpoint --checkpoint_num 6 --layer_scale_init_value 1e-5 --opt adamw --opt_betas 0.9 0.999 --weight_decay 0.05 --test_num_segment 2 --test_num_crop 3 --dist_eval --enable_deepspeed --bf16 --zero_stage 1 --test_best --eval
With raw images or videos as input, we both got extreme low evaluation results (0.59% top-1 and 2.80% top-5 accuracies using raw images as input).
Would you kindly help to check what might be the reason? Is it a problem with dataset preparation or parameter configurations?
Thank you very much for your time.
The text was updated successfully, but these errors were encountered:
The top-1 accuracy of 0.59% seems to be a random guess (1/174).
I also evaluated ssv1 model (https://huggingface.co/OpenGVLab/InternVideo2-Stage1-1B-224p-f8-SthSth/blob/main/1B_ft_ssv1_f8.pth) on SSV1 dataset. The top-1 and top-5 accuracies are 0.50% and 2.42%.
I have checked the model weights loaded and compared them with the weights in the evaluation forward path (fc_norm & head) and they are the same.
Sorry, something went wrong.
Andy1621
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Thank you for your great work!
I downloaded the finetuned model provided in your model zoo: https://huggingface.co/OpenGVLab/InternVideo2-Stage1-1B-224p-f8-thSth/blob/main/1B_ft_ssv2_f8.pth (with 77.1% topp-1 accuracy reported on SthV2) and prepared the dataset SthV2 according to your instructions (though may be a bit vague).
And I evaluated the model using most of the parameters provided in the script: https://github.com/OpenGVLab/InternVideo/blob/main/InternVideo2/single_modality/scripts/finetuning/full_tuning/ssv2/1B_ft_ssv2_f8.sh as below:
python run_finetuning.py
--model
internvideo2_1B_patch14_224
--data_path
[our data path]
--prefix
[our data path]
--data_set
SSV2
--filename_tmpl
img_{:05}.jpg
--no_use_decord
--nb_classes
174
--finetune
[our path]/OpenGVLab--InternVideo2-Stage1-1B-224p-f8-SthSth/1B_ft_ssv2_f8.pth
--log_dir
[our path]/logs/1B_ft_ssv2_f8
--output_dir
[our path]/1B_ft_ssv2_f8
--batch_size
8
--num_sample
2
--input_size
224
--short_side_size
224
--save_ckpt_freq
100
--num_frames
8
--num_workers
12
--warmup_epochs
3
--tubelet_size
1
--epochs
8
--lr
1e-4
--drop_path
0.3
--layer_decay
0.915
--use_checkpoint
--checkpoint_num
6
--layer_scale_init_value
1e-5
--opt
adamw
--opt_betas
0.9
0.999
--weight_decay
0.05
--test_num_segment
2
--test_num_crop
3
--dist_eval
--enable_deepspeed
--bf16
--zero_stage
1
--test_best
--eval
With raw images or videos as input, we both got extreme low evaluation results (0.59% top-1 and 2.80% top-5 accuracies using raw images as input).
Would you kindly help to check what might be the reason? Is it a problem with dataset preparation or parameter configurations?
Thank you very much for your time.
The text was updated successfully, but these errors were encountered: