diff --git "a/mmbench-test-en.log" "b/mmbench-test-en.log" deleted file mode 100644--- "a/mmbench-test-en.log" +++ /dev/null @@ -1,181 +0,0 @@ -+ CHECKPOINT=work_dirs/InternVL2-2B -+ DATASET=mmbench-test-en -++ pwd -+ CHECKPOINT=/mnt/petrelfs/wangweiyun/workspace_zyc/VLM-Dev/work_dirs/InternVL2-2B -++ pwd -+ export PYTHONPATH=/mnt/petrelfs/wangweiyun/workspace_zyc/VLM-Dev:/mnt/petrelfs/wangweiyun/workspace_wwy/pkgs/petrel-oss-sdk-2.3.14:/mnt/petrelfs/share_data/wangweiyun/share_pkgs/petrel-oss-sdk-2.3.12: -+ PYTHONPATH=/mnt/petrelfs/wangweiyun/workspace_zyc/VLM-Dev:/mnt/petrelfs/wangweiyun/workspace_wwy/pkgs/petrel-oss-sdk-2.3.14:/mnt/petrelfs/share_data/wangweiyun/share_pkgs/petrel-oss-sdk-2.3.12: -+ echo 'CHECKPOINT: /mnt/petrelfs/wangweiyun/workspace_zyc/VLM-Dev/work_dirs/InternVL2-2B' -CHECKPOINT: /mnt/petrelfs/wangweiyun/workspace_zyc/VLM-Dev/work_dirs/InternVL2-2B -+ MASTER_PORT=63669 -+ PORT=63665 -+ GPUS=8 -+ GPUS_PER_NODE=8 -+ NODES=1 -+ export MASTER_PORT=63669 -+ MASTER_PORT=63669 -+ export PORT=63665 -+ PORT=63665 -+ ARGS=("$@") -+ [[ 5 -gt 0 ]] -+ case "$1" in -+ shift -+ [[ 4 -gt 0 ]] -+ case "$1" in -+ shift -+ [[ 3 -gt 0 ]] -+ case "$1" in -+ shift -+ [[ 2 -gt 0 ]] -+ case "$1" in -+ shift -+ [[ 1 -gt 0 ]] -+ case "$1" in -+ shift -+ [[ 0 -gt 0 ]] -+ echo 'GPUS: 8' -GPUS: 8 -+ [[ /mnt/petrelfs/wangweiyun/workspace_zyc/VLM-Dev/work_dirs/InternVL2-2B == */ ]] -+ '[' mmbench-test-en == mme ']' -+ '[' mmbench-test-en == caption ']' -+ '[' mmbench-test-en == caption-coco ']' -+ '[' mmbench-test-en == caption-flickr30k ']' -+ '[' mmbench-test-en == caption-nocaps ']' -+ '[' mmbench-test-en == vqa ']' -+ '[' mmbench-test-en == vqa-okvqa-val ']' -+ '[' mmbench-test-en == vqa-textvqa-val ']' -+ '[' mmbench-test-en == vqa-textvqa-val-ocr ']' -+ '[' mmbench-test-en == vqa-vizwiz-val ']' -+ '[' mmbench-test-en == vqa-vizwiz-test ']' -+ '[' mmbench-test-en == vqa-vqav2-testdev ']' -+ '[' mmbench-test-en == vqa-ai2d-test ']' -+ '[' mmbench-test-en == vqa-vqav2-val ']' -+ '[' mmbench-test-en == vqa-gqa-testdev ']' -+ '[' mmbench-test-en == vqa-docvqa-val ']' -+ '[' mmbench-test-en == vqa-docvqa-test ']' -+ '[' mmbench-test-en == vqa-chartqa-test ']' -+ '[' mmbench-test-en == vqa-infovqa-val ']' -+ '[' mmbench-test-en == vqa-infovqa-test ']' -+ '[' mmbench-test-en == vqa-chartqa-test-human ']' -+ '[' mmbench-test-en == vqa-chartqa-test-augmented ']' -+ '[' mmbench-test-en == vqa-ocrvqa-val ']' -+ '[' mmbench-test-en == vqa-ocrvqa-test ']' -+ '[' mmbench-test-en == refcoco ']' -+ '[' mmbench-test-en == refcoco-val ']' -+ '[' mmbench-test-en == llava-bench ']' -+ '[' mmbench-test-en == pope ']' -+ '[' mmbench-test-en == tiny_lvlm ']' -+ '[' mmbench-test-en == mmvet ']' -+ '[' mmbench-test-en == cmmmu ']' -+ '[' mmbench-test-en == mmbench-dev-en ']' -+ '[' mmbench-test-en == mmbench-dev-cn ']' -+ '[' mmbench-test-en == mmbench-test-en ']' -+ torchrun --nnodes=1 --node_rank=0 --master_addr=127.0.0.1 --nproc_per_node=8 --master_port=63669 eval/mmbench/evaluate_mmbench.py --checkpoint /mnt/petrelfs/wangweiyun/workspace_zyc/VLM-Dev/work_dirs/InternVL2-2B --datasets mmbench_test_en_20231003 --dynamic --max-num 6 -[2024-08-07 21:58:59,972] torch.distributed.run: [WARNING] -[2024-08-07 21:58:59,972] torch.distributed.run: [WARNING] ***************************************** -[2024-08-07 21:58:59,972] torch.distributed.run: [WARNING] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. -[2024-08-07 21:58:59,972] torch.distributed.run: [WARNING] ***************************************** -datasets: ['mmbench_test_en_20231003'] -datasets: ['mmbench_test_en_20231003'] -datasets:datasets: ['mmbench_test_en_20231003']['mmbench_test_en_20231003'] - -datasets: ['mmbench_test_en_20231003'] -datasets: ['mmbench_test_en_20231003'] -datasets: ['mmbench_test_en_20231003'] -datasets: ['mmbench_test_en_20231003'] -Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. -Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. -Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. -Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. -Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. -Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. -Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. -Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. -[test] total_params: 2.205754368B, use num_beams: 1 -[test] image_size: 448 -[test] template: internlm2-chat -[test] dynamic_image_size: True -[test] use_thumbnail: True -[test] max_num: 6 -[test] total_params: 2.205754368B, use num_beams: 1 -[test] image_size: 448 -[test] template: internlm2-chat -[test] dynamic_image_size: True -[test] use_thumbnail: True -[test] max_num: 6 -[test] total_params: 2.205754368B, use num_beams: 1 -[test] image_size: 448 -[test] template: internlm2-chat -[test] dynamic_image_size: True -[test] use_thumbnail: True -[test] max_num: 6 -[test] total_params: 2.205754368B, use num_beams: 1 -[test] image_size: 448 -[test] template: internlm2-chat -[test] dynamic_image_size: True -[test] use_thumbnail: True -[test] max_num: 6 -[test] total_params: 2.205754368B, use num_beams: 1 -[test] image_size: 448 -[test] template: internlm2-chat -[test] dynamic_image_size: True -[test] use_thumbnail: True -[test] max_num: 6 -[test] total_params: 2.205754368B, use num_beams: 1 -[test] image_size: 448 -[test] template: internlm2-chat -[test] dynamic_image_size: True -[test] use_thumbnail: True -[test] max_num: 6 -[test] total_params: 2.205754368B, use num_beams: 1 -[test] image_size: 448 -[test] template: internlm2-chat -[test] dynamic_image_size: True -[test] use_thumbnail: True -[test] max_num: 6 -[test] total_params: 2.205754368B, use num_beams: 1 -[test] image_size: 448 -[test] template: internlm2-chat -[test] dynamic_image_size: True -[test] use_thumbnail: True -[test] max_num: 6 - 0it [00:00, ?it/s] 0it [00:00, ?it/s] 0it [00:00, ?it/s] 0it [00:00, ?it/s] 0it [00:00, ?it/s] 0it [00:00, ?it/s] 0it [00:00, ?it/s] 0it [00:00, ?it/s]/mnt/petrelfs/wangweiyun/miniconda3/envs/internvl/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:392: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0.0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. - warnings.warn( -/mnt/petrelfs/wangweiyun/miniconda3/envs/internvl/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:392: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0.0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. - warnings.warn( -/mnt/petrelfs/wangweiyun/miniconda3/envs/internvl/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:392: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0.0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. - warnings.warn( -/mnt/petrelfs/wangweiyun/miniconda3/envs/internvl/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:392: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0.0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. - warnings.warn( -/mnt/petrelfs/wangweiyun/miniconda3/envs/internvl/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:392: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0.0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. - warnings.warn( -/mnt/petrelfs/wangweiyun/miniconda3/envs/internvl/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:392: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0.0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. - warnings.warn( -/mnt/petrelfs/wangweiyun/miniconda3/envs/internvl/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:392: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0.0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`. - warnings.warn( -/mnt/petrelfs/wangweiyun/miniconda3/envs/internvl/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:392: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0.0` -- this flag is only used in sample-based generation modes. 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[01:31, 7.29it/s] 773it [01:31, 9.08it/s] 802it [01:31, 7.34it/s] 776it [01:31, 11.99it/s] 820it [01:31, 11.27it/s] 801it [01:31, 7.59it/s] 774it [01:31, 9.21it/s] 783it [01:31, 9.40it/s] 790it [01:31, 8.06it/s] 781it [01:31, 8.80it/s] 803it [01:31, 7.33it/s] 776it [01:31, 9.86it/s] 778it [01:31, 11.21it/s] 803it [01:31, 8.45it/s] 791it [01:31, 7.85it/s] 804it [01:31, 7.32it/s] 822it [01:31, 9.68it/s] 785it [01:31, 9.28it/s] 783it [01:31, 9.49it/s] 777it [01:31, 9.35it/s] 804it [01:31, 8.12it/s] 792it [01:32, 7.70it/s] 805it [01:32, 7.32it/s] 780it [01:32, 10.76it/s] 784it [01:32, 9.45it/s] 786it [01:32, 8.80it/s] 778it [01:32, 9.22it/s] 805it [01:32, 7.88it/s] 793it [01:32, 7.59it/s] 785it [01:32, 9.12it/s] 782it [01:32, 11.86it/s] 806it [01:32, 7.33it/s] 824it [01:32, 8.81it/s] 787it [01:32, 8.42it/s] 779it [01:32, 8.56it/s] 807it [01:32, 9.93it/s] 784it [01:32, 12.80it/s] 808it [01:32, 9.77it/s] 794it [01:32, 7.51it/s] 780it [01:32, 8.88it/s] 825it [01:32, 8.51it/s] 788it [01:32, 8.11it/s] 787it [01:32, 9.83it/s] 810it [01:32, 11.56it/s] 795it [01:32, 7.44it/s] 782it [01:32, 10.95it/s] 826it [01:32, 8.24it/s] 809it [01:32, 9.83it/s] 789it [01:32, 7.88it/s] 786it [01:32, 11.74it/s] 789it [01:32, 10.28it/s] 812it [01:32, 12.87it/s] 784it [01:32, 12.38it/s] 796it [01:32, 7.39it/s] 827it [01:32, 8.03it/s] 810it [01:32, 9.15it/s] 791it [01:32, 9.30it/s] 788it [01:32, 11.99it/s] 814it [01:32, 13.79it/s] 786it [01:32, 13.31it/s] 797it [01:32, 7.36it/s] 828it [01:32, 7.86it/s] 811it [01:32, 8.62it/s] 792it [01:32, 8.72it/s] 791it [01:32, 9.43it/s] 816it [01:32, 14.48it/s] 788it [01:32, 13.47it/s] 798it [01:32, 7.33it/s] 829it [01:32, 7.72it/s] 790it [01:32, 11.23it/s] 813it [01:32, 10.47it/s] 793it [01:32, 8.29it/s] 792it [01:32, 8.90it/s] 818it [01:32, 14.95it/s] 799it [01:32, 7.31it/s] 792it [01:32, 12.22it/s] 830it [01:32, 7.62it/s] 794it [01:33, 8.00it/s] 790it [01:33, 12.06it/s] 794it [01:33, 9.80it/s] 815it [01:33, 9.96it/s] 831it [01:33, 7.54it/s] 795it [01:33, 7.80it/s] 792it [01:33, 12.98it/s] 820it [01:33, 11.24it/s] 801it [01:33, 8.04it/s] 794it [01:33, 11.08it/s] 832it [01:33, 7.49it/s] 796it [01:33, 9.78it/s] 797it [01:33, 9.30it/s] 802it [01:33, 7.84it/s] 817it [01:33, 8.85it/s] 794it [01:33, 11.83it/s] 833it [01:33, 7.44it/s] 822it [01:33, 10.56it/s] 796it [01:33, 10.66it/s] 833it [01:33, 8.91it/s] - 798it [01:33, 9.98it/s] 798it [01:33, 8.72it/s] 803it [01:33, 7.69it/s] 818it [01:33, 8.48it/s] 796it [01:33, 11.19it/s] 799it [01:33, 8.30it/s] 804it [01:33, 7.57it/s] 798it [01:33, 10.17it/s] 819it [01:33, 8.18it/s] 800it [01:33, 10.32it/s] 824it [01:33, 9.29it/s] 798it [01:33, 12.26it/s] 800it [01:33, 8.01it/s] 805it [01:33, 7.48it/s] 820it [01:33, 7.95it/s] 802it [01:33, 10.35it/s] 800it [01:33, 9.64it/s] 802it [01:33, 9.77it/s] 806it [01:33, 7.41it/s] 821it [01:33, 7.76it/s] 800it [01:33, 11.42it/s] 826it [01:33, 8.58it/s] 801it [01:33, 9.09it/s] 803it [01:34, 9.04it/s] 807it [01:34, 7.37it/s] 822it [01:34, 7.63it/s] 802it [01:34, 10.90it/s] 804it [01:34, 9.08it/s] 802it [01:34, 8.62it/s] 828it [01:34, 8.99it/s] 804it [01:34, 8.53it/s] 808it [01:34, 7.34it/s] 823it [01:34, 7.53it/s] 805it [01:34, 8.61it/s] 803it [01:34, 8.24it/s] 829it [01:34, 8.64it/s] 809it [01:34, 7.33it/s] 804it [01:34, 10.30it/s] 806it [01:34, 8.85it/s] 825it [01:34, 8.41it/s] 806it [01:34, 8.80it/s] 810it [01:34, 7.31it/s] 805it [01:34, 8.77it/s] 831it [01:34, 9.07it/s] 808it [01:34, 10.19it/s] 826it [01:34, 8.06it/s] 811it [01:34, 7.31it/s] 808it [01:34, 9.19it/s] 806it [01:34, 9.15it/s] 832it [01:34, 8.64it/s] 806it [01:34, 8.36it/s] 810it [01:34, 11.62it/s] 828it [01:34, 9.42it/s] 812it [01:34, 7.31it/s] 807it [01:34, 8.76it/s] 833it [01:34, 8.30it/s] 810it [01:34, 9.20it/s] 833it [01:34, 8.79it/s] - 808it [01:34, 8.86it/s] 812it [01:34, 11.03it/s] 830it [01:34, 10.34it/s] 813it [01:34, 7.31it/s] 808it [01:34, 8.41it/s] 814it [01:34, 12.19it/s] 814it [01:34, 7.32it/s] 812it [01:35, 9.42it/s] 810it [01:35, 9.18it/s] 810it [01:35, 9.55it/s] 832it [01:35, 9.01it/s] 815it [01:35, 7.32it/s] 813it [01:35, 8.92it/s] 811it [01:35, 9.49it/s] 816it [01:35, 11.42it/s] 812it [01:35, 9.38it/s] 833it [01:35, 8.61it/s] 816it [01:35, 7.33it/s] 813it [01:35, 11.11it/s] 814it [01:35, 8.51it/s] 818it [01:35, 10.96it/s] 814it [01:35, 10.74it/s] 834it [01:35, 8.27it/s] 815it [01:35, 8.19it/s] 818it [01:35, 9.11it/s] 834it [01:35, 8.74it/s] - 820it [01:35, 12.07it/s] 815it [01:35, 9.82it/s] 816it [01:35, 7.94it/s] 816it [01:35, 10.41it/s] 820it [01:35, 10.24it/s] 822it [01:35, 12.93it/s] 817it [01:35, 7.75it/s] 817it [01:35, 9.58it/s] 822it [01:35, 9.85it/s] 824it [01:35, 11.79it/s] 818it [01:35, 7.60it/s] 818it [01:35, 9.14it/s] 818it [01:35, 9.02it/s] 823it [01:35, 9.17it/s] 819it [01:35, 7.50it/s] 826it [01:35, 12.10it/s] 820it [01:35, 10.43it/s] 819it [01:36, 8.56it/s] 825it [01:36, 10.20it/s] 821it [01:36, 9.71it/s] 822it [01:36, 10.45it/s] 828it [01:36, 11.36it/s] 821it [01:36, 9.00it/s] 822it [01:36, 8.94it/s] 827it [01:36, 10.93it/s] 830it [01:36, 12.36it/s] 822it [01:36, 8.56it/s] 824it [01:36, 9.89it/s] 824it [01:36, 8.81it/s] 823it [01:36, 8.22it/s] 829it [01:36, 9.40it/s] 832it [01:36, 11.19it/s] 826it [01:36, 10.11it/s] 825it [01:36, 8.41it/s] 833it [01:36, 8.62it/s] - 830it [01:36, 8.91it/s] 825it [01:36, 8.81it/s] 832it [01:36, 9.93it/s] 827it [01:36, 8.70it/s] 828it [01:36, 9.54it/s] 826it [01:36, 8.41it/s] 829it [01:36, 9.32it/s] 829it [01:36, 9.99it/s] 827it [01:36, 8.11it/s] 834it [01:37, 10.00it/s] 834it [01:37, 8.59it/s] - 831it [01:37, 9.45it/s] 831it [01:37, 9.89it/s] 829it [01:37, 8.49it/s] 832it [01:37, 8.91it/s] 832it [01:37, 9.25it/s] 830it [01:37, 8.19it/s] 833it [01:37, 8.46it/s] 833it [01:37, 8.75it/s] 833it [01:37, 8.55it/s] - 833it [01:37, 8.54it/s] - 832it [01:37, 8.55it/s] 833it [01:37, 8.24it/s] 833it [01:37, 8.52it/s] -Evaluating mmbench_test_en_20231003 ... -Results saved to results/mmbench_test_en_20231003_240807220052.xlsx -+ '[' mmbench-test-en == mmbench-test-cn ']' -+ '[' mmbench-test-en == ccbench-dev ']' -+ '[' mmbench-test-en == scienceqa ']' -+ '[' mmbench-test-en == mmmu-dev ']' -+ '[' mmbench-test-en == mmmu-val ']' -+ '[' mmbench-test-en == mmmu-test ']' -+ '[' mmbench-test-en == mmmu-dev-cot ']' -+ '[' mmbench-test-en == mmmu-val-cot ']' -+ '[' mmbench-test-en == mmmu-test-cot ']' -+ '[' mmbench-test-en == mmvp ']' -+ '[' mmbench-test-en == mathvista-testmini ']' -+ '[' mmbench-test-en == mathvista-test ']' -+ '[' mmbench-test-en == seed ']' -+ '[' mmbench-test-en == mvbench ']'