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How to train VQA on my custom data? #73
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Hi, could you please provide the exact script you run on your machine and the information of your GPU-cards type? I will have a check on my environment. |
Moreover, for fine-tuning on customed VQA-formated data, please also refer to this recent issue for more information #76. |
Hi, have you checked the path of |
Thanks! It seems to be a problem with my image that is causing this, I am using the code you replied to in issue #56 for imgbase64. |
Hi, please check whether the fields of the input data line which caused this error correspond with the specified |
Hi, I think there is a misunderstanding of how each data line is organized. As mentioned in the readme, in each line in TSV file, the fields follow the exact order of question-id, image-id, question, answer (with confidence), predicted object labels and image base64 string, thus there are 6 fields in total in the TSV file (also the image-id field is not used). By specifying the |
By the way, for preparing the dataset TSV file, I would also recommend to prepare an original training sample with more than one golden answers into multiple samples each of which contains only one of the answers. This will take full advantage of the supervision of ground-truth answers of training samples. Otherwise, only the golden answer with the highest confidence score will be used as supervision. |
how you resolve this problem? I''m having same problem. Thanks |
Hello! I am trying to finetune OFA-large on VQA using custom dataset, using the finetuning instruction in the repo. I have checked my .tsv and .pkl file several times and they are correct as your provided sample. But after command "bash train_vqa_distributed.sh", the terminal just prints:
total_num_updates 40000
warmup_updates 1000
lr 5e-5
patch_image_size 480
The GPU usage will rise to a certain value and then suddenly return to zero, and then the program will end. I train on single server with 2 GPU. Looking forward to reply, thanks for your sharing work!
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