Hi, the validation accuracy I calculated for the fine-tuned models are different from the paper.
Command:
python -m torch.distributed.launch --nproc_per_node 2 tools/run.py --tasks vqa --datasets m4c_textvqa --model m4c_split \
--config $config \
--save_dir $folder \
--run_type val \
--resume_file $finetuned_model \
training_parameters.distributed True
I observed changing the batch size results in different values.
|
Val accuracy for batch size = 32 |
Val acc for batch size = 128 |
In paper |
|
| TextVQA TAP (base) |
49.87 |
49.53 |
49.91 |
|
| TextVQA TAP (additional data) |
54.31 |
54.13 |
54.71 |
|
Hi, the validation accuracy I calculated for the fine-tuned models are different from the paper.
Command:
I observed changing the batch size results in different values.