The model meter_clip16_288_roberta_flickr.ckpt is inconsistent with the network weight parameter dimension

[attutude]

Hi,
Thank you for your excellent work, may I use this model "METER-CLIP16-RoBERTa fine-tuned on Flickr30k IR/TR (resolution: 384^2)" as meter_clip16_288_roberta_flickr.ckpt, why does the code report this error showing inconsistent dimensions, thank you answer my question.

[zdou0830]

it seems that you are using BERT and CLIP32 as the text and image encoder while the checkpoint is based on RoBERTa and CLIP16. As in README, an example command is:

python run.py with data_root=/data2/dsets/dataset num_gpus=8 num_nodes=1 task_finetune_irtr_f30k_clip_bert get_recall_metric=True per_gpu_batchsize=32 load_path=meter_f30k.ckpt clip16 text_roberta image_size=384 test_only=True

[attutude]

it seems that you are using BERT and CLIP32 as the text and image encoder while the checkpoint is based on RoBERTa and CLIP16. As in README, an example command is:

python run.py with data_root=/data2/dsets/dataset num_gpus=8 num_nodes=1 task_finetune_irtr_f30k_clip_bert get_recall_metric=True per_gpu_batchsize=32 load_path=meter_f30k.ckpt clip16 text_roberta image_size=384 test_only=True

Thank you for your answer, can you please publish the weights of the merged attention model, thank you very much.

[zdou0830]

Hi, see #21

[attutude]

Hi, see #21

OK, thanks