| from .pretrain import * | |
| del available_corpus | |
| train_file = [ | |
| f"{anno_root_downstream}/tvqa_train_with_answer.json", | |
| f"{data_root}/tvqa_trimmed_3fps", | |
| "video", | |
| ] | |
| test_file = dict( | |
| val=[ | |
| f"{anno_root_downstream}/tvqa_val_with_answer.json", | |
| f"{data_root}/tvqa_trimmed_3fps", | |
| "video", | |
| ], | |
| test=[ | |
| f"{anno_root_downstream}/tvqa_test_public_with_answer.json", | |
| f"{data_root}/tvqa_trimmed_3fps", | |
| "video", | |
| ], | |
| ) | |
| test_types = ["val"] | |
| stop_key = "val" # used to choose the best ckpt. If None, save the last. | |
| is_paragraph_retrieval = False | |
| criterion["loss_weight"]["mlm"] = 0.0 | |
| optimizer["lr"] = 1e-5 | |
| scheduler["warmup_epochs"] = 0.5 | |
| scheduler["epochs"] = 10 | |
| max_txt_l = 150 | |
| batch_size = 32 | |
| num_frames = 12 | |
| log_freq = 100 | |