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vith16_k400_16x8x3.yaml

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+nodes: 8
+tasks_per_node: 8
+tag: k400-16x8x3
+eval_name: video_classification_frozen
+resume_checkpoint: false
+data:
+  dataset_train: /your_path_to_kinetics400_train_csv_file_index.csv
+  dataset_val: /your_path_to_kinetics400_val_csv_file_index.csv
+  dataset_type: VideoDataset
+  num_classes: 400
+  frames_per_clip: 16
+  num_segments: 8
+  num_views_per_segment: 3
+  frame_step: 4
+optimization:
+  attend_across_segments: true
+  num_epochs: 20
+  resolution: 224
+  batch_size: 4
+  weight_decay: 0.01
+  lr: 0.001
+  start_lr: 0.001
+  final_lr: 0.0
+  warmup: 0.
+  use_bfloat16: true
+pretrain:
+  model_name: vit_huge
+  checkpoint_key: target_encoder
+  clip_duration: null
+  frames_per_clip: 16
+  tubelet_size: 2
+  uniform_power: true
+  use_silu: false
+  tight_silu: false
+  use_sdpa: true
+  patch_size: 16
+  folder: /your_absolute_file_path_to_directory_where_pretrained_models_are_contained/
+  checkpoint: jepa-latest.pth.tar  # name of pretrained model file inside folder
+  write_tag: jepa

vitl16_k400_16x8x3.yaml

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+nodes: 8
+tasks_per_node: 8
+tag: k400-16x8x3
+eval_name: video_classification_frozen
+resume_checkpoint: false
+data:
+  dataset_train: /your_path_to_kinetics400_train_csv_file_index.csv
+  dataset_val: /your_path_to_kinetics400_val_csv_file_index.csv
+  dataset_type: VideoDataset
+  num_classes: 400
+  frames_per_clip: 16
+  num_segments: 8
+  num_views_per_segment: 3
+  frame_step: 4
+optimization:
+  attend_across_segments: true
+  num_epochs: 20
+  resolution: 224
+  batch_size: 4
+  weight_decay: 0.01
+  lr: 0.001
+  start_lr: 0.001
+  final_lr: 0.0
+  warmup: 0.
+  use_bfloat16: true
+pretrain:
+  model_name: vit_large
+  checkpoint_key: target_encoder
+  clip_duration: null
+  frames_per_clip: 16
+  tubelet_size: 2
+  uniform_power: true
+  use_silu: false
+  tight_silu: false
+  use_sdpa: true
+  patch_size: 16
+  folder: /your_absolute_file_path_to_directory_where_pretrained_models_are_contained/
+  checkpoint: jepa-latest.pth.tar  # name of pretrained model file inside folder
+  write_tag: jepa