vitl16_k400_16x8x3.yaml

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