| MODEL: | |
| WEIGHTS: '' | |
| compute_precision: | |
| grad_scaler: true | |
| teacher: | |
| backbone: | |
| sharding_strategy: SHARD_GRAD_OP | |
| mixed_precision: | |
| param_dtype: fp16 | |
| reduce_dtype: fp16 | |
| buffer_dtype: fp32 | |
| dino_head: | |
| sharding_strategy: SHARD_GRAD_OP | |
| mixed_precision: | |
| param_dtype: fp16 | |
| reduce_dtype: fp16 | |
| buffer_dtype: fp32 | |
| ibot_head: | |
| sharding_strategy: SHARD_GRAD_OP | |
| mixed_precision: | |
| param_dtype: fp16 | |
| reduce_dtype: fp16 | |
| buffer_dtype: fp32 | |
| student: | |
| backbone: | |
| sharding_strategy: SHARD_GRAD_OP | |
| mixed_precision: | |
| param_dtype: fp16 | |
| reduce_dtype: fp16 | |
| buffer_dtype: fp32 | |
| dino_head: | |
| sharding_strategy: SHARD_GRAD_OP | |
| mixed_precision: | |
| param_dtype: fp16 | |
| reduce_dtype: fp32 | |
| buffer_dtype: fp32 | |
| ibot_head: | |
| sharding_strategy: SHARD_GRAD_OP | |
| mixed_precision: | |
| param_dtype: fp16 | |
| reduce_dtype: fp32 | |
| buffer_dtype: fp32 | |
| dino: | |
| loss_weight: 1.0 | |
| head_n_prototypes: 65536 | |
| head_bottleneck_dim: 256 | |
| head_nlayers: 3 | |
| head_hidden_dim: 2048 | |
| koleo_loss_weight: 0.1 | |
| ibot: | |
| loss_weight: 1.0 | |
| mask_sample_probability: 0.5 | |
| mask_ratio_min_max: | |
| - 0.1 | |
| - 0.5 | |
| separate_head: false | |
| head_n_prototypes: 65536 | |
| head_bottleneck_dim: 256 | |
| head_nlayers: 3 | |
| head_hidden_dim: 2048 | |
| train: | |
| batch_size_per_gpu: 64 | |
| dataset_path: ImageNet:split=TRAIN | |
| output_dir: . | |
| saveckp_every_n_epoch: 5 | |
| seed: 0 | |
| num_workers: 10 | |
| OFFICIAL_EPOCH_LENGTH: 0 # automatic rescaling based on the dataset len is applied if this is set to 0 | |
| cache_dataset: true | |
| centering: "centering" # or "sinkhorn_knopp" | |
| student: | |
| arch: vit_large | |
| patch_size: 16 | |
| drop_block_rate: 0.0 | |
| drop_path_rate: 0.3 | |
| layerscale: 1.0e-05 | |
| drop_path_uniform: true | |
| pretrained_weights: '' | |
| ffn_layer: "mlp" | |
| block_chunks: 0 | |
| qkv_bias: true | |
| proj_bias: true | |
| ffn_bias: true | |
| num_register_tokens: 0 | |
| interpolate_antialias: false | |
| interpolate_offset: 0.1 | |
| load_weights: true | |
| checkpoints_dir: null | |
| teacher: | |
| momentum_teacher: 0.992 | |
| final_momentum_teacher: 1 | |
| warmup_teacher_temp: 0.04 | |
| teacher_temp: 0.07 | |
| warmup_teacher_temp_epochs: 30 | |
| optim: | |
| epochs: 100 | |
| weight_decay: 0.04 | |
| weight_decay_end: 0.4 | |
| base_lr: 0.004 # learning rate for a batch size of 1024 | |
| lr: 0. # will be set after applying scaling rule | |
| warmup_epochs: 10 | |
| min_lr: 1.0e-06 | |
| clip_grad: 3.0 | |
| freeze_last_layer_epochs: 1 | |
| scaling_rule: sqrt_wrt_1024 | |
| patch_embed_lr_mult: 0.2 | |
| layerwise_decay: 0.9 | |
| adamw_beta1: 0.9 | |
| adamw_beta2: 0.999 | |
| crops: | |
| global_crops_scale: | |
| - 0.32 | |
| - 1.0 | |
| local_crops_number: 8 | |
| local_crops_scale: | |
| - 0.05 | |
| - 0.32 | |
| global_crops_size: 224 | |
| local_crops_size: 96 | |
| evaluation: | |
| eval_period_iterations: 12500 | |
| dataset_str: None | |
| online: # see dinov2.eval.linear_callback for documentation | |
| learning_rate: 1e-6 # will be multiplied by batch size and number of devices | |
| num_last_blocks: 1 | |
| add_avg_pool: true | |
| num_update_epochs_per_eval: 3 | |
| augmentation: | |
| degrees: 30 | |
| scale: | |
| - 0.8 | |
| - 1.2 | |
| shear: 15 | |
| interpolation: BICUBIC | |
| horizontal_flip: true | |