base_configs: 
  - config/base.yaml
  - config/cluster_paths_inat.yaml
name: swin_v2_tiny_1e-4_xl_512_256_context_2chips
fsdp: off
fp16: off
data:
  dataset: inaturalist
  crop_size: 512 
  val_crop_size: 512
  batch_size: ${train.batch_size}
  val_batch_size: ${train.val_batch_size}
  num_workers: 1
  num_classes: 284
  interpolation: bilinear
  test_crop: False
  aug:
    auto_augment: rand-m9-mstd0.5-inc1
    color_jitter: 0.4
    reprob: 0.0
    remode: pixel
    recount: 1
    mixup: 0.0
    cutmix: 0.0
    label_smoothing: 0.3
    random_resized_crop: False
    mean: [0.485, 0.456, 0.406]
    std: [0.229, 0.224, 0.225]
  supercategories:
    - Reptilia
model: 
  name: EncoderDecoderV2
  num_classes: ${data.num_classes}
  mlp_ratio: 4
  backbone_class: swinv2_tiny_window16_256_timm
  backbone:
    img_size: 256
    input_dim: 3
    use_vanilla_backward: False
    pretrained: ${oc.env:PRETRAINED_CKPT_PATH, "./ckpts"}/swinv2_base_patch4_window16_256.pth
    upsample: False
  cls_head: xl
  xl_context:
    skip_connection: off
    enabled: off
    hidden_size: 768
    classification_mode: off
    in_context_patches: 128
    tiling: naive_two_stream
    n_layer: 2
    mem_chip: 2
  resume: ''
optimizer:
  name: adamw
  lr: 1e-4
  classifier_ratio: 1.0
  warmup_epochs: 0
train:
  epochs: 100
  batch_size: 30
  val_batch_size: 1
  freeze_epochs: 0
  test_every: 1
  test_reset: True
  clip_grad: 5.0
val: False
losses:
  losses:
    - name: cls
      type: CrossEntropy
      params: 
        field: label 
      weight: 1.0
      display: on