finetune_modelnet_pgst.yaml

optimizer: { type: AdamW,part: adapt,  kwargs: { lr: 0.0001, weight_decay: 0.05 } }

scheduler: { type: CosLR, kwargs: { epochs: 50, initial_epochs: 10 } }

dataset:
  {
    train:
      {
        _base_: cfgs/dataset_configs/ModelNet40.yaml,
        others: { subset: "train" },
      },
    val:
      {
        _base_: cfgs/dataset_configs/ModelNet40.yaml,
        others: { subset: "test" },
      },
    test:
      {
        _base_: cfgs/dataset_configs/ModelNet40.yaml,
        others: { subset: "test" },
      },
  }
model:
  {
    NAME: GPT_Transformer_PGST,
    trans_dim: 1024,
    depth: 24,
    drop_path_rate: 0.2,
    cls_dim: 40,
    num_heads: 16,
    group_size: 32,
    num_group: 64,
    encoder_dims: 1024,
    decoder_depth: 4,
    loss: cdl2,
    weight_center: 1,
    rank: 36,
    local: 32,
  }

npoints: 1024
total_bs: 128
step_per_update: 1
max_epoch: 50
grad_norm_clip: 10