add supervised training pipeline
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meta:
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model_name: vit_huge
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embed_dim: 1280
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load_checkpoint: true
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read_checkpoint: jepa-latest.pth.tar
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use_bfloat16: true
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num_classes: 182
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data:
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batch_size: 128
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root_path: ./wilds_data
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num_workers: 10
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pin_mem: true
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crop_size: 224
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optimization:
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optimizer: adamw # 'adamw' or 'sgd'
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freeze_weights: true # true for linear probing, false for full fine-tuning
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epochs: 50
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lr: 0.001
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weight_decay: 0.05
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start_lr: 0.0001
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final_lr: 1.0e-06
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warmup: 5
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ipe_scale: 1.0
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logging:
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folder: experiment_logs/supervised-vith14.224-bs.128-ep.300/
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write_tag: linear_probe
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