Download reproduction/protocol.json from Yang0822/SlimFormerPlusPlus-AMOS2022-CT: direct link, hf CLI and curl.
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https://huggingface.co/Yang0822/SlimFormerPlusPlus-AMOS2022-CT/resolve/main/reproduction/protocol.json
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curl -L -o protocol.json https://huggingface.co/Yang0822/SlimFormerPlusPlus-AMOS2022-CT/resolve/main/reproduction/protocol.json
2.27 kB
| { | |
| "alias": "amos-ct", | |
| "dataset": "Dataset004_AMOS", | |
| "dataset_id": 4, | |
| "model_folder": "nnUNetTrainer_SlimFormerPlusPlus__nnUNetPlans__3d_fullres", | |
| "release_tag": "amos2022-ct-best-v1", | |
| "checkpoint": "checkpoint_best.pth", | |
| "checkpoint_sha256": "20fba6d680922bcb31ed69e7dab655b7607d366bc451e8843a6a84ceca9e9780", | |
| "checkpoint_current_epoch": 1199, | |
| "trainer_sha256": "ecb4ff6bc99d724248e8215a0c435e8e30cca4e96a122588317ed11a13bb1245", | |
| "split": { | |
| "fold": 0, | |
| "train_cases": 200, | |
| "validation_cases": 100, | |
| "evaluation_set": "single-fold validation; not an independent test set" | |
| }, | |
| "training": { | |
| "run": "slimformer-plusplus-ep1200-b8", | |
| "completed_epochs": 1200, | |
| "optimizer_steps_per_epoch": 250, | |
| "validation_iterations_per_epoch": 50, | |
| "global_batch": 8, | |
| "gpus": 4, | |
| "per_gpu_batch": 2, | |
| "initialization_seed": 20260921, | |
| "optimizer": "SGD", | |
| "initial_lr": 0.01, | |
| "momentum": 0.99, | |
| "nesterov": true, | |
| "weight_decay": 3e-05, | |
| "no_weight_decay": [ | |
| "theta", | |
| "relation_bias" | |
| ], | |
| "scheduler": "PolyLR", | |
| "poly_exponent": 0.9, | |
| "deep_supervision": false, | |
| "compile": false, | |
| "best_selection": "highest validation EMA pseudo-Dice" | |
| }, | |
| "inference": { | |
| "configuration": "3d_fullres", | |
| "patch": [ | |
| 64, | |
| 192, | |
| 160 | |
| ], | |
| "tile_step_size": 0.5, | |
| "gaussian_weighting": true, | |
| "mirroring_axes": [ | |
| 0, | |
| 1, | |
| 2 | |
| ], | |
| "ensemble": false, | |
| "postprocessing": false | |
| }, | |
| "metrics": { | |
| "aggregation": "mean over cases per foreground label, then mean over labels", | |
| "Dice_IoU_units": "fraction", | |
| "HD95_ASD_units": "mm", | |
| "implementation": "reproduce.py; project evaluation convention" | |
| }, | |
| "provenance": { | |
| "network_weights_verified_equal_to_release": true, | |
| "plans_and_dataset_verified_equal_to_release": true, | |
| "source_summary_sha256": "5a82c435ee4f98c594824bde6a980f0a1360a3c5e215e415d76ce51b24a5733c", | |
| "source_surface_summary_sha256": "11e9066b7421381f92b54b161a73e091b7d3296018e7e0e4da82791d96492846", | |
| "source_splits_sha256": "a0429db779ceed5a4b5b42132f643f9dee735cb28876012bd3e0a2c1b368a8aa", | |
| "efficiency_source": "measure_slimformer_plusplus_mixswap_ft_cost.py, baseline arm" | |
| } | |
| } | |