config.json

{
  "_name_or_path": "microsoft/resnet-152",
  "architectures": [
    "ResNetForImageClassification"
  ],
  "depths": [
    3,
    8,
    36,
    3
  ],
  "downsample_in_bottleneck": false,
  "downsample_in_first_stage": false,
  "embedding_size": 64,
  "hidden_act": "relu",
  "hidden_sizes": [
    256,
    512,
    1024,
    2048
  ],
  "id2label": {
    "0": "left",
    "1": "right",
    "2": "parietal",
    "3": "temporal",
    "4": "frontal",
    "5": "occipital",
    "6": "basal_ganglia",
    "7": "necrotic",
    "8": "cystic",
    "9": "glioblastoma_multiforme",
    "10": "astrocytoma",
    "11": "glioma",
    "12": "metastasis",
    "13": "abscess",
    "14": "dysembryoplastic_neuroepithelial_tumor"
  },
  "label2id": {
    "abscess": 13,
    "astrocytoma": 10,
    "basal_ganglia": 6,
    "cystic": 8,
    "dysembryoplastic_neuroepithelial_tumor": 14,
    "frontal": 4,
    "glioblastoma_multiforme": 9,
    "glioma": 11,
    "left": 0,
    "metastasis": 12,
    "necrotic": 7,
    "occipital": 5,
    "parietal": 2,
    "right": 1,
    "temporal": 3
  },
  "layer_type": "bottleneck",
  "model_type": "resnet",
  "num_channels": 3,
  "out_features": [
    "stage4"
  ],
  "out_indices": [
    4
  ],
  "problem_type": "multi_label_classification",
  "stage_names": [
    "stem",
    "stage1",
    "stage2",
    "stage3",
    "stage4"
  ],
  "torch_dtype": "float32",
  "transformers_version": "4.47.0"
}