config.json

{
  "_name_or_path": "microsoft/resnet-50",
  "architectures": [
    "ResNetForImageClassification"
  ],
  "depths": [
    3,
    4,
    6,
    3
  ],
  "downsample_in_bottleneck": false,
  "downsample_in_first_stage": false,
  "embedding_size": 64,
  "hidden_act": "relu",
  "hidden_sizes": [
    256,
    512,
    1024,
    2048
  ],
  "id2label": {
    "0": "aluminium",
    "1": "batteries",
    "10": "takeaway cups",
    "2": "cardboard",
    "3": "disposable plates",
    "4": "glass",
    "5": "hard plastic",
    "6": "paper",
    "7": "paper towel",
    "8": "polystyrene",
    "9": "soft plastics"
  },
  "label2id": {
    "aluminium": "0",
    "batteries": "1",
    "cardboard": "2",
    "disposable plates": "3",
    "glass": "4",
    "hard plastic": "5",
    "paper": "6",
    "paper towel": "7",
    "polystyrene": "8",
    "soft plastics": "9",
    "takeaway cups": "10"
  },
  "layer_type": "bottleneck",
  "model_type": "resnet",
  "num_channels": 3,
  "out_features": [
    "stage4"
  ],
  "out_indices": [
    4
  ],
  "problem_type": "single_label_classification",
  "stage_names": [
    "stem",
    "stage1",
    "stage2",
    "stage3",
    "stage4"
  ],
  "torch_dtype": "float32",
  "transformers_version": "4.41.2"
}