config.json

{
  "_name_or_path": "microsoft/resnet-50",
  "architectures": [
    "ResNetForImageClassification"
  ],
  "depths": [
    3,
    4,
    6,
    3
  ],
  "downsample_in_first_stage": false,
  "embedding_size": 64,
  "hidden_act": "relu",
  "hidden_sizes": [
    256,
    512,
    1024,
    2048
  ],
  "id2label": {
    "0": "letter",
    "1": "form",
    "2": "email",
    "3": "handwritten",
    "4": "advertisement",
    "5": "scientific_report",
    "6": "scientific_publication",
    "7": "specification",
    "8": "file_folder",
    "9": "news_article",
    "10": "budget",
    "11": "invoice",
    "12": "presentation",
    "13": "questionnaire",
    "14": "resume",
    "15": "memo"
  },
  "label2id": {
    "advertisement": 4,
    "budget": 10,
    "email": 2,
    "file_folder": 8,
    "form": 1,
    "handwritten": 3,
    "invoice": 11,
    "letter": 0,
    "memo": 15,
    "news_article": 9,
    "presentation": 12,
    "questionnaire": 13,
    "resume": 14,
    "scientific_publication": 6,
    "scientific_report": 5,
    "specification": 7
  },
  "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": "4.33.3"
}