resnet-50 / config.json
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{
"_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": "Audemars Piguet",
"1": "Breguet",
"2": "Breitling",
"3": "Maurice Lacroix",
"4": "Omega",
"5": "Patek Philippe",
"6": "Rado",
"7": "Rolex",
"8": "Tissot",
"9": "Vacheron Constantin"
},
"label2id": {
"Audemars Piguet": 0,
"Breguet": 1,
"Breitling": 2,
"Maurice Lacroix": 3,
"Omega": 4,
"Patek Philippe": 5,
"Rado": 6,
"Rolex": 7,
"Tissot": 8,
"Vacheron Constantin": 9
},
"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": "4.40.1"
}