swin-base-best-model / config.json
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{
"_name_or_path": "/content/drive/MyDrive/AML-group/Project/model_Swin_b",
"architectures": [
"SwinForImageClassification"
],
"attention_probs_dropout_prob": 0.0,
"depths": [
2,
2,
18,
2
],
"drop_path_rate": 0.1,
"embed_dim": 128,
"encoder_stride": 32,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.0,
"hidden_size": 1024,
"id2label": {
"0": "cardboard",
"1": "glass",
"2": "metal",
"3": "paper",
"4": "plastic",
"5": "trash"
},
"image_size": 224,
"initializer_range": 0.02,
"label2id": {
"cardboard": "0",
"glass": "1",
"metal": "2",
"paper": "3",
"plastic": "4",
"trash": "5"
},
"layer_norm_eps": 1e-05,
"mlp_ratio": 4.0,
"model_type": "swin",
"num_channels": 3,
"num_heads": [
4,
8,
16,
32
],
"num_layers": 4,
"patch_size": 4,
"path_norm": true,
"problem_type": "single_label_classification",
"qkv_bias": true,
"torch_dtype": "float32",
"transformers_version": "4.25.1",
"use_absolute_embeddings": false,
"window_size": 7
}