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"model_type": "efficientnetv2-s",
"base_model": "efficientnetv2-s",
"task": "image-classification",
"num_labels": 8,
"id2label": {
"0": "barn",
"1": "bridge",
"2": "castle",
"3": "mosque",
"4": "skyscraper",
"5": "stadium",
"6": "temple",
"7": "windmill"
},
"label2id": {
"barn": 0,
"bridge": 1,
"castle": 2,
"mosque": 3,
"skyscraper": 4,
"stadium": 5,
"temple": 6,
"windmill": 7
},
"input_shape": [
320,
320,
3
],
"preprocessing": {
"mode": "efficientnet_v2_preprocess_input",
"mean": [
0.0,
0.0,
0.0
],
"std": [
1.0,
1.0,
1.0
],
"note": "preprocess_input is identity in TF 2.12+; EfficientNetV2-S includes internal Rescaling layer. Input expects raw [0, 255] float32.",
"channel_order": "RGB"
},
"training_info": {
"dataset_source": "Pexels Architectural Buildings (13440 images, 8 classes, balanced)",
"dataset_size": 13440,
"split_ratio": [
0.8,
0.1,
0.1
],
"split_seed": 42,
"phases": [
{
"name": "Fase 1 - Feature Extraction (Head)",
"optimizer": "AdamW",
"lr": 0.001,
"epochs_max": 25,
"epochs_actual": 1,
"val_accuracy": 0.9234,
"val_loss": 1.0109,
"train_accuracy": 0.5696,
"cutmix_mixup": true,
"label_smoothing": 0.1,
"early_stop_reason": "myCallback val_acc >= 0.85"
},
{
"name": "Fase 2 - Selective Fine-Tuning",
"optimizer": "DiscriminativeAdamW",
"lr": 0.0003,
"epochs_max": 50,
"epochs_actual": 1,
"val_accuracy": 0.9628,
"val_loss": 0.5655,
"train_accuracy": 0.8496,
"unfreeze": "block6+top_conv (BN frozen)",
"discriminative_lr": {
"block6": 0.1
},
"cutmix_mixup": false,
"label_smoothing": 0.05,
"early_stop_reason": "myCallback val_acc >= 0.92"
},
{
"name": "SWA Post-Training",
"epochs": 10,
"lr": 0.0001,
"bn_update": true,
"bn_update_steps": 100,
"val_accuracy": 0.9836,
"val_loss": 0.4109,
"method": "Izmailov et al., UAI 2018"
}
],
"metrics": {
"train_accuracy": 0.9988,
"val_accuracy": 0.9836,
"test_accuracy": 0.9777,
"test_loss": 0.4262,
"tta_accuracy": 0.9799,
"overfitting_gap": 0.0211,
"test_correct": 1314,
"test_total": 1344,
"macro_precision": 0.9777,
"macro_recall": 0.9777,
"macro_f1": 0.9777,
"per_class_f1": {
"barn": 0.9731,
"bridge": 0.9676,
"castle": 0.9792,
"mosque": 0.9792,
"skyscraper": 0.994,
"stadium": 0.9791,
"temple": 0.9668,
"windmill": 0.9822
},
"per_class_recall": {
"barn": 0.9702,
"bridge": 0.9762,
"castle": 0.9821,
"mosque": 0.9821,
"skyscraper": 0.994,
"stadium": 0.9762,
"temple": 0.9524,
"windmill": 0.9881
},
"checkpoint_comparison": {
"fine_tuning_swa": {
"val_accuracy": 0.9836,
"val_loss": 0.4109,
"rank": 0
},
"fine_tuning": {
"val_accuracy": 0.9628,
"val_loss": 0.5655,
"rank": 1
},
"fine_tuning_ema": {
"val_accuracy": 0.9353,
"val_loss": 0.6007,
"rank": 2
},
"head_training": {
"val_accuracy": 0.9234,
"val_loss": 1.0109,
"rank": 3
}
}
}
},
"version": "v6",
"license": "apache-2.0",
"github": "https://github.com/arcxteam/building-architectural-image-classifier",
"author": {
"name": "Saugani",
"email": "team@greyscope.xyz"
}
} |