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config.json

@@ -1,6 +1,6 @@
 {
-  "model_type": "densenet121",
-  "base_model": "densenet121",
+  "model_type": "efficientnet_v2_s",
+  "base_model": "efficientnet_v2_s",
   "task": "image-classification",
   "num_labels": 8,
   "id2label": {
@@ -29,21 +29,22 @@
     3
   ],
   "preprocessing": {
-    "mode": "densenet_preprocess_input",
+    "mode": "efficientnet_v2_preprocess_input",
     "mean": [
-      123.675,
-      116.28,
-      103.53
+      0.0,
+      0.0,
+      0.0
     ],
     "std": [
-      58.395,
-      57.12,
-      57.375
+      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": "World Architectural Buildings (13440 images, 8 classes, balanced)",
+    "dataset_source": "Pexels Architectural Buildings (13440 images, 8 classes, balanced)",
     "dataset_size": 13440,
     "split_ratio": [
       0.8,
@@ -53,30 +54,30 @@
     "split_seed": 42,
     "phases": [
       {
-        "name": "Phase 1 - Feature Extraction (Head)",
+        "name": "Fase 1 - Feature Extraction (Head)",
         "optimizer": "AdamW",
         "lr": 0.001,
         "epochs_max": 25,
         "epochs_actual": 1,
-        "val_accuracy": 0.8921,
-        "val_loss": 1.2231,
-        "train_accuracy": 0.5318,
+        "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": "Phase 2 - Selective Fine-Tuning",
+        "name": "Fase 2 - Selective Fine-Tuning",
         "optimizer": "DiscriminativeAdamW",
         "lr": 0.0003,
         "epochs_max": 50,
-        "epochs_actual": 6,
-        "val_accuracy": 0.9204,
-        "val_loss": 0.6171,
-        "train_accuracy": 0.911,
-        "unfreeze": "conv4_block+conv5_block (BN frozen)",
+        "epochs_actual": 1,
+        "val_accuracy": 0.9628,
+        "val_loss": 0.5655,
+        "train_accuracy": 0.8496,
+        "unfreeze": "block6+top_conv (BN frozen)",
         "discriminative_lr": {
-          "conv4_block": 0.1
+          "block6": 0.1
         },
         "cutmix_mixup": false,
         "label_smoothing": 0.05,
@@ -88,70 +89,70 @@
         "lr": 0.0001,
         "bn_update": true,
         "bn_update_steps": 100,
-        "val_accuracy": 0.9658,
-        "val_loss": 0.4256,
+        "val_accuracy": 0.9836,
+        "val_loss": 0.4109,
         "method": "Izmailov et al., UAI 2018"
       }
     ],
     "metrics": {
       "train_accuracy": 0.9988,
-      "val_accuracy": 0.9658,
-      "test_accuracy": 0.9688,
-      "test_loss": 0.4485,
-      "tta_accuracy": 0.968,
-      "overfitting_gap": 0.03,
-      "test_correct": 1302,
+      "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": 0.9691,
-      "macro_recall": 0.9688,
-      "macro_f1": 0.9687,
+      "macro_precision": 0.9777,
+      "macro_recall": 0.9777,
+      "macro_f1": 0.9777,
       "per_class_f1": {
-        "barn": 0.9674,
-        "bridge": 0.9645,
-        "castle": 0.9735,
-        "mosque": 0.9735,
-        "skyscraper": 0.9794,
-        "stadium": 0.96,
+        "barn": 0.9731,
+        "bridge": 0.9676,
+        "castle": 0.9792,
+        "mosque": 0.9792,
+        "skyscraper": 0.994,
+        "stadium": 0.9791,
         "temple": 0.9668,
-        "windmill": 0.9647
+        "windmill": 0.9822
       },
       "per_class_recall": {
         "barn": 0.9702,
-        "bridge": 0.9702,
+        "bridge": 0.9762,
         "castle": 0.9821,
         "mosque": 0.9821,
-        "skyscraper": 0.9881,
-        "stadium": 0.9286,
+        "skyscraper": 0.994,
+        "stadium": 0.9762,
         "temple": 0.9524,
-        "windmill": 0.9762
+        "windmill": 0.9881
       },
       "checkpoint_comparison": {
-        "best_phase2_swa": {
-          "val_accuracy": 0.9658,
-          "val_loss": 0.4256,
+        "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
         },
-        "best_phase2": {
-          "val_accuracy": 0.9204,
-          "val_loss": 0.6171,
+        "fine_tuning_ema": {
+          "val_accuracy": 0.9353,
+          "val_loss": 0.6007,
           "rank": 2
         },
-        "best_phase2_ema": {
-          "val_accuracy": 0.8936,
-          "val_loss": 0.8183,
+        "head_training": {
+          "val_accuracy": 0.9234,
+          "val_loss": 1.0109,
           "rank": 3
-        },
-        "best_phase1": {
-          "val_accuracy": 0.8921,
-          "val_loss": 1.2231,
-          "rank": 4
         }
       }
     }
   },
   "version": "v6",
   "license": "apache-2.0",
-  "github": "https://github.com/arcxteam/arch-building-classifier",
+  "github": "https://github.com/arcxteam/building-architectural-image-classifier",
   "author": {
     "name": "Saugani",
     "email": "team@greyscope.xyz"