Update alter_config.json

alter_config.json

@@ -1,22 +1,33 @@
 {
-    "model_type": "ConcatModelWithRationale",
-    "hatebert_model": "GroNLP/hateBERT",
-    "rationale_model": "bert-base-uncased",
-    "cnn_num_filters": 128,
-    "cnn_kernel_sizes": [2, 3, 4],
+  "model_type": "ConcatModelWithRationale",
+  "hatebert_model": "GroNLP/HateBERT",
+  "rationale_model": "bert-base-uncased",
+
+  "training_config": {
+    "cnn_filters": 128,
+    "cnn_kernels": [2, 3, 4],
+    "cnn_dropout": 0.3,
     "adapter_dim": 128,
     "max_length": 128,
     "num_labels": 2,
-    "architecture": {
-        "temporal_cnn": "TemporalCNN",
-        "msa_cnn": "MultiScaleAttentionCNN",
-        "projection": "ProjectionMLP"
-    },
-    "training_info": {
-        "batch_size": 8,
-        "learning_rate": 1e-5,
-        "weight_decay": 0.05,
-        "dropout": 0.5,
-        "best_val_loss": 0.27
-    }
+
+    "batch_size": 8,
+    "learning_rate": 2e-5,
+    "weight_decay": 0.05,
+    "best_val_f1": 0.00
+  },
+
+  "architecture": {
+    "temporal_cnn": "TemporalCNN (max+mean pooling)",
+    "msa_cnn": "MultiScaleAttentionCNN (token attention pooling)",
+    "selector": "Gumbel-Sigmoid Token Selector",
+    "projection": "ProjectionMLP (concat CLS + CNN + rationale pooled)"
+  },
+
+  "notes": {
+    "trained_with": "ConcatModelWithRationale",
+    "framework": "PyTorch + Transformers",
+    "encoder_main": "HateBERT",
+    "encoder_rationale": "BERT-base-uncased"
+  }
 }