model: graph_conv-dot_product_h128_l3_edge_prediction | (graph_conv-dot_product_h128_l3) | WandB: s6xbw29d

config.json

@@ -2,13 +2,14 @@
   "name": null,
   "seed": 42,
   "deterministic": true,
-  "output_dir": "relation_prediction_dotprod_128e_v1",
+  "output_dir": "edge_prediction_dotprod_128e_v4",
   "model": {
     "encoder": "graph_conv",
     "hidden_channels": 128,
     "num_layers": 3,
     "dropout": 0.2,
     "head": "dot_product",
+    "init_head_as_identity": false,
     "gat_heads": 4,
     "gat_concat": true,
     "graph_conv_aggregator": "mean",
@@ -52,13 +53,15 @@
     ],
     "edge_prediction_neg_sampling_ratio": 1.0,
     "edge_prediction_neg_sampling_stratify_by": "node_type",
-    "edge_prediction_neg_sampling_strategy": "degree_weighted"
+    "edge_prediction_neg_sampling_strategy": "degree_weighted",
+    "weight_loss_by_relation_frequency": false,
+    "loss_weight_alpha": 0.5
   },
   "training": {
-    "lr": 0.0008,
-    "weight_decay": 0.00003,
+    "lr": 0.003,
+    "weight_decay": 0.0001,
     "optimizer": "adamw",
-    "scheduler": null,
+    "scheduler": "plateau",
     "epochs": 500,
     "batches_per_epoch": 20,
     "accelerator": "auto",
@@ -67,21 +70,25 @@
     "early_stopping": true,
     "early_stopping_patience": 20,
     "early_stopping_metric": "val_auc",
-    "checkpoint_subdir": "checkpoints",
     "save_checkpoints": true,
-    "checkpoint_metric": "val_auc"
+    "checkpoint_subdir": "checkpoints",
+    "checkpoint_metric": "val_auc",
+    "score_distribution_monitoring": true,
+    "score_distribution_monitoring_log_every_n_epochs": 10,
+    "embedding_norm_monitoring": true,
+    "embedding_norm_monitoring_log_every_n_epochs": 10
   },
   "wandb": {
     "project": "napistu-experiments",
     "entity": "napistu",
     "group": "baseline",
     "tags": [
-      "relation_prediction",
+      "edge_prediction",
       "graph_conv",
       "edge_prediction",
       "hidden_128",
       "layers_3",
-      "lr_0.0008",
+      "lr_0.003",
       "epochs_500"
     ],
     "log_model": false,