best val_rmse 0.4433

config.json

@@ -1,5 +1,5 @@
 {
-  "best_val_loss": 0.3677442669868469,
+  "best_val_loss": 0.4433233141899109,
   "comet_ai_key": null,
   "context_observations": {
     "add_rem": true,
@@ -17,7 +17,7 @@
     "route": "oral",
     "time": 0.0
   },
-  "experiment_dir": "/home/cesarali/Pharma/generative_pk/results/comet/node_pk_compartments/73cdc2b3d72b4436b85336710cbacdc9",
+  "experiment_dir": "/home/cesarali/Pharma/generative_pk/results/comet/node_pk_compartments/803452f598674599b78ffdb2865cca81",
   "experiment_indentifier": null,
   "experiment_name": "node_pk_compartments",
   "hf_model_card_path": [
@@ -31,6 +31,10 @@
       0.01,
       0.1
     ],
+    "V_tscl_range": [
+      1.0,
+      5.0
+    ],
     "drug_id_options": [
       "Drug_A",
       "Drug_B",
@@ -40,18 +44,34 @@
       0.01,
       0.1
     ],
+    "k_1p_tscl_range": [
+      1.0,
+      5.0
+    ],
     "k_a_tmag_range": [
       0.01,
       0.1
     ],
+    "k_a_tscl_range": [
+      1.0,
+      5.0
+    ],
     "k_e_tmag_range": [
       0.01,
       0.1
     ],
+    "k_e_tscl_range": [
+      1.0,
+      5.0
+    ],
     "k_p1_tmag_range": [
       0.01,
       0.1
     ],
+    "k_p1_tscl_range": [
+      1.0,
+      5.0
+    ],
     "log_V_mean_range": [
       -1.5,
       1.5
@@ -100,6 +120,10 @@
       1,
       3
     ],
+    "rel_ruv_range": [
+      0.05,
+      0.3
+    ],
     "solver_method": "rk4",
     "time_num_steps": 100,
     "time_start": 0.0,
@@ -198,6 +222,7 @@
     "num_batch_plot": 1,
     "num_workers": 3,
     "optimizer_name": "AdamW",
+    "persistent_workers": true,
     "scheduler_name": "CosineAnnealingLR",
     "scheduler_params": {
       "T_max": 1000,

pytorch_model.bin

@@ -1,3 +1,3 @@
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+oid sha256:4e006a32e82f30e60858bea9620c0d332b9a08771924b326e2c395cd2f3ba8ce
 size 168701