best val_rmse 0.2538

config.json

@@ -1,5 +1,5 @@
 {
-  "best_val_loss": 0.29546692967414856,
+  "best_val_loss": 0.2538306415081024,
   "comet_ai_key": null,
   "context_observations": {
     "add_rem": false,
@@ -33,7 +33,7 @@
     "same_route": true,
     "time": 0.0
   },
-  "experiment_dir": "/work/ojedamarin/Projects/Pharma/Results/comet/functional-flow-pk/476c26a019bb464399fd6ed3289cb9d0",
+  "experiment_dir": "/work/ojedamarin/Projects/Pharma/Results/comet/functional-flow-pk/39f07b30bb024f0caf01e23e9876e0f8",
   "experiment_indentifier": null,
   "experiment_name": "functional-flow-pk",
   "experiment_type": "flowpk",
@@ -47,7 +47,7 @@
   "meta_study": {
     "V_tmag_range": [
       0.001,
-      0.001
+      0.01
     ],
     "V_tscl_range": [
       1,
@@ -60,7 +60,7 @@
     ],
     "k_1p_tmag_range": [
       0.01,
-      0.02
+      0.1
     ],
     "k_1p_tscl_range": [
       1,
@@ -68,7 +68,7 @@
     ],
     "k_a_tmag_range": [
       0.01,
-      0.02
+      0.1
     ],
     "k_a_tscl_range": [
       1,
@@ -76,7 +76,7 @@
     ],
     "k_e_tmag_range": [
       0.01,
-      0.02
+      0.1
     ],
     "k_e_tscl_range": [
       1,
@@ -84,51 +84,51 @@
     ],
     "k_p1_tmag_range": [
       0.01,
-      0.02
+      0.1
     ],
     "k_p1_tscl_range": [
       1,
       5
     ],
     "log_V_mean_range": [
-      2,
-      8
+      1,
+      7
     ],
     "log_V_std_range": [
-      0.2,
-      0.6
+      0.15,
+      0.45
     ],
     "log_k_1p_mean_range": [
       -4,
       0
     ],
     "log_k_1p_std_range": [
-      0.2,
-      0.6
+      0.15,
+      0.45
     ],
     "log_k_a_mean_range": [
       -1,
       2
     ],
     "log_k_a_std_range": [
-      0.2,
-      0.6
+      0.15,
+      0.45
     ],
     "log_k_e_mean_range": [
       -5,
       0
     ],
     "log_k_e_std_range": [
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-      0.6
+      0.15,
+      0.45
     ],
     "log_k_p1_mean_range": [
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       -1
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     "log_k_p1_std_range": [
-      0.2,
-      0.6
+      0.15,
+      0.45
     ],
     "num_individuals_range": [
       5,
@@ -139,8 +139,8 @@
       3
     ],
     "rel_ruv_range": [
-      0.001,
-      0.01
+      0.01,
+      0.1
     ],
     "solver_method": "rk4",
     "time_num_steps": 100,
@@ -175,7 +175,7 @@
   "model_type": "node_pk",
   "my_results_path": "/work/ojedamarin/Projects/Pharma/Results/",
   "name_str": "FlowPK",
-  "run_index": 0,
+  "run_index": 1,
   "source_process": {
     "flow_sigma": 1e-05,
     "gp_eps": 1e-07,
@@ -205,7 +205,7 @@
       "val_rmse": {
         "epoch": null,
         "step": null,
-        "value": 0.29546692967414856
+        "value": 0.2538306415081024
       }
     },
     "meta": {}

pytorch_model.bin

@@ -1,3 +1,3 @@
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+oid sha256:cbdcfbb3952e6e90406cbe93e0aaf5f497290b8b4875abc92285465c4e145e88
 size 20016967