best val_rmse -0.1630

config.json

@@ -1,5 +1,5 @@
 {
-  "best_val_loss": 0.007172345649451017,
+  "best_val_loss": -0.16302864253520966,
   "comet_ai_key": null,
   "context_observations": {
     "add_rem": true,
@@ -11,7 +11,7 @@
     "split_past_future": false,
     "type": "pk_peak_half_life"
   },
-  "debug_test": true,
+  "debug_test": false,
   "dosing": {
     "logdose_mean_range": [
       -2.0,
@@ -33,7 +33,7 @@
     "same_route": true,
     "time": 0.0
   },
-  "experiment_dir": "/home/cesarali/Pharma/sim_priors_pk/results/comet/aistats/d4a1f655681347bb8fc255a25bab7924",
+  "experiment_dir": "/work/ojedamarin/Projects/Pharma/Results/comet/aistats/942b32938bf745978a5af7fb4b3fdd9d",
   "experiment_indentifier": null,
   "experiment_name": "aistats",
   "experiment_type": "nodepk",
@@ -164,14 +164,14 @@
     "test_empirical_datasets": [
       "cesarali/Theophylline"
     ],
-    "test_size": 128,
+    "test_size": 64,
     "tqdm_progress": false,
-    "train_size": 1280,
-    "val_size": 128,
+    "train_size": 128,
+    "val_size": 64,
     "z_score_normalization": false
   },
   "model_type": "node_pk",
-  "my_results_path": null,
+  "my_results_path": "/work/ojedamarin/Projects/Pharma/Results/",
   "name_str": "AICMEPK",
   "network": {
     "activation": "ReLU",
@@ -237,25 +237,24 @@
       "val_rmse": {
         "epoch": null,
         "step": null,
-        "value": 0.007172345649451017
+        "value": -0.16302864253520966
       }
     },
     "meta": {}
   },
   "train": {
     "amsgrad": false,
-    "batch_size": 64,
+    "batch_size": 128,
     "betas": [
       0.9,
       0.999
     ],
-    "empirical_every_pct": 0.2,
-    "epochs": 100,
+    "empirical_every_pct": 0.1,
+    "epochs": 10,
     "eps": 1e-08,
     "generative_image_ids": null,
     "generative_image_ids_empirical_during": null,
     "generative_image_ids_empirical_end": [
-      "new_individuals_images",
       "vpc_images_per_batch"
     ],
     "generative_image_ids_val": [
@@ -281,10 +280,10 @@
     "log_predictive_val": true,
     "models_end_of_training": [
       "last",
-      "best"
+      "best-summary"
     ],
     "num_batch_plot": 1,
-    "num_workers": 4,
+    "num_workers": 8,
     "optimizer_name": "AdamW",
     "persistent_workers": true,
     "predictive_image_ids": null,
@@ -309,8 +308,14 @@
       "eta_min": 5e-05,
       "last_epoch": -1
     },
+    "selected_summary_drugs": [],
+    "selected_summary_metric": null,
     "shuffle_val": true,
-    "val_every_pct": 0.5,
+    "summary_metric_checkpoint_dir": null,
+    "summary_metric_checkpoint_filename": "best-summary.ckpt",
+    "summary_metric_mode": "min",
+    "summary_metric_name": "rmse",
+    "val_every_pct": 0.1,
     "weight_decay": 0.0001
   },
   "transformers_version": "4.52.4",

pytorch_model.bin

@@ -1,3 +1,3 @@
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+oid sha256:bb4bb92418e550190669cffea2ea2159b1cc3e251e55ff11aeff2fbaa94a6841
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