best val_rmse 104.9450

config.json

@@ -1,5 +1,5 @@
 {
-  "best_val_loss": 1.4664826393127441,
+  "best_val_loss": 104.94497680664062,
   "comet_ai_key": null,
   "context_observations": {
     "add_rem": true,
@@ -8,7 +8,7 @@
     "min_past": 3,
     "obs_dataset": "/home/ojedamarin/Projects/Pharma/generative_pk/data/preprocessed/lenuzza/Lenuzza2016.csv",
     "past_time_ratio": 0.1,
-    "split_past_future": false,
+    "split_past_future": true,
     "type": "pk_peak_half_life"
   },
   "debug_test": true,
@@ -33,7 +33,7 @@
     "same_route": true,
     "time": 0.0
   },
-  "experiment_dir": "/home/cesarali/Pharma/sim_priors_pk/results/comet/node-pk/8f897dad6cc0477793b8dedad97fb59a",
+  "experiment_dir": "/home/cesarali/Pharma/sim_priors_pk/results/comet/node-pk/86c08b8325714466917ceedd23db30c8",
   "experiment_indentifier": null,
   "experiment_name": "node-pk",
   "hf_model_card_path": [
@@ -174,12 +174,12 @@
       0.9,
       0.999
     ],
-    "epochs": 50,
+    "epochs": 20,
     "eps": 1e-08,
     "eval_empirical_every_pct": 2.0,
     "gradient_clip_val": 1.0,
     "learning_rate": 0.0001,
-    "log_image_every_epoch": 10,
+    "log_image_every_epoch": 2,
     "log_interval": 1,
     "log_vcp": false,
     "num_batch_plot": 1,

pytorch_model.bin

@@ -1,3 +1,3 @@
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+oid sha256:9f61bf1dc3d23490b18b02a617de3566c7cb8a9fe5c8fccbf088faf19840d16b
 size 39270535