best val_rmse 0.0420

config.json

@@ -1,5 +1,5 @@
 {
-  "best_val_loss": 0.041567400097846985,
+  "best_val_loss": 0.04201662167906761,
   "comet_ai_key": null,
   "context_observations": {
     "add_rem": true,
@@ -18,7 +18,7 @@
     "route": "oral",
     "time": 0.0
   },
-  "experiment_dir": "/work/ojedamarin/Projects/Pharma/Results/comet/node_pk_compartments/e48dc87ce52a47858f242c7749f54dbd",
+  "experiment_dir": "/work/ojedamarin/Projects/Pharma/Results/comet/node_pk_compartments/43b5890e30124cc9b31f40fd167842f5",
   "experiment_indentifier": null,
   "experiment_name": "node_pk_compartments",
   "hf_model_card_path": [
@@ -145,7 +145,7 @@
     ],
     "pretraining_epochs": 2000,
     "pretraining_protocol": "none",
-    "recreate_tempfile": false,
+    "recreate_tempfile": true,
     "return_split_versions": false,
     "split_seed": 42,
     "split_strategy": "study",
@@ -194,7 +194,9 @@
     "time_obs_encoder_hidden_dim": 256,
     "time_obs_encoder_output_dim": 256,
     "use_attention": true,
+    "use_invariance_loss": true,
     "use_kl_i": true,
+    "use_kl_i_np": true,
     "use_kl_init": true,
     "use_kl_s": true,
     "zi_latent_dim": 512
@@ -226,12 +228,12 @@
     "eps": 1e-08,
     "eval_empirical_every_pct": 0.25,
     "gradient_clip_val": 1.0,
-    "learning_rate": 0.0001,
-    "log_image_every_epoch": 25,
+    "learning_rate": 0.00023,
+    "log_image_every_epoch": 2,
     "log_interval": 1,
     "log_vcp": true,
     "num_batch_plot": 1,
-    "num_workers": 8,
+    "num_workers": 3,
     "optimizer_name": "AdamW",
     "persistent_workers": true,
     "scheduler_name": "CosineAnnealingLR",

pytorch_model.bin

@@ -1,3 +1,3 @@
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+oid sha256:9992b5872763e9cd24943bcd266c9132bf4bf0ef2f56d1a820b37c7630747722
 size 40834196