best val_rmse 0.1585

config.json

@@ -1,5 +1,5 @@
 {
-  "best_val_loss": 0.1920255869626999,
+  "best_val_loss": 0.15854664146900177,
   "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/11ea6ff2323e4cf7b9583a578457dfcb",
+  "experiment_dir": "/work/ojedamarin/Projects/Pharma/Results/comet/node_pk_compartments/d6e4e97ca5f64de09823a2f75281d781",
   "experiment_indentifier": null,
   "experiment_name": "node_pk_compartments",
   "hf_model_card_path": [
@@ -132,7 +132,7 @@
   },
   "mix_data": {
     "evaluate_prediction_steps_past": 5,
-    "keep_tempfile": true,
+    "keep_tempfile": false,
     "log_transform": false,
     "n_of_databatches": 3,
     "n_of_target_individuals": 1,
@@ -145,7 +145,7 @@
     ],
     "pretraining_epochs": 8,
     "pretraining_protocol": "none",
-    "recreate_tempfile": false,
+    "recreate_tempfile": true,
     "return_split_versions": true,
     "split_seed": 42,
     "split_strategy": "study",
@@ -167,7 +167,7 @@
   "network": {
     "activation": "ReLU",
     "aggregator_num_heads": 8,
-    "aggregator_type": "mean",
+    "aggregator_type": "attention",
     "cov_proj_dim": 16,
     "decoder_attention_layers": 2,
     "decoder_hidden_dim": 512,
@@ -195,7 +195,7 @@
     "use_kl_i": true,
     "use_kl_init": true,
     "use_kl_s": true,
-    "zi_latent_dim": 100
+    "zi_latent_dim": 256
   },
   "run_index": 1,
   "tags": [

pytorch_model.bin

@@ -1,3 +1,3 @@
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-size 35650566
+oid sha256:f07fceac4ade363454df306b81bcf82e88b584bd01fc260361290a7a3dbc9e27
+size 38747354