best val_rmse 0.0663

config.json

@@ -1,5 +1,5 @@
 {
-  "best_val_loss": 0.06232593581080437,
+  "best_val_loss": 0.06627163290977478,
   "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/a4f4e9b4337044629420d2c9ea3cef91",
+  "experiment_dir": "/work/ojedamarin/Projects/Pharma/Results/comet/node_pk_compartments/23a80a8f063947ee86e7e2c2248ef543",
   "experiment_indentifier": null,
   "experiment_name": "node_pk_compartments",
   "hf_model_card_path": [
@@ -167,7 +167,7 @@
   "network": {
     "activation": "ReLU",
     "aggregator_num_heads": 8,
-    "aggregator_type": "attention",
+    "aggregator_type": "mean",
     "cov_proj_dim": 16,
     "decoder_attention_layers": 2,
     "decoder_hidden_dim": 512,
@@ -181,7 +181,7 @@
     "exclusive_node_step": true,
     "individual_encoder_name": "RNNContextEncoder",
     "individual_encoder_number_of_heads": 4,
-    "init_hidden_num_layers": 2,
+    "init_hidden_num_layers": 4,
     "input_encoding_hidden_dim": 128,
     "loss_name": "nll",
     "node_step": true,
@@ -197,7 +197,7 @@
     "use_kl_s": true,
     "zi_latent_dim": 256
   },
-  "run_index": 1,
+  "run_index": 4,
   "tags": [
     "NP",
     "OU",

pytorch_model.bin

@@ -1,3 +1,3 @@
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-size 38747354
+oid sha256:f54718f2c775ccc0bc311965f610569f4264e2af61ed3ad621c317efcfe9b592
+size 37691910