best val_rmse 0.0973

config.json

@@ -1,5 +1,5 @@
 {
-  "best_val_loss": 0.2079005241394043,
+  "best_val_loss": 0.09732607007026672,
   "comet_ai_key": null,
   "context_observations": {
     "add_rem": true,
@@ -34,7 +34,7 @@
     "same_route": true,
     "time": 0.0
   },
-  "experiment_dir": "/home/cesarali/Pharma/generative_pk/results/comet/node_pk_compartments/3f60f5793e364be7a8cad341b59e40a8",
+  "experiment_dir": "/home/cesarali/Pharma/generative_pk/results/comet/node_pk_compartments/25090ec430a14b26ba2171f866e18670",
   "experiment_indentifier": null,
   "experiment_name": "node_pk_compartments",
   "hf_model_card_path": [
@@ -189,7 +189,7 @@
     "cov_proj_dim": 16,
     "decoder_attention_layers": 2,
     "decoder_hidden_dim": 512,
-    "decoder_name": "RNNDecoder",
+    "decoder_name": "TransformerDecoder",
     "decoder_num_layers": 4,
     "decoder_rnn_hidden_dim": 256,
     "drift_activation": "Tanh",
@@ -205,11 +205,11 @@
     "node_step": true,
     "norm": "layer",
     "output_head_num_layers": 3,
-    "prediction_latent_deterministic": false,
+    "prediction_latent_deterministic": true,
     "prediction_only": false,
     "rnn_decoder_number_of_layers": 4,
     "rnn_individual_encoder_number_of_layers": 4,
-    "study_latent_deterministic": false,
+    "study_latent_deterministic": true,
     "time_obs_encoder_hidden_dim": 256,
     "time_obs_encoder_output_dim": 256,
     "use_attention": true,
@@ -244,7 +244,7 @@
       0.9,
       0.999
     ],
-    "epochs": 5,
+    "epochs": 3,
     "eps": 1e-08,
     "eval_empirical_every_pct": 0.5,
     "gradient_clip_val": 1.0,

pytorch_model.bin

@@ -1,3 +1,3 @@
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-size 29034507
+oid sha256:810a4f37a3ae7caaa09393ca47b2a84f63e8fa586c88d4c47f0213331d77ae6f
+size 38753907