best val_rmse 0.1490

config.json

@@ -1,5 +1,5 @@
 {
-  "best_val_loss": 0.2538306415081024,
+  "best_val_loss": 0.14899936318397522,
   "comet_ai_key": null,
   "context_observations": {
     "add_rem": false,
@@ -33,7 +33,7 @@
     "same_route": true,
     "time": 0.0
   },
-  "experiment_dir": "/work/ojedamarin/Projects/Pharma/Results/comet/functional-flow-pk/39f07b30bb024f0caf01e23e9876e0f8",
+  "experiment_dir": "/home/ojedamarin/Projects/Pharma/Results/comet/functional-flow-pk/4c1fdf6439144ea8b4590604eff468f5",
   "experiment_indentifier": null,
   "experiment_name": "functional-flow-pk",
   "experiment_type": "flowpk",
@@ -47,7 +47,7 @@
   "meta_study": {
     "V_tmag_range": [
       0.001,
-      0.01
+      0.001
     ],
     "V_tscl_range": [
       1,
@@ -60,7 +60,7 @@
     ],
     "k_1p_tmag_range": [
       0.01,
-      0.1
+      0.02
     ],
     "k_1p_tscl_range": [
       1,
@@ -68,7 +68,7 @@
     ],
     "k_a_tmag_range": [
       0.01,
-      0.1
+      0.02
     ],
     "k_a_tscl_range": [
       1,
@@ -76,7 +76,7 @@
     ],
     "k_e_tmag_range": [
       0.01,
-      0.1
+      0.02
     ],
     "k_e_tscl_range": [
       1,
@@ -84,51 +84,51 @@
     ],
     "k_p1_tmag_range": [
       0.01,
-      0.1
+      0.02
     ],
     "k_p1_tscl_range": [
       1,
       5
     ],
     "log_V_mean_range": [
-      1,
-      7
+      2,
+      8
     ],
     "log_V_std_range": [
-      0.15,
-      0.45
+      0.2,
+      0.6
     ],
     "log_k_1p_mean_range": [
       -4,
       0
     ],
     "log_k_1p_std_range": [
-      0.15,
-      0.45
+      0.2,
+      0.6
     ],
     "log_k_a_mean_range": [
       -1,
       2
     ],
     "log_k_a_std_range": [
-      0.15,
-      0.45
+      0.2,
+      0.6
     ],
     "log_k_e_mean_range": [
       -5,
       0
     ],
     "log_k_e_std_range": [
-      0.15,
-      0.45
+      0.2,
+      0.6
     ],
     "log_k_p1_mean_range": [
       -4,
       -1
     ],
     "log_k_p1_std_range": [
-      0.15,
-      0.45
+      0.2,
+      0.6
     ],
     "num_individuals_range": [
       5,
@@ -139,8 +139,8 @@
       3
     ],
     "rel_ruv_range": [
-      0.01,
-      0.1
+      0.001,
+      0.01
     ],
     "solver_method": "rk4",
     "time_num_steps": 100,
@@ -148,7 +148,7 @@
     "time_stop": 16.0
   },
   "mix_data": {
-    "evaluate_prediction_steps_past": 0,
+    "evaluate_prediction_steps_past": 5,
     "keep_tempfile": false,
     "log_transform": false,
     "n_of_databatches": null,
@@ -157,44 +157,47 @@
     "normalize_by_max": true,
     "normalize_time": true,
     "recreate_tempfile": false,
-    "sample_size_for_generative_evaluation": 50,
+    "sample_size_for_generative_evaluation": null,
+    "sample_size_for_generative_evaluation_end_of_training": 500,
+    "sample_size_for_generative_evaluation_val": 10,
     "store_in_tempfile": false,
     "tempfile_path": [
       "preprocessed",
       "simulated_ou_as_rates"
     ],
     "test_empirical_datasets": [
-      "cesarali/Indometacin"
+      "cesarali/lenuzza-2016",
+      "cesarali/Indometacin",
+      "cesarali/Theophylline"
     ],
     "test_size": 64,
     "tqdm_progress": false,
-    "train_size": 256,
-    "val_size": 64,
+    "train_size": 12800,
+    "val_size": 256,
     "z_score_normalization": false
   },
   "model_type": "node_pk",
-  "my_results_path": "/work/ojedamarin/Projects/Pharma/Results/",
+  "my_results_path": "/home/ojedamarin/Projects/Pharma/Results/",
   "name_str": "FlowPK",
-  "run_index": 1,
+  "run_index": 0,
   "source_process": {
-    "flow_sigma": 1e-05,
-    "gp_eps": 1e-07,
-    "gp_length_scale": 0.1,
-    "gp_transform": "softplus",
-    "gp_variance": 0.05,
+    "flow_sigma": 0.0001,
+    "gp_eps": 0.001,
+    "gp_length_scale": 0.01,
+    "gp_transform": "none",
+    "gp_variance": 0.01,
     "source_type": "gaussian_process",
     "use_OT_coupling": false
   },
   "tags": [
     "UAI",
-    "FlowPK-Grid",
-    "FLOWPK"
+    "FlowPK"
   ],
   "target_observations": {
     "add_rem": true,
     "empirical_number_of_obs": 2,
     "max_num_obs": 10,
-    "max_past": 0,
+    "max_past": 5,
     "min_past": 0,
     "past_time_ratio": 0.3,
     "split_past_future": true,
@@ -205,7 +208,7 @@
       "val_rmse": {
         "epoch": null,
         "step": null,
-        "value": 0.2538306415081024
+        "value": 0.14899936318397522
       }
     },
     "meta": {}
@@ -217,8 +220,8 @@
       0.9,
       0.999
     ],
-    "empirical_every_pct": 0.5,
-    "epochs": 30,
+    "empirical_every_pct": 0.1,
+    "epochs": 300,
     "eps": 1e-08,
     "generative_image_ids": null,
     "generative_image_ids_empirical_during": null,
@@ -229,25 +232,23 @@
       "new_individuals_images"
     ],
     "generative_metric_ids": null,
-    "generative_metric_ids_empirical_during": [
-      "vpc_npde_pvalues"
-    ],
+    "generative_metric_ids_empirical_during": null,
     "generative_metric_ids_empirical_end": [
       "vpc_npde_pvalues"
     ],
     "generative_metric_ids_val": [],
     "gradient_clip_val": 0.5,
-    "learning_rate": 0.0001,
+    "learning_rate": 0.001,
     "log_generative_empirical_during": true,
     "log_generative_empirical_end": true,
-    "log_generative_val": false,
-    "log_images_empirical_during": false,
+    "log_generative_val": true,
+    "log_images_empirical_during": true,
     "log_images_empirical_end": true,
-    "log_images_val": false,
+    "log_images_val": true,
     "log_interval": 1,
-    "log_predictive_empirical_during": false,
+    "log_predictive_empirical_during": true,
     "log_predictive_empirical_end": true,
-    "log_predictive_val": false,
+    "log_predictive_val": true,
     "models_end_of_training": [
       "last",
       "best-summary"
@@ -258,28 +259,37 @@
     "persistent_workers": true,
     "predictive_image_ids": null,
     "predictive_image_ids_empirical_during": null,
-    "predictive_image_ids_empirical_end": [],
-    "predictive_image_ids_val": [],
+    "predictive_image_ids_empirical_end": [
+      "prediction_images"
+    ],
+    "predictive_image_ids_val": [
+      "prediction_images"
+    ],
     "predictive_metric_ids": null,
-    "predictive_metric_ids_empirical_during": null,
-    "predictive_metric_ids_empirical_end": [],
+    "predictive_metric_ids_empirical_during": [
+      "prediction_metrics"
+    ],
+    "predictive_metric_ids_empirical_end": [
+      "prediction_metrics"
+    ],
     "predictive_metric_ids_val": [],
     "scheduler_name": "CosineAnnealingLR",
     "scheduler_params": {
-      "T_max": 1000,
-      "eta_min": 5e-05,
+      "T_max": 100,
+      "eta_min": 0.0001,
       "last_epoch": -1
     },
     "selected_summary_drugs": [
-      "Indometacin"
+      "paracetamol glucuronide",
+      "midazolam"
     ],
-    "selected_summary_metric": "npde_pvalue_mean",
+    "selected_summary_metric": "log_rmse",
     "shuffle_val": true,
     "summary_metric_checkpoint_dir": null,
     "summary_metric_checkpoint_filename": "best-summary.ckpt",
-    "summary_metric_mode": "max",
-    "summary_metric_name": "npde_pvalue_mean",
-    "val_every_pct": 0.5,
+    "summary_metric_mode": "min",
+    "summary_metric_name": "log_rmse",
+    "val_every_pct": 0.1,
     "weight_decay": 0.0001
   },
   "transformers_version": "4.52.4",
@@ -287,14 +297,14 @@
   "vector_field": {
     "combine_latent_mode": "mlp",
     "cov_proj_dim": 16,
-    "decoder_attention_layers": 8,
+    "decoder_attention_layers": 4,
     "decoder_num_heads": 4,
-    "dropout": 0.2,
-    "encoder_attention_layers": 8,
+    "dropout": 0.1,
+    "encoder_attention_layers": 4,
     "encoder_num_heads": 4,
-    "fourier_modes": 20,
-    "hidden_dim": 128,
-    "time_fourier_max_freq": 128,
+    "fourier_modes": 64,
+    "hidden_dim": 256,
+    "time_fourier_max_freq": 256,
     "use_spectral_qkv": false,
     "zi_latent_dim": 200
   },

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:cbdcfbb3952e6e90406cbe93e0aaf5f497290b8b4875abc92285465c4e145e88
-size 20016967
+oid sha256:6b4eea360ed008e2946e1ee1dcba445d5d05c141ecce07cbff243dba91f51fc0
+size 40022839