initial commit with the pipeline for training and evaluating seisbench models

experiments/config.json

@@ -1,11 +0,0 @@
-{
-  "epochs": 10,
-  "batch_size": 256,
-  "dataset": "igf_1",
-  "sampling_rate": 100,
-  "model_names": "EQTransformer,BasicPhaseAE,GPD",
-  "model_name": "PhaseNet",
-  "learning_rate": 0.01,
-  "pretrained": null,
-  "sampling_rate": 100
-}

experiments/sweep_gpd.yaml

@@ -0,0 +1,26 @@
+name: GPD_fixed_highpass:2-10
+method: bayes
+metric:
+  goal: minimize
+  name: val_loss
+parameters:
+  model_name:
+    value:
+      - GPD
+  batch_size:
+    distribution: int_uniform
+    max: 1024
+    min: 256
+  max_epochs:
+    value:
+      - 3
+  learning_rate:
+    distribution: uniform
+    max: 0.02
+    min: 0.005
+  highpass:
+    value:
+      - 2
+  lowpass:
+    value:
+      - 10

experiments/sweep_gpd_highpass.yaml

@@ -0,0 +1,27 @@
+name: GPD_fixed_highpass:2-10
+method: bayes
+metric:
+  goal: minimize
+  name: val_loss
+parameters:
+  model_name:
+    value:
+      - GPD
+  batch_size:
+    distribution: int_uniform
+    max: 1024
+    min: 256
+  max_epochs:
+    value:
+      - 15
+  learning_rate:
+    distribution: uniform
+    max: 0.02
+    min: 0.005
+  highpass:
+    distribution: uniform
+    min: 0.5
+    max: 2.0
+  lowpass:
+    value:
+      - 10

experiments/sweep_phasenet.yaml

@@ -0,0 +1,20 @@
+name: PhaseNet-lr0.005-0.02-bs256-1024
+method: bayes
+metric:
+  goal: minimize
+  name: val_loss
+parameters:
+  model_name:
+    value:
+      - PhaseNet
+  batch_size:
+    distribution: int_uniform
+    max: 1024
+    min: 256
+  max_epochs:
+    value:
+      - 15
+  learning_rate:
+    distribution: uniform
+    max: 0.02
+    min: 0.005