add all new configs

configs/evaluations/informer-btcusdt-15m-gmadl.yaml

@@ -1,4 +1,5 @@
 program: ./scripts/train.py
+name: informer-btcusdt-15m-gmadl-eval
 project: wne-masters-thesis-testing
 command:
   - ${env}

configs/evaluations/informer-btcusdt-15m-quantile.yaml

@@ -1,4 +1,5 @@
 program: ./scripts/train.py
+name: informer-btcusdt-15m-quantile-eval
 project: wne-masters-thesis-testing
 command:
   - ${env}

configs/evaluations/informer-btcusdt-30m-gmadl.yaml

@@ -1,4 +1,5 @@
 program: ./scripts/train.py
+name: informer-btcusdt-30m-gmadl-eval
 project: wne-masters-thesis-testing
 command:
   - ${env}

configs/evaluations/informer-btcusdt-30m-quantile.yaml

@@ -1,4 +1,5 @@
 program: ./scripts/train.py
+name: informer-btcusdt-30m-quantile-eval
 project: wne-masters-thesis-testing
 command:
   - ${env}

configs/evaluations/informer-btcusdt-5m-gmadl.yaml

@@ -1,4 +1,5 @@
 program: ./scripts/train.py
+name: informer-btcusdt-5m-gmadl-eval
 project: wne-masters-thesis-testing
 command:
   - ${env}

configs/evaluations/informer-btcusdt-5m-quantile.yaml

@@ -1,4 +1,5 @@
 program: ./scripts/train.py
+name: informer-btcusdt-5m-quantile-eval
 project: wne-masters-thesis-testing
 command:
   - ${env}

configs/experiments/informer-btcusdt-30m-gmadl.yaml

@@ -0,0 +1,70 @@
+future_window:
+  value: 2
+past_window:
+  value: 28
+batch_size:
+  value: 256
+max_epochs:
+  value: 40
+data:
+  value:
+    dataset: "btc-usdt-30m:latest"
+    sliding_window: 0
+    validation: 0.2
+fields:
+  value:
+    time_index: "time_index"
+    target: "returns"
+    group_ids: ["group_id"]
+    dynamic_unknown_real:
+      - "high_price"
+      - "low_price"
+      - "open_price"
+      - "close_price"
+      - "volume"
+      - "open_to_close_price"
+      - "high_to_close_price"
+      - "low_to_close_price"
+      - "high_to_low_price"
+      - "returns"
+      - "log_returns"
+      - "vol_1h"
+      - "macd"
+      - "macd_signal"
+      - "rsi"
+      - "low_bband_to_close_price"
+      - "up_bband_to_close_price"
+      - "mid_bband_to_close_price"
+      - "sma_1h_to_close_price"
+      - "sma_1d_to_close_price"
+      - "sma_7d_to_close_price"
+      - "ema_1h_to_close_price"
+      - "ema_1d_to_close_price"
+    dynamic_unknown_cat: []
+    dynamic_known_real:
+      - "effective_rates"
+      - "vix_close_price"
+      - "fear_greed_index"
+      - "vol_1d"
+      - "vol_7d"
+    dynamic_known_cat:
+      - "hour"
+      - "weekday"
+    static_real: []
+    static_cat: []
+loss:
+  value:
+   name: "GMADL"
+   a: 1000
+   b: 2
+model:
+  value:
+    name: "Informer"
+    d_model: 256
+    d_fully_connected: 256
+    n_attention_heads: 2
+    dropout: 0.05
+    n_encoder_layers: 1
+    n_decoder_layers: 1
+    learning_rate: 0.0001
+    optimizer: "Adam"

configs/sweeps/informer-btcusdt-15m-quantile.yaml

@@ -0,0 +1,41 @@
+program: ./scripts/train.py
+name: informer-btcusdt-15m-quantile-sweep
+project: wne-masters-thesis-testing
+command:
+  - ${env}
+  - ${interpreter}
+  - ${program}
+  - "./configs/experiments/informer-btcusdt-15m-quantile.yaml"
+  - "--patience"
+  - "15"
+method: random
+metric:
+  goal: minimize
+  name: val_loss
+parameters:
+  past_window:
+    distribution: int_uniform
+    min: 20
+    max: 120
+  batch_size:
+    values: [64, 128, 256]
+  model:
+    parameters:
+      name:
+        value: "Informer"
+      d_model:
+        values: [256, 512, 1024]
+      d_fully_connected:
+        values: [256, 512, 1024]
+      n_attention_heads:
+        values: [1, 2, 4, 6]
+      dropout:
+        values: [0.05, 0.1, 0.2, 0.3]
+      n_encoder_layers:
+        values: [1, 2, 3]
+      n_decoder_layers: 
+        values: [1, 2, 3]
+      learning_rate:
+        values: [0.001, 0.0005, 0.0001]
+      optimizer:
+        value: "Adam"

configs/sweeps/informer-btcusdt-30m-gmadl.yaml

@@ -0,0 +1,41 @@
+program: ./scripts/train.py
+name: informer-btcusdt-30m-gmadl-sweep
+project: wne-masters-thesis-testing
+command:
+  - ${env}
+  - ${interpreter}
+  - ${program}
+  - "./configs/experiments/informer-btcusdt-30m-gmadl.yaml"
+  - "--patience"
+  - "15"
+method: random
+metric:
+  goal: minimize
+  name: val_loss
+parameters:
+  past_window:
+    distribution: int_uniform
+    min: 20
+    max: 120
+  batch_size:
+    values: [64, 128, 256]
+  model:
+    parameters:
+      name:
+        value: "Informer"
+      d_model:
+        values: [256, 512, 1024]
+      d_fully_connected:
+        values: [256, 512, 1024]
+      n_attention_heads:
+        values: [1, 2, 4, 6]
+      dropout:
+        values: [0.05, 0.1, 0.2, 0.3]
+      n_encoder_layers:
+        values: [1, 2, 3]
+      n_decoder_layers: 
+        values: [1, 2, 3]
+      learning_rate:
+        values: [0.001, 0.0005, 0.0001]
+      optimizer:
+        value: "Adam"

configs/sweeps/informer-btcusdt-30m-quantile.yaml

@@ -0,0 +1,41 @@
+program: ./scripts/train.py
+name: informer-btcusdt-30m-quantile-sweep
+project: wne-masters-thesis-testing
+command:
+  - ${env}
+  - ${interpreter}
+  - ${program}
+  - "./configs/experiments/informer-btcusdt-30m-quantile.yaml"
+  - "--patience"
+  - "15"
+method: random
+metric:
+  goal: minimize
+  name: val_loss
+parameters:
+  past_window:
+    distribution: int_uniform
+    min: 20
+    max: 120
+  batch_size:
+    values: [64, 128, 256]
+  model:
+    parameters:
+      name:
+        value: "Informer"
+      d_model:
+        values: [256, 512, 1024]
+      d_fully_connected:
+        values: [256, 512, 1024]
+      n_attention_heads:
+        values: [1, 2, 4, 6]
+      dropout:
+        values: [0.05, 0.1, 0.2, 0.3]
+      n_encoder_layers:
+        values: [1, 2, 3]
+      n_decoder_layers: 
+        values: [1, 2, 3]
+      learning_rate:
+        values: [0.001, 0.0005, 0.0001]
+      optimizer:
+        value: "Adam"

configs/sweeps/informer-btcusdt-5m-quantile.yaml

@@ -1,4 +1,5 @@
 program: ./scripts/train.py
+name: informer-btcusdt-5m-quantile-sweep
 project: wne-masters-thesis-testing
 command:
   - ${env}