add experiments with RMSE

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

@@ -0,0 +1,25 @@
+program: ./scripts/train.py
+name: informer-btcusdt-15m-rmse-eval
+project: wne-masters-thesis-testing
+command:
+  - ${env}
+  - ${interpreter}
+  - ${program}
+  - "./configs/experiments/informer-btcusdt-15m-rmse.yaml"
+  - "--patience"
+  - "20"
+  - "--store-predictions"
+method: grid
+metric:
+  goal: minimize
+  name: val_loss
+parameters:
+  data:
+    parameters:
+      dataset: 
+        value: "btc-usdt-15m:latest"
+      validation:
+        value: 0.2
+      sliding_window:
+        min: 0
+        max: 5

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

@@ -0,0 +1,27 @@
+program: ./scripts/train.py
+name: informer-btcusdt-30m-rmse-eval
+project: wne-masters-thesis-testing
+command:
+  - ${env}
+  - ${interpreter}
+  - ${program}
+  - "./configs/experiments/informer-btcusdt-30m-rmse.yaml"
+  - "--patience"
+  - "20"
+  - "--store-predictions"
+  - "--val-check-interval"
+  - "100"
+method: grid
+metric:
+  goal: minimize
+  name: val_loss
+parameters:
+  data:
+    parameters:
+      dataset: 
+        value: "btc-usdt-30m:latest"
+      validation:
+        value: 0.2
+      sliding_window:
+        min: 0
+        max: 5

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

@@ -0,0 +1,25 @@
+program: ./scripts/train.py
+name: informer-btcusdt-5m-rmse-eval
+project: wne-masters-thesis-testing
+command:
+  - ${env}
+  - ${interpreter}
+  - ${program}
+  - "./configs/experiments/informer-btcusdt-5m-rmse.yaml"
+  - "--patience"
+  - "20"
+  - "--store-predictions"
+method: grid
+metric:
+  goal: minimize
+  name: val_loss
+parameters:
+  data:
+    parameters:
+      dataset: 
+        value: "btc-usdt-5m:latest"
+      validation:
+        value: 0.2
+      sliding_window:
+        min: 0
+        max: 5

configs/experiments/informer-btcusdt-15m-rmse.yaml

@@ -0,0 +1,68 @@
+future_window:
+  value: 2
+past_window:
+  value: 110
+batch_size:
+  value: 64
+max_epochs:
+  value: 30
+data:
+  value:
+    dataset: "btc-usdt-15m: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: "RMSE"
+model:
+  value:
+    name: "Informer"
+    d_model: 512
+    d_fully_connected: 256
+    n_attention_heads: 4
+    dropout: 0.1
+    n_encoder_layers: 3
+    n_decoder_layers: 2
+    learning_rate: 0.0005
+    optimizer: "Adam"

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

@@ -0,0 +1,68 @@
+future_window:
+  value: 2
+past_window:
+  value: 115
+batch_size:
+  value: 64
+max_epochs:
+  value: 50
+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: "RMSE"
+model:
+  value:
+    name: "Informer"
+    d_model: 256
+    d_fully_connected: 512
+    n_attention_heads: 2
+    dropout: 0.2
+    n_encoder_layers: 2
+    n_decoder_layers: 2
+    learning_rate: 0.0005
+    optimizer: "Adam"

configs/experiments/informer-btcusdt-5m-rmse.yaml

@@ -0,0 +1,68 @@
+future_window:
+  value: 2
+past_window:
+  value: 102
+batch_size:
+  value: 64
+max_epochs:
+  value: 30
+data:
+  value:
+    dataset: "btc-usdt-5m: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: "RMSE"
+model:
+  value:
+    name: "Informer"
+    d_model: 512
+    d_fully_connected: 512
+    n_attention_heads: 4
+    dropout: 0.3
+    n_encoder_layers: 2
+    n_decoder_layers: 3
+    learning_rate: 0.0005
+    optimizer: "Adam"

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

@@ -0,0 +1,41 @@
+program: ./scripts/train.py
+name: informer-btcusdt-15m-rmse-sweep
+project: wne-masters-thesis-testing
+command:
+  - ${env}
+  - ${interpreter}
+  - ${program}
+  - "./configs/experiments/informer-btcusdt-15m-rmse.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]
+      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-rmse.yaml

@@ -0,0 +1,43 @@
+program: ./scripts/train.py
+name: informer-btcusdt-30m-rmse-sweep
+project: wne-masters-thesis-testing
+command:
+  - ${env}
+  - ${interpreter}
+  - ${program}
+  - "./configs/experiments/informer-btcusdt-30m-rmse.yaml"
+  - "--patience"
+  - "15"
+  - "--val-check-interval"
+  - "100"
+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]
+      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-rmse.yaml

@@ -0,0 +1,41 @@
+program: ./scripts/train.py
+name: informer-btcusdt-5m-rmse-sweep
+project: wne-masters-thesis-testing
+command:
+  - ${env}
+  - ${interpreter}
+  - ${program}
+  - "./configs/experiments/informer-btcusdt-5m-rmse.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]
+      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"

src/ml/loss.py

@@ -1,6 +1,6 @@
 import torch
 
-from pytorch_forecasting import QuantileLoss
+from pytorch_forecasting import QuantileLoss, RMSE
 from pytorch_forecasting.metrics.base_metrics import MultiHorizonMetric
 
 
@@ -15,6 +15,9 @@ def get_loss(config):
             a=config['loss']['a'],
             b=config['loss']['b']
         )
+    
+    if loss_name == 'RMSE':
+        return RMSE()
 
     raise ValueError("Unknown loss")