add experiments with RMSE
This commit is contained in:
Filip Stefaniuk
parent
6360d76d11
commit
96950fcf90
25
configs/evaluations/informer-btcusdt-15m-rmse.yaml
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25
configs/evaluations/informer-btcusdt-15m-rmse.yaml
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@ -0,0 +1,25 @@
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program: ./scripts/train.py
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name: informer-btcusdt-15m-rmse-eval
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project: wne-masters-thesis-testing
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command:
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- ${env}
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- ${interpreter}
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- ${program}
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- "./configs/experiments/informer-btcusdt-15m-rmse.yaml"
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- "--patience"
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- "20"
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- "--store-predictions"
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method: grid
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metric:
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goal: minimize
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name: val_loss
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parameters:
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data:
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parameters:
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dataset:
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value: "btc-usdt-15m:latest"
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validation:
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value: 0.2
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sliding_window:
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min: 0
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max: 5
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27
configs/evaluations/informer-btcusdt-30m-rmse.yaml
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27
configs/evaluations/informer-btcusdt-30m-rmse.yaml
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@ -0,0 +1,27 @@
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program: ./scripts/train.py
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name: informer-btcusdt-30m-rmse-eval
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project: wne-masters-thesis-testing
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command:
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- ${env}
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- ${interpreter}
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- ${program}
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- "./configs/experiments/informer-btcusdt-30m-rmse.yaml"
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- "--patience"
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- "20"
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- "--store-predictions"
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- "--val-check-interval"
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- "100"
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method: grid
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metric:
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goal: minimize
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name: val_loss
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parameters:
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data:
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parameters:
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dataset:
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value: "btc-usdt-30m:latest"
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validation:
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value: 0.2
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sliding_window:
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min: 0
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max: 5
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25
configs/evaluations/informer-btcusdt-5m-rmse.yaml
Normal file
25
configs/evaluations/informer-btcusdt-5m-rmse.yaml
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@ -0,0 +1,25 @@
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program: ./scripts/train.py
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name: informer-btcusdt-5m-rmse-eval
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project: wne-masters-thesis-testing
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command:
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- ${env}
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- ${interpreter}
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- ${program}
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- "./configs/experiments/informer-btcusdt-5m-rmse.yaml"
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- "--patience"
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- "20"
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- "--store-predictions"
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method: grid
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metric:
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goal: minimize
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name: val_loss
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parameters:
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data:
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parameters:
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dataset:
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value: "btc-usdt-5m:latest"
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validation:
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value: 0.2
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sliding_window:
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min: 0
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max: 5
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68
configs/experiments/informer-btcusdt-15m-rmse.yaml
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68
configs/experiments/informer-btcusdt-15m-rmse.yaml
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@ -0,0 +1,68 @@
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future_window:
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value: 2
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past_window:
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value: 110
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batch_size:
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value: 64
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max_epochs:
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value: 30
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data:
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value:
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dataset: "btc-usdt-15m:latest"
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sliding_window: 0
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validation: 0.2
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fields:
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value:
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time_index: "time_index"
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target: "returns"
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group_ids: ["group_id"]
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dynamic_unknown_real:
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- "high_price"
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- "low_price"
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- "open_price"
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- "close_price"
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- "volume"
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- "open_to_close_price"
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- "high_to_close_price"
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- "low_to_close_price"
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- "high_to_low_price"
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- "returns"
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- "log_returns"
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- "vol_1h"
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- "macd"
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- "macd_signal"
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- "rsi"
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- "low_bband_to_close_price"
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- "up_bband_to_close_price"
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- "mid_bband_to_close_price"
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- "sma_1h_to_close_price"
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- "sma_1d_to_close_price"
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- "sma_7d_to_close_price"
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- "ema_1h_to_close_price"
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- "ema_1d_to_close_price"
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dynamic_unknown_cat: []
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dynamic_known_real:
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- "effective_rates"
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- "vix_close_price"
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- "fear_greed_index"
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- "vol_1d"
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- "vol_7d"
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dynamic_known_cat:
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- "hour"
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- "weekday"
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static_real: []
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static_cat: []
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loss:
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value:
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name: "RMSE"
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model:
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value:
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name: "Informer"
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d_model: 512
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d_fully_connected: 256
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n_attention_heads: 4
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dropout: 0.1
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n_encoder_layers: 3
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n_decoder_layers: 2
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learning_rate: 0.0005
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optimizer: "Adam"
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68
configs/experiments/informer-btcusdt-30m-rmse.yaml
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68
configs/experiments/informer-btcusdt-30m-rmse.yaml
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@ -0,0 +1,68 @@
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future_window:
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value: 2
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past_window:
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value: 115
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batch_size:
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value: 64
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max_epochs:
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value: 50
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data:
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value:
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dataset: "btc-usdt-30m:latest"
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sliding_window: 0
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validation: 0.2
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fields:
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value:
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time_index: "time_index"
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target: "returns"
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group_ids: ["group_id"]
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dynamic_unknown_real:
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- "high_price"
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- "low_price"
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- "open_price"
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- "close_price"
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- "volume"
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- "open_to_close_price"
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- "high_to_close_price"
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- "low_to_close_price"
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- "high_to_low_price"
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- "returns"
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- "log_returns"
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- "vol_1h"
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- "macd"
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- "macd_signal"
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- "rsi"
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- "low_bband_to_close_price"
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- "up_bband_to_close_price"
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- "mid_bband_to_close_price"
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- "sma_1h_to_close_price"
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- "sma_1d_to_close_price"
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- "sma_7d_to_close_price"
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- "ema_1h_to_close_price"
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- "ema_1d_to_close_price"
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dynamic_unknown_cat: []
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dynamic_known_real:
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- "effective_rates"
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- "vix_close_price"
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- "fear_greed_index"
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- "vol_1d"
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- "vol_7d"
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dynamic_known_cat:
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- "hour"
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- "weekday"
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static_real: []
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static_cat: []
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loss:
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value:
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name: "RMSE"
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model:
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value:
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name: "Informer"
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d_model: 256
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d_fully_connected: 512
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n_attention_heads: 2
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dropout: 0.2
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n_encoder_layers: 2
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n_decoder_layers: 2
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learning_rate: 0.0005
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optimizer: "Adam"
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68
configs/experiments/informer-btcusdt-5m-rmse.yaml
Normal file
68
configs/experiments/informer-btcusdt-5m-rmse.yaml
Normal file
@ -0,0 +1,68 @@
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future_window:
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value: 2
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past_window:
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value: 102
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batch_size:
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value: 64
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max_epochs:
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value: 30
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data:
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value:
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dataset: "btc-usdt-5m:latest"
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sliding_window: 0
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validation: 0.2
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fields:
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value:
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time_index: "time_index"
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target: "returns"
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group_ids: ["group_id"]
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dynamic_unknown_real:
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- "high_price"
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- "low_price"
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- "open_price"
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- "close_price"
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- "volume"
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- "open_to_close_price"
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- "high_to_close_price"
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- "low_to_close_price"
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- "high_to_low_price"
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- "returns"
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- "log_returns"
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- "vol_1h"
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- "macd"
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- "macd_signal"
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- "rsi"
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- "low_bband_to_close_price"
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- "up_bband_to_close_price"
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- "mid_bband_to_close_price"
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- "sma_1h_to_close_price"
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- "sma_1d_to_close_price"
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- "sma_7d_to_close_price"
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- "ema_1h_to_close_price"
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- "ema_1d_to_close_price"
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dynamic_unknown_cat: []
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dynamic_known_real:
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- "effective_rates"
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- "vix_close_price"
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- "fear_greed_index"
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- "vol_1d"
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- "vol_7d"
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dynamic_known_cat:
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- "hour"
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- "weekday"
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static_real: []
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static_cat: []
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loss:
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value:
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name: "RMSE"
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model:
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value:
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name: "Informer"
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d_model: 512
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d_fully_connected: 512
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n_attention_heads: 4
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dropout: 0.3
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n_encoder_layers: 2
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n_decoder_layers: 3
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learning_rate: 0.0005
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optimizer: "Adam"
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41
configs/sweeps/informer-btcusdt-15m-rmse.yaml
Normal file
41
configs/sweeps/informer-btcusdt-15m-rmse.yaml
Normal file
@ -0,0 +1,41 @@
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program: ./scripts/train.py
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name: informer-btcusdt-15m-rmse-sweep
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project: wne-masters-thesis-testing
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command:
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- ${env}
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- ${interpreter}
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- ${program}
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- "./configs/experiments/informer-btcusdt-15m-rmse.yaml"
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- "--patience"
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- "15"
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method: random
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metric:
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goal: minimize
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name: val_loss
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parameters:
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past_window:
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distribution: int_uniform
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min: 20
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max: 120
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batch_size:
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values: [64, 128, 256]
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model:
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parameters:
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name:
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value: "Informer"
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d_model:
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values: [256, 512, 1024]
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d_fully_connected:
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values: [256, 512, 1024]
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n_attention_heads:
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values: [1, 2, 4]
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dropout:
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values: [0.05, 0.1, 0.2, 0.3]
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n_encoder_layers:
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values: [1, 2, 3]
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n_decoder_layers:
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values: [1, 2, 3]
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learning_rate:
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values: [0.001, 0.0005, 0.0001]
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optimizer:
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value: "Adam"
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43
configs/sweeps/informer-btcusdt-30m-rmse.yaml
Normal file
43
configs/sweeps/informer-btcusdt-30m-rmse.yaml
Normal file
@ -0,0 +1,43 @@
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program: ./scripts/train.py
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name: informer-btcusdt-30m-rmse-sweep
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project: wne-masters-thesis-testing
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command:
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- ${env}
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- ${interpreter}
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- ${program}
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- "./configs/experiments/informer-btcusdt-30m-rmse.yaml"
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- "--patience"
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- "15"
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- "--val-check-interval"
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- "100"
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method: random
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metric:
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goal: minimize
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name: val_loss
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parameters:
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past_window:
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distribution: int_uniform
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min: 20
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max: 120
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batch_size:
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values: [64, 128, 256]
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model:
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parameters:
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name:
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value: "Informer"
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d_model:
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values: [256, 512, 1024]
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d_fully_connected:
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values: [256, 512, 1024]
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n_attention_heads:
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values: [1, 2, 4]
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dropout:
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values: [0.05, 0.1, 0.2, 0.3]
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n_encoder_layers:
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values: [1, 2, 3]
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n_decoder_layers:
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values: [1, 2, 3]
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learning_rate:
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values: [0.001, 0.0005, 0.0001]
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optimizer:
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value: "Adam"
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41
configs/sweeps/informer-btcusdt-5m-rmse.yaml
Normal file
41
configs/sweeps/informer-btcusdt-5m-rmse.yaml
Normal file
@ -0,0 +1,41 @@
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program: ./scripts/train.py
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name: informer-btcusdt-5m-rmse-sweep
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project: wne-masters-thesis-testing
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command:
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- ${env}
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- ${interpreter}
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- ${program}
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- "./configs/experiments/informer-btcusdt-5m-rmse.yaml"
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- "--patience"
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- "15"
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method: random
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metric:
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goal: minimize
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name: val_loss
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parameters:
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past_window:
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distribution: int_uniform
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min: 20
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max: 120
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batch_size:
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values: [64, 128, 256]
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model:
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parameters:
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name:
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value: "Informer"
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d_model:
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values: [256, 512, 1024]
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d_fully_connected:
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values: [256, 512, 1024]
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n_attention_heads:
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values: [1, 2, 4]
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dropout:
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values: [0.05, 0.1, 0.2, 0.3]
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n_encoder_layers:
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values: [1, 2, 3]
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n_decoder_layers:
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values: [1, 2, 3]
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learning_rate:
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values: [0.001, 0.0005, 0.0001]
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optimizer:
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value: "Adam"
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@ -1,6 +1,6 @@
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import torch
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from pytorch_forecasting import QuantileLoss
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from pytorch_forecasting import QuantileLoss, RMSE
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from pytorch_forecasting.metrics.base_metrics import MultiHorizonMetric
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@ -16,6 +16,9 @@ def get_loss(config):
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b=config['loss']['b']
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)
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if loss_name == 'RMSE':
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return RMSE()
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raise ValueError("Unknown loss")
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