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Set training script to execute remotely

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Victor Mylle
2024-02-21 18:13:51 +01:00
parent f8823f7efa
commit 4ad3336b98
1 changed files with 6 additions and 6 deletions
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12
src/training_scripts/autoregressive_quantiles.py
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@@ -15,7 +15,7 @@ from src.models.time_embedding_layer import TimeEmbedding
#### ClearML #### #### ClearML ####
clearml_helper = ClearMLHelper(project_name="Thesis/NrvForecast") clearml_helper = ClearMLHelper(project_name="Thesis/NrvForecast")
task = clearml_helper.get_task(task_name="Autoregressive Quantile Regression: Linear + Quarter + DoW + Load + Wind + Net") task = clearml_helper.get_task(task_name="Autoregressive Quantile Regression: Non Linear")
#### Data Processor #### #### Data Processor ####
@@ -59,11 +59,11 @@ else:
quantiles = eval(quantiles) quantiles = eval(quantiles)
model_parameters = { model_parameters = {
"learning_rate": 0.0001, "learning_rate": 0.001,
"hidden_size": 512, "hidden_size": 512,
"num_layers": 2, "num_layers": 4,
"dropout": 0.2, "dropout": 0.2,
"time_feature_embedding": 4, "time_feature_embedding": 8,
} }
model_parameters = task.connect(model_parameters, name="model_parameters") model_parameters = task.connect(model_parameters, name="model_parameters")
@@ -96,9 +96,9 @@ trainer = AutoRegressiveQuantileTrainer(
trainer.add_metrics_to_track( trainer.add_metrics_to_track(
[PinballLoss(quantiles), MSELoss(), L1Loss(), CRPSLoss(quantiles)] [PinballLoss(quantiles), MSELoss(), L1Loss(), CRPSLoss(quantiles)]
) )
trainer.early_stopping(patience=10) trainer.early_stopping(patience=15)
trainer.plot_every(5) trainer.plot_every(5)
trainer.train(task=task, epochs=epochs, remotely=False) trainer.train(task=task, epochs=epochs, remotely=True)
### Policy Evaluation ### ### Policy Evaluation ###
idx_samples = trainer.test_set_samples idx_samples = trainer.test_set_samples