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use one iteration on all test and train data for evaluation

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This commit is contained in:
Yinon Polak
2023-03-12 12:48:15 +02:00
parent 8a9f2aedbb
commit 1cf0e7be24
2 changed files with 16 additions and 16 deletions
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4
freqtrade/freqai/prediction_models/PyTorchClassifierMultiTarget.py
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@@ -39,7 +39,7 @@ class PyTorchClassifierMultiTarget(BasePyTorchModel):
self.max_iters = model_training_parameters.get("max_iters", 100)
self.batch_size = model_training_parameters.get("batch_size", 64)
self.learning_rate = model_training_parameters.get("learning_rate", 3e-4)
self.eval_iters = model_training_parameters.get("eval_iters", 10)
self.max_n_eval_batches = model_training_parameters.get("max_n_eval_batches", None)
self.class_name_to_index = None
self.index_to_class_name = None
@@ -79,7 +79,7 @@ class PyTorchClassifierMultiTarget(BasePyTorchModel):
device=self.device,
batch_size=self.batch_size,
max_iters=self.max_iters,
eval_iters=self.eval_iters,
max_n_eval_batches=self.max_n_eval_batches,
init_model=init_model
)
trainer.fit(data_dictionary)