fix: normalize hyper params

2025-09-21 13:10:07 +02:00
parent 83d21c640b
commit 63e23d6600
8 changed files with 26 additions and 19 deletions
@@ -13,7 +13,7 @@ from research.neural_network_model import NeuralNetworkModel
 class LSTMModel(NeuralNetworkModel):
    """LSTM model for sequence learning"""

-    def build_model_with_vocab(self, vocab_size: int, max_len: int = 6, **kwargs) -> Any:
+    def build_model_with_vocab(self, vocab_size: int, **kwargs) -> Any:
        params = kwargs
        model = Sequential(
            [
@@ -21,7 +21,6 @@ class LSTMModel(NeuralNetworkModel):
                Embedding(
                    input_dim=vocab_size,
                    output_dim=params.get("embedding_dim", 64),
-                    input_length=max_len,
                    mask_zero=True,
                ),
                # Stacked bidirectional LSTMs: first returns sequences to feed the next.