diff --git a/src/hyperparameters.py b/src/hyperparameters.py
index 6e9704a..597929b 100644
--- a/src/hyperparameters.py
+++ b/src/hyperparameters.py
@@ -6,8 +6,8 @@ class Hyperparameters:
         train_dataset="data/train_data.tfrecords",
         test_dataset="data/test_data.tfrecords",
         eval_dataset="data/eval_data.tfrecords",
-        epochs=1000,
-        batch_size=256,
+        epochs=100,
+        batch_size=64,
         learning_rate=0.004,
         l2_rate=0.001,
         log_directory="logs",
diff --git a/src/model.py b/src/model.py
index 907fefa..30f2ff8 100644
--- a/src/model.py
+++ b/src/model.py
@@ -17,23 +17,16 @@ def build_model(hyperparams) -> Model:
     """
     model = Sequential(
         [
-            Input(shape=(None, hyperparams.max_length, len(BASES))),
+            Input(shape=(hyperparams.batch_size, hyperparams.max_length, len(BASES))),
             Masking(mask_value=-1),
-            Conv1D(
-                filters=16,
-                kernel_size=5,
-                activation="relu",
-                kernel_regularizer=l2(hyperparams.l2_rate),
+            Dense(
+                units=16, activation="relu", kernel_regularizer=l2(hyperparams.l2_rate)
             ),
-            MaxPool1D(pool_size=3, strides=1),
-            Conv1D(
-                filters=16,
-                kernel_size=3,
-                activation="relu",
-                kernel_regularizer=l2(hyperparams.l2_rate),
+            Dropout(rate=0.3),
+            Dense(
+                units=16, activation="relu", kernel_regularizer=l2(hyperparams.l2_rate)
             ),
-            MaxPool1D(pool_size=3, strides=1),
-            GlobalAveragePooling1D(),
+            Dropout(rate=0.3),
             Dense(
                 units=16, activation="relu", kernel_regularizer=l2(hyperparams.l2_rate)
             ),