--- a
+++ b/bert_mixup/early_mixup/model.py
@@ -0,0 +1,31 @@
+from torch import nn
+
+class MolNet(nn.Module):
+    """
+    This class is created to specify the Neural Network on which vectorized datasets we have created previously
+    is trained on, validated and later tested.
+    It consist of one input layer, one output layer and multiple hidden layers.
+    ...
+    """
+    def __init__(self, input_dim, output_dim, dropout=0.5):
+        super(MolNet, self).__init__()
+        # Layer definitions
+        self.layers = nn.Sequential(
+        nn.Linear(input_dim, 1024),
+        nn.ReLU(),
+        nn.Dropout(dropout),
+        nn.Linear(1024, 512),
+        nn.ReLU(),
+        nn.Dropout(dropout),
+        nn.Linear(512, 256),
+        nn.ReLU(),
+        nn.Dropout(dropout),
+        nn.Linear(256, 128),
+        nn.ReLU(),
+        nn.Dropout(dropout),
+        nn.Linear(128, output_dim)
+        )
+
+    def forward(self, x):
+        # Forward pass
+        return self.layers(x)
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