Update app.py

app.py

@@ -38,21 +38,21 @@ class EEG_CNN(nn.Module):
     def __init__(self, input_dim, output_dim):
         super().__init__()
 
-        self.conv1 = nn.Conv1d(1, 16, kernel_size=3, padding=1)
-        self.bn1 = nn.BatchNorm1d(16)
+        self.conv1 = nn.Conv1d(1, 32, kernel_size=7, padding=3)
+        self.bn1 = nn.BatchNorm1d(32)
 
-        self.conv2 = nn.Conv1d(16, 32, kernel_size=3, padding=1)
-        self.bn2 = nn.BatchNorm1d(32)
+        self.conv2 = nn.Conv1d(32, 64, kernel_size=5, padding=2)
+        self.bn2 = nn.BatchNorm1d(64)
 
-        self.conv3 = nn.Conv1d(32, 64, kernel_size=3, padding=1)
-        self.bn3 = nn.BatchNorm1d(64)
+        self.conv3 = nn.Conv1d(64, 128, kernel_size=3, padding=1)
+        self.bn3 = nn.BatchNorm1d(128)
 
         self.pool = nn.AdaptiveAvgPool1d(1)
 
-        self.fc = nn.Linear(64, output_dim)
+        self.fc = nn.Linear(128, output_dim)
 
     def forward(self, x):
-        x = x.unsqueeze(1)  # (batch, 1, 76)
+        x = x.unsqueeze(1)
 
         x = torch.relu(self.bn1(self.conv1(x)))
         x = torch.relu(self.bn2(self.conv2(x)))