🔒 torch lstm model not learning

[dense quartz]

Hello, my binary text classification always makes the same prediction

[dusky pine]

@dense quartz

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[dense quartz]

class LSTM(nn.Module):
    def __init__(self, num_emb, output_size, num_layers=1, hidden_size=128):
        super(LSTM, self).__init__()
        self.hidden_size = hidden_size
        self.num_layers = num_layers
        
        # Create an embedding for each token
        self.embedding = nn.Embedding(num_emb, 500)
        
        self.lstm = nn.LSTM(input_size=hidden_size, hidden_size=hidden_size, 
                            num_layers=num_layers, batch_first=True, dropout=0.5)
        self.fc_out = nn.Linear(hidden_size, output_size)

    def forward(self, input_seq):
        input_embs = self.embedding(input_seq)
        output, _ = self.lstm(input_embs)
        return self.fc_out(output[:, -1, :])

                
        return self.fc_out(output)```

[dusky pine]

@dense quartz

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