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Lære Challenge: Building an LSTM for Sentiment Analysis | Sentiment Analysis
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Challenge: Building an LSTM for Sentiment Analysis

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  • Define the SentimentLSTM class, completing its __init__ method to set up the nn.Embedding, nn.LSTM, and nn.Linear layers, and implement its forward method to process input sequences.

  • Instantiate the SentimentLSTM model, then define the nn.BCEWithLogitsLoss criterion and torch.optim.Adam optimizer.

  • Implement the training and evaluation loops, including forward and backward passes, parameter updates, and accuracy calculation.

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Challenge: Building an LSTM for Sentiment Analysis

Opgave

Swipe to start coding

  • Define the SentimentLSTM class, completing its __init__ method to set up the nn.Embedding, nn.LSTM, and nn.Linear layers, and implement its forward method to process input sequences.

  • Instantiate the SentimentLSTM model, then define the nn.BCEWithLogitsLoss criterion and torch.optim.Adam optimizer.

  • Implement the training and evaluation loops, including forward and backward passes, parameter updates, and accuracy calculation.

Løsning

Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

close

Awesome!

Completion rate improved to 4.76

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