Building LSTMs with PyTorch and Lightning AI Part 8: Setting Up a Simpler LSTM
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In the previous article , we saw how easily we could continue training by adding more epochs. We also observed the improvements in the model's predictions using TensorBoard. Let's train the model one more time to bring the predictions even closer to the desired values. As before, we first retrieve the latest checkpoint. path_to_best_checkpoint = trainer . checkpoint_callback . best_model_path Next, we increase the maximum number of epochs to 5000 . trainer = L . Trainer ( max_epochs = 5000 )…
1Key Takeaways
- In the previous article , we saw how easily we could continue training by adding more epochs.
- We also observed the improvements in the model's predictions using TensorBoard.
- Let's train the model one more time to bring the predictions even closer to the desired values.
- As before, we first retrieve the latest checkpoint.
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that in the previous article , we saw how easily we could continue training by adding more epochs.
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