Building LSTMs with PyTorch and Lightning AI Part 7: Resuming Training with Checkpoints
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In the previous article , we used TensorBoard to analyze the training process. Based on the graphs, we concluded that the model had not fully converged and could benefit from additional training epochs. Let's continue with that in this article. One of the advantages of Lightning is that we can continue training without starting from scratch. This is possible because Lightning automatically saves checkpoints during training. These checkpoints allow us to resume training from where we left off…
1Key Takeaways
- In the previous article , we used TensorBoard to analyze the training process.
- Based on the graphs, we concluded that the model had not fully converged and could benefit from additional training epochs.
- Let's continue with that in this article.
- One of the advantages of Lightning is that we can continue training without starting from scratch.
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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 used TensorBoard to analyze the training process.
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