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docs(tutorial): clarify location of "learning steps" and "relearning …
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…steps" settings (#706)
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loqusion authored Nov 17, 2024
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Expand Up @@ -19,7 +19,7 @@ If you find this tutorial helpful, I'd be grateful if you could give it a star.
Are you busy and have no time to waste? Here's a summary of the guide.

1) Go to deck options and enable FSRS under the "FSRS" section (under the "Advanced" section in Anki versions before 24.04), at the bottom of the deck options page. FSRS can only be enabled globally; you cannot enable it for some presets and disable it for others.
2) Ensure that all your learning and re-learning steps are shorter than `1d` and can be completed on the same day. `23h` is not recommended even though it's less than one day because you won't be able to finish this step on the same day as your first review. Steps such as `10m` or `30m` are good.
2) Ensure that all your learning steps (under the "New Cards" section) and re-learning steps (under the "Lapses" section) are shorter than `1d` and can be completed on the same day. `23h` is not recommended even though it's less than one day because you won't be able to finish this step on the same day as your first review. Steps such as `10m` or `30m` are good.
3) Click the "Optimize" button under the "FSRS parameters" field. If you see a message that says "The FSRS parameters currently appear to be optimal", that's fine. In the versions before 24.06, an error message might pop up, saying that you don't have a sufficient number of reviews (400 in Anki 24.04, 1000 in older versions). In that case, use FSRS with the default parameters; it's still better than using the legacy SM-2 algorithm.
4) Choose a value of desired retention: the proportion of cards recalled successfully when they are due. **This is the most important setting in FSRS. Higher retention leads to shorter intervals and more reviews per day.** 80-95% is reasonable, 90% should work fine for most people. Parameters and desired retention are preset-specific, you can make multiple presets with different parameters and desired retention.

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