FSRS parameters for different card types

I am using Anki to learn Spanish vocabulary. My notes consist of a word and a picture. I like to learn the notes both ways: a Word->Picture card and a Picture->Word card.

In an effort to improve retention, I switched to FSRS two months ago. However, I am still struggling to reach my desired retention of 85%.

I previously had both card types in a single preset. Since Word->Picture is easier than Picture->Word, this may not be appropriate. As an experiment, today I split my cards into two separate presets. I hope this will give me more accurate scheduling in the future.

Single preset FSRS parameters (old)

I optimized these parameters today before splitting the cards.

FSRS parameters: 0.1609, 0.4215, 1.7874, 4.6831, 4.9613, 1.3292, 0.8547, 0.0000, 1.3738, 0.2560, 0.7025, 2.3295, 0.1508, 0.4556, 1.2092, 0.2272, 3.2732
Log loss: 0.4334, RMSE(bins): 3.52%

Split preset FSRS parameters (new)

As demonstrated below, Word->Picture was too easy, but Picture->Word was too hard.

Word->Picture statistics

Average difficulty: 70%
Average stability: 1.8 months
Average retrievability: 91%
Answer buttons (1 month): Learning 90.3%; Young 90.53%; Mature 92.08%

Newly optimized FSRS parameters: 0.2045, 0.6116, 3.1642, 9.4648, 5.0499, 0.9030, 1.1044, 0.0290, 1.4329, 0.0345, 0.9120, 2.2954, 0.0513, 0.4450, 2.0277, 0.2272, 2.8755
Log loss: 0.3081, RMSE(bins): 3.02%

Picture->Word statistics

Average difficulty: 89%
Average stability: 23 days
Average retrievability: 90%
Answer buttons (1 month): Learning 80.87%; Young 80.52%; Mature 71.14%

Newly optimized FSRS parameters: 0.1405, 0.2357, 0.5124, 0.8598, 5.2881, 1.0804, 0.7191, 0.0375, 1.1031, 0.5867, 0.4996, 2.2051, 0.0626, 0.4601, 1.3239, 0.2272, 3.2784
Log loss: 0.4908, RMSE(bins): 4.10%


The Word->Picture RMSE improved. Curiously, the Picture->Word RMSE got worse. Interesting.

I will monitor my retention in the coming weeks. Most importantly, I need to improve retention for mature Picture->Word cards.

As a thought: might it be beneficial for Anki to automatically apply different FSRS parameters to different card types?

You shouldn’t compare RMSE like this. Comparing RMSE makes sense only when the evaluation is done on the same reviews. In this case, the number of reviews becomes roughly half.

For a proper comparison, copy the old parameters into the new presets and then calculate the RMSE for each preset using both old and new parameters.


I realized another advantage of using distinct scheduling parameters for distinct Card Types: siblings will more easily be dispersed over time.