From a5778f337753637127eefd6efb8e7a42fa652c7f Mon Sep 17 00:00:00 2001
From: Jarrett Ye <jarrett.ye@outlook.com>
Date: Sat, 26 Apr 2025 10:05:13 +0800
Subject: [PATCH] Fix/FSRS-6 doesn't give <1d intervals & use log loss instead
 of RMSE(bins) (#3948)

* Fix/FSRS-6 doesn't give <1d intervals

https://forums.ankiweb.net/t/anki-25-05-beta-1/59710/8?u=l.m.sherlock

* use log loss instead of rmse to determine use which parameters
---
 rslib/src/scheduler/answering/mod.rs | 2 +-
 rslib/src/scheduler/fsrs/params.rs   | 6 +++---
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/rslib/src/scheduler/answering/mod.rs b/rslib/src/scheduler/answering/mod.rs
index e9461279f..13006fa88 100644
--- a/rslib/src/scheduler/answering/mod.rs
+++ b/rslib/src/scheduler/answering/mod.rs
@@ -468,7 +468,7 @@ impl Collection {
             self.get_config_bool(BoolKey::FsrsShortTermWithStepsEnabled);
         let fsrs_allow_short_term = if fsrs_enabled {
             let params = config.fsrs_params();
-            if params.len() == 19 {
+            if params.len() >= 19 {
                 params[17] > 0.0 && params[18] > 0.0
             } else {
                 false
diff --git a/rslib/src/scheduler/fsrs/params.rs b/rslib/src/scheduler/fsrs/params.rs
index 13e588535..d313a6851 100644
--- a/rslib/src/scheduler/fsrs/params.rs
+++ b/rslib/src/scheduler/fsrs/params.rs
@@ -116,10 +116,10 @@ impl Collection {
         })?;
         progress_thread.join().ok();
         if let Ok(fsrs) = FSRS::new(Some(current_params)) {
-            let current_rmse = fsrs.evaluate(items.clone(), |_| true)?.rmse_bins;
+            let current_log_loss = fsrs.evaluate(items.clone(), |_| true)?.log_loss;
             let optimized_fsrs = FSRS::new(Some(&params))?;
-            let optimized_rmse = optimized_fsrs.evaluate(items.clone(), |_| true)?.rmse_bins;
-            if current_rmse <= optimized_rmse {
+            let optimized_log_loss = optimized_fsrs.evaluate(items.clone(), |_| true)?.log_loss;
+            if current_log_loss <= optimized_log_loss {
                 if num_of_relearning_steps <= 1 {
                     params = current_params.to_vec();
                 } else {