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README.md

@@ -80,7 +80,7 @@ The references are the `transcription` column of FLEURS and the `human_transcrip
 
 ## Relation to the paper
 
-The CER of a run is the corpus-level character error rate of its rows in percent, computed with the `cer` metric of the `evaluate` library and rounded to two decimals. Recomputed from these rows, it equals the CER the paper uses for 298 of the 299 runs. The rows of `ERISLab/q2a_openai_whisper-medium_CohereLabs_tiny-aya-earth_ws-ha_ng-600` on `google/fleurs` `ha_ng` come from a second evaluation of that checkpoint with the same settings; they score 46.29 CER, and the paper uses the 46.64 of the evaluation it logged. The paper's per-test-set tables print, for each test set, the lowest of these CERs among the three baselines and among the language's four trained checkpoints: the in-domain and out-of-domain test sets in the table that compares training with the baselines, and the trained and held-out varieties in the table of country varieties.
+The CER of a run is the corpus-level character error rate of its rows in percent, computed with the `cer` metric of the `evaluate` library and rounded to two decimals. Recomputed from these rows, it equals the CER the paper uses for all 299 runs. The paper's per-test-set tables print, for each test set, the lowest of these CERs among the three baselines and among the language's four trained checkpoints: the in-domain and out-of-domain test sets in the table that compares training with the baselines, and the trained and held-out varieties in the table of country varieties.
 
 ## Load the transcripts and score a run