A word

README.md

@@ -60,7 +60,7 @@ cm_probs.npy: {'thres': 0.2493, 'F1': 0.7148, 'F2': 0.7226, 'MCC': 0.7266, 'A':
 
 The swinv2_v3 tagger has got an unfair home advantage, in that out of the 20116 validation samples, only 2908 are guaranteed to not have been part of the training set.
 
-Gathering a more fair validation set is left as an excersise for the reader.  
+Gathering a more fair validation set is left as an exercise for the reader.  
 The exact datasets splits use for wd_v3 models are available here: https://huggingface.co/datasets/SmilingWolf/wdtagger-v3-seed
 
 The analysis script removes tags that have no positive samples in the val set.