Update README.md

README.md

@@ -13,6 +13,9 @@ language:
 - la
 - fr
 - es
+tags:
+- handwritten-text-recognition
+pipeline_tag: image-to-text
 ---
 
 
@@ -58,4 +61,4 @@ TRIDIS was trained using a encode-decoder architecture based on a fine-tuned ver
 This final model operates in a multilingual environment (Latin, Old French, and Old Spanish) and is capable of recognizing several Latin script families (mostly Textualis and Cursiva) in documents produced circa 11th - 16th centuries. 
 
 During evaluation, the model showed an accuracy of 94.3% on the validation set and a CER (Character Error Ratio) of about 0.06 to 0.12 on three external unseen datasets 
-and a WER of about 0.14 to 0.26 respectively, which is about 30% lower compared to CRNN+CTC solutions trained on the same corpora.
+and a WER of about 0.14 to 0.26 respectively, which is about 30% lower compared to CRNN+CTC solutions trained on the same corpora.