Update README.md

README.md

@@ -11,7 +11,7 @@ The model's name is taken from 'machine learning' (ML) and translation (Tibetan:
 
 The model expects Tibetan transliterated according to THL Simplified Phonetic Transliteration as an input and outputs an English translation.
 
-The model was evaluated using the BLEU metric, with a final score of 83.4374 on evaluation data. 
+The model was evaluated using the BLEU metric as implemented by [sacreBLEU](https://pypi.org/project/sacrebleu/), with a final score of 83.4374 on evaluation data. 
 However, this score is unusually high, and may be the result of testing error. Stricter evaluation
 and training are currently in progress.
 
@@ -246,7 +246,8 @@ This model was trained for 6 epochs on the dataset described above.
 
 ## Evaluation
 
-The evaluation metric for this model was the BLEU score. BLEU (Bilingual Evaluation Understudy) scores measure the quality of 
+The evaluation metric for this model was the BLEU score as implemented by [sacreBLEU](https://pypi.org/project/sacrebleu/). 
+BLEU (Bilingual Evaluation Understudy) scores measure the quality of 
 machine-generated translations by comparing them to human-provided reference translations. The score ranges from 0 to 100, 
 where 100 represents a perfect match with the reference translations. It evaluates the precision of n-grams (word sequences) 
 in the generated text, with higher scores indicating closer alignment to the reference translations. A brevity penalty is applied