Update README.md

README.md

@@ -31,7 +31,7 @@ outputs = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
 
 ## Approach
 ### Dataset
-Since the Axolotl corpus contains misaligments, we just select the best samples (~8,000 samples). We also use the [bible-corpus](https://github.com/christos-c/bible-corpus) (7,821 samples). 
+Since the Axolotl corpus contains misaligments, we just select the best samples (12,207 samples). We also use the [bible-corpus](https://github.com/christos-c/bible-corpus) (7,821 samples). 
 
 | Axolotl best aligned books                            | 
 |:-----------------------------------------------------:|
@@ -73,7 +73,7 @@ For a fair comparison, the models are evaluated on the same 505 validation  Nahu
 | False                        | 1.34            | 6.17 | 26.96  | 
 | True                         | 1.31            | 6.18 | 28.21  | 
 
-The English-Spanish pretrained model improves BLEU and Chrf, and leads to faster convergence.
+The English-Spanish pretraining improves BLEU and Chrf, and leads to faster convergence.
 
 ## References
 - Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2019. Exploring the limits