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README.md

@@ -20,7 +20,7 @@ This is a BERT model fine-tuned for Named Entity Recognition (NER).
 
 This is a fine-tuned BERT model for Named Entity Recognition (NER) task using CONLL2002 dataset.
 
-In the first part, the dataset must be pre-processed in order to give it to the model. This is done using the 🤗 Transformers and BERT tokenizers. Once this is done, finetuning is applied from *[bert-base-cased](https://huggingface.co/google-bert/bert-base-cased)* and using the 🤗 *AutoModelForTokenClassification*.
+In the first part, the dataset must be pre-processed in order to give it to the model. This is done using the 🤗 Transformers and BERT tokenizers. Once this is done, finetuning is applied from *[BETO](https://huggingface.co/NazaGara/NER-fine-tuned-BETO)* and using the 🤗 *AutoModelForTokenClassification*.
 
 Finally, the model is trained obtaining the neccesary metrics for evaluating its performance (Precision, Recall, F1 and Accuracy)