Update README.md

README.md

@@ -92,7 +92,7 @@ pprint(ner_results)
 ## Training
 
 ### Training data
-We used the NER dataset in Catalan called [Ancora-ca-NER](https://huggingface.co/datasets/projecte-aina/ancora-ca-ner) for training and evaluation.
+We used the NER dataset in Catalan called [AnCora-Ca-NER](https://huggingface.co/datasets/projecte-aina/ancora-ca-ner) for training and evaluation.
 
 ### Training Procedure
 The model was trained with a batch size of 16 and a learning rate of 5e-5 for 5 epochs. We then selected the best checkpoint using the downstream task metric in the corresponding development set and then evaluated it on the test set.
@@ -104,9 +104,9 @@ The model was trained with a batch size of 16 and a learning rate of 5e-5 for 5
 This model was finetuned maximizing F1 score.
 
 ### Evaluation results
-We evaluated the _roberta-base-ca-v2-cased-ner_ on the Ancora-ca-ner test set against standard multilingual and monolingual baselines:
+We evaluated the _roberta-base-ca-v2-cased-ner_ on the AnCora-Ca-NER test set against standard multilingual and monolingual baselines:
 
-| Model        | Ancora-ca-ner (F1)| 
+| Model        | AnCora-Ca-NER (F1)| 
 | ------------|:-------------|
 | roberta-base-ca-v2-cased-ner | 89.29 |
 | roberta-base-ca-cased-ner | **89.76** |