Update README.md

README.md

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 # masakhane/afroxlmr-large-ner-masakhaner-1.0_2.0
 ## Model description
-**masakhane/afroxlmr-large-ner-masakhaner-1.0_2.0** is a **Named Entity Recognition (NER)** model for 21 African languages. Specifically, this model is a *Davlan/afro-xlmr-large* model that was fine-tuned on an aggregation of African language datasets obtained from two versions of MasakhaNER dataset i.e. [MasakhaNER 1.0](https://huggingface.co/datasets/masakhaner) and [MasakhaNER 2.0](https://huggingface.co/datasets/masakhane/masakhaner2.0). The languages covered are:
+**masakhane/afroxlmr-large-ner-masakhaner-1.0_2.0** is a **Named Entity Recognition (NER)** model for 21 African languages. Specifically, this model is a *Davlan/afro-xlmr-large* model that was fine-tuned on an aggregation of African language datasets obtained from two versions of MasakhaNER dataset i.e. [MasakhaNER 1.0](https://huggingface.co/datasets/masakhaner) and [MasakhaNER 2.0](https://huggingface.co/datasets/masakhane/masakhaner2). The languages covered are:
 
 - Amharic (Amharic)
 - Bambara (bam)
@@ -106,7 +106,7 @@ avg |**85.1**| **87.7**
 #### Limitations and bias
 This model is limited by its training dataset of entity-annotated news articles from a specific span of time. This may not generalize well for all use cases in different domains.  
 ## Training data
-This model was fine-tuned on the aggregation of [MasakhaNER 1.0](https://huggingface.co/datasets/masakhaner) and [MasakhaNER 2.0](https://huggingface.co/datasets/masakhane/masakhaner2.0) datasets
+This model was fine-tuned on the aggregation of [MasakhaNER 1.0](https://huggingface.co/datasets/masakhaner) and [MasakhaNER 2.0](https://huggingface.co/datasets/masakhane/masakhaner2) datasets
 
 The training dataset distinguishes between the beginning and continuation of an entity so that if there are back-to-back entities of the same type, the model can output where the second entity begins. As in the dataset, each token will be classified as one of the following classes:
 Abbreviation|Description