Update README.md

README.md

@@ -17,7 +17,7 @@ metrics:
 - accuracy
 ---
 
-# TUS Named Entity Recognition
+# Swahili Named Entity Recognition
 
 - **TUS-NER-sw** is a fine-tuned BERT model that is ready to use for **Named Entity Recognition** and achieves **state-of-the-art performance 😀** 
 - Finetuned from model: [eolang/SW-v1](https://huggingface.co/eolang/SW-v1)
@@ -51,4 +51,4 @@ The languages forming this dataset are: Amharic, Hausa, Igbo, Kinyarwanda, Lugan
 
 ## Training procedure
 
-This model was trained on a single NVIDIA RTX 3090 GPU with recommended hyperparameters from the [original BERT paper](https://arxiv.org/pdf/1810.04805) which trained & evaluated the model on CoNLL-2003 NER task.
+This model was trained on a single NVIDIA RTX 3090 GPU with recommended hyperparameters from the [original BERT paper](https://arxiv.org/pdf/1810.04805).