Update README.md

README.md

@@ -20,7 +20,7 @@ metrics:
 pipeline_tag: text-classification
 ---
 
-# naija-twitter-sentiment-afriberta-large
+# AfriSenti-twitter-sentiment-afroxlmr-large
 ## Model description
 **afrisenti-twitter-sentiment-afroxlmr-large** is the first multilingual twitter **sentiment classification** model for twelve (12) Nigerian languages (Amharic, Algerian Arabic, Darija, Hausa, Igbo, Kinyarwanda, Nigerian Pidgin, Mozambique Portuguese, Swahili, Tsonga, Twi, and Yorùbá) based on a fine-tuned  castorini/afriberta_large large model.  
 It achieves the **state-of-the-art performance** for the twitter sentiment classification task trained on the [AfriSenti corpus](https://github.com/afrisenti-semeval/afrisent-semeval-2023). 
@@ -63,13 +63,6 @@ This model is limited by its training dataset and domain i.e Twitter. This may n
 
 ## Training procedure
 This model was trained on a single Nvidia A10 GPU with recommended hyperparameters from the [original AfriSenti paper](https://arxiv.org/abs/2302.08956).
-## Eval results on Test set (F-score), average over 5 runs.
-language|F1-score
--|-
-hau |81.2
-ibo |80.8
-pcm |74.5
-yor |80.4
 
 ### BibTeX entry and citation info
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