Update README.md

README.md

@@ -10,6 +10,14 @@ BERT medium (cased) model trained on a subset of 125M tokens of cc100-Swahili fo
 The model has 51M parameters (8L), and a vocab size of 50K.
 It was trained for 500K steps with a sequence length of 512 tokens.
 
+Results
+-----------
+|           | [bert-base-sw](https://huggingface.co/orai-nlp/bert-base-sw) | [bert-medium-sw](https://huggingface.co/orai-nlp/bert-medium-sw) | Flair | [mBERT](https://huggingface.co/bert-base-multilingual-cased) | [swahBERT](https://github.com/gatimartin/SwahBERT#pre-trained-models) (Martin et al., 2022b) |
+|-----------|--------------|----------------|-------|-------|---------------------------------|
+| NERC      | **92.09**    | 91.63          | 92.04 | 91.17 | 88.60                           |
+| Topic     | **93.07**    | 92.88          | 91.83 | 91.52 | 90.90                           |
+| Sentiment | **79.04**    | 77.07          | 73.60 | 69.17 | 71.12                           |
+| QNLI      | 63.34        | 63.87          | 52.82 | 63.48 | **64.72**                       |
 
 Authors
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