updating readme

README.md

@@ -4,52 +4,53 @@ language: ha
 datasets:
 
 ---
-# bert-base-multilingual-cased-finetuned-hausa
+# bert-base-multilingual-cased-finetuned-swahili
 ## Model description
-**bert-base-multilingual-cased-finetuned-hausa** is a **Hausa BERT** model obtained by fine-tuning **bert-base-multilingual-cased** model on Hausa language texts.  It provides **better performance** than the multilingual BERT on text classification and named entity recognition datasets.  
+**bert-base-multilingual-cased-finetuned-swahili** is a **Swahili BERT** model obtained by fine-tuning **bert-base-multilingual-cased** model on Swahili language texts.  It provides **better performance** than the multilingual BERT on text classification and named entity recognition datasets.  
 
-Specifically, this model is a *bert-base-multilingual-cased* model that was fine-tuned on Hausa corpus. 
+Specifically, this model is a *bert-base-multilingual-cased* model that was fine-tuned on Swahili corpus. 
 ## Intended uses & limitations
 #### How to use
 You can use this model with Transformers *pipeline* for masked token prediction.
 ```python
 >>> from transformers import pipeline
->>> unmasker = pipeline('fill-mask', model='Davlan/bert-base-multilingual-cased-finetuned-hausa')
->>> unmasker("Shugaban [MASK] Muhammadu Buhari ya amince da shawarar da ma’aikatar sufuri karkashin jagoranci")
+>>> unmasker = pipeline('fill-mask', model='Davlan/bert-base-multilingual-cased-finetuned-swahili')
+>>> unmasker("Jumatatu, Bwana Kagame alielezea shirika la France24 huko [MASK] kwamba "hakuna uhalifu ulitendwa")
                     
-[{'sequence': 
-'[CLS] Shugaban Nigeria Muhammadu Buhari ya amince da shawarar da ma [UNK] aikatar sufuri karkashin jagoranci [SEP]', 
-'score': 0.9762618541717529, 
-'token': 22045, 
-'token_str': 'Nigeria'}, 
-{'sequence': '[CLS] Shugaban Ka Muhammadu Buhari ya amince da shawarar da ma [UNK] aikatar sufuri karkashin jagoranci [SEP]', 'score': 0.007239189930260181, 
-'token': 25444, 
-'token_str': 'Ka'}, 
-{'sequence': '[CLS] Shugaban, Muhammadu Buhari ya amince da shawarar da ma [UNK] aikatar sufuri karkashin jagoranci [SEP]', 'score': 0.001990817254409194, 
-'token': 117, 
-'token_str': ','}, 
-{'sequence': '[CLS] Shugaban Ghana Muhammadu Buhari ya amince da shawarar da ma [UNK] aikatar sufuri karkashin jagoranci [SEP]', 'score': 0.001566368737258017, 
-'token': 28682, 
-'token_str': 'Ghana'}, 
-{'sequence': '[CLS] Shugabanmu Muhammadu Buhari ya amince da shawarar da ma [UNK] aikatar sufuri karkashin jagoranci [SEP]', 'score': 0.0009375187801197171, 
-'token': 11717, 
-'token_str': '##mu'}]
+[{'sequence': 'Jumatatu, Bwana Kagame alielezea shirika la France24 huko Paris kwamba hakuna uhalifu ulitendwa', 
+'score': 0.31642526388168335, 
+'token': 10728, 
+'token_str': 'Paris'}, 
+{'sequence': 'Jumatatu, Bwana Kagame alielezea shirika la France24 huko Rwanda kwamba hakuna uhalifu ulitendwa', 
+'score': 0.15753623843193054, 
+'token': 57557, 
+'token_str': 'Rwanda'}, 
+{'sequence': 'Jumatatu, Bwana Kagame alielezea shirika la France24 huko Burundi kwamba hakuna uhalifu ulitendwa', 
+'score': 0.07211585342884064, 
+'token': 57824, 
+'token_str': 'Burundi'}, 
+{'sequence': 'Jumatatu, Bwana Kagame alielezea shirika la France24 huko France kwamba hakuna uhalifu ulitendwa', 
+'score': 0.029844321310520172, 
+'token': 10688, 
+'token_str': 'France'}, 
+{'sequence': 'Jumatatu, Bwana Kagame alielezea shirika la France24 huko Senegal kwamba hakuna uhalifu ulitendwa', 
+'score': 0.0265930388122797, 
+'token': 38052, 
+'token_str': 'Senegal'}]
 
 ```
 #### 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 [Hausa CC-100](http://data.statmt.org/cc-100/)
+This model was fine-tuned on [Swahili CC-100](http://data.statmt.org/cc-100/)
 
 ## Training procedure
 This model was trained on a single NVIDIA V100 GPU
 
 ## Eval results on Test set (F-score, average over 5 runs)
-Dataset| mBERT F1 | ha_bert F1
+Dataset| mBERT F1 | sw_bert F1
 -|-|-
-[Hausa VOA NER](https://huggingface.co/datasets/hausa_voa_ner) | | 
-[MasakhaNER](https://github.com/masakhane-io/masakhane-ner) | 86.65 | 
-[VOA Hausa Textclass](https://huggingface.co/datasets/hausa_voa_topics) | 84.76 | 90.98 
+[MasakhaNER](https://github.com/masakhane-io/masakhane-ner) | 86.80 | 
 
 ### BibTeX entry and citation info
 By David Adelani