| Hugging Face's logo | |
| --- | |
| language: ha | |
| datasets: | |
| --- | |
| # bert-base-multilingual-cased-finetuned-hausa | |
| ## 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. | |
| Specifically, this model is a *bert-base-multilingual-cased* model that was fine-tuned on Hausa 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") | |
| [{'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'}] | |
| ``` | |
| #### 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/) | |
| ## 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 | |
| -|-|- | |
| [MasakhaNER](https://github.com/masakhane-io/masakhane-ner) | 86.65 | 91.31 | |
| [VOA Hausa Textclass](https://huggingface.co/datasets/hausa_voa_topics) | 84.76 | 90.98 | |
| ### BibTeX entry and citation info | |
| By David Adelani | |
| ``` | |
| ``` | |