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bert-base-sw

Feature Extraction
Transformers
PyTorch
Safetensors
Swahili
bert
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@@ -12,7 +12,6 @@ It was trained for 500K steps with a sequence length of 512 tokens.
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  Results
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  | | [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) |
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  |-----------|--------------|----------------|-------|-------|---------------------------------|
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  | NERC | **92.09** | 91.63 | 92.04 | 91.17 | 88.60 |
 
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  Results
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  -----------
 
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  | | [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) |
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  |-----------|--------------|----------------|-------|-------|---------------------------------|
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  | NERC | **92.09** | 91.63 | 92.04 | 91.17 | 88.60 |