| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google-bert/bert-base-multilingual-cased |
| tags: |
| - named-entity-recognition |
| - hausa |
| - african-language |
| - pii-detection |
| - token-classification |
| - generated_from_trainer |
| datasets: |
| - Beijuka/Multilingual_PII_NER_dataset |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: multilingual-google-bert/bert-base-multilingual-cased-hausa-ner-v1 |
| results: |
| - task: |
| name: Token Classification |
| type: token-classification |
| dataset: |
| name: Beijuka/Multilingual_PII_NER_dataset |
| type: Beijuka/Multilingual_PII_NER_dataset |
| args: 'split: train+validation+test' |
| metrics: |
| - name: Precision |
| type: precision |
| value: 0.9529745042492918 |
| - name: Recall |
| type: recall |
| value: 0.9236683141131247 |
| - name: F1 |
| type: f1 |
| value: 0.9380925822643614 |
| - name: Accuracy |
| type: accuracy |
| value: 0.9788954787029192 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # multilingual-google-bert/bert-base-multilingual-cased-hausa-ner-v1 |
|
|
| This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the Beijuka/Multilingual_PII_NER_dataset dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1237 |
| - Precision: 0.9530 |
| - Recall: 0.9237 |
| - F1: 0.9381 |
| - Accuracy: 0.9789 |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| More information needed |
| |
| ## Training and evaluation data |
| |
| More information needed |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 5e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 20 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 301 | 0.1502 | 0.8451 | 0.8843 | 0.8643 | 0.9526 | |
| | 0.2112 | 2.0 | 602 | 0.1347 | 0.8573 | 0.9393 | 0.8964 | 0.9604 | |
| | 0.2112 | 3.0 | 903 | 0.1241 | 0.8813 | 0.9398 | 0.9096 | 0.9668 | |
| | 0.0847 | 4.0 | 1204 | 0.1770 | 0.8589 | 0.9460 | 0.9004 | 0.9640 | |
| | 0.0619 | 5.0 | 1505 | 0.1295 | 0.9012 | 0.9146 | 0.9078 | 0.9673 | |
| | 0.0619 | 6.0 | 1806 | 0.1502 | 0.9018 | 0.9254 | 0.9134 | 0.9683 | |
| | 0.0394 | 7.0 | 2107 | 0.1801 | 0.8729 | 0.9506 | 0.9101 | 0.9661 | |
| | 0.0394 | 8.0 | 2408 | 0.1807 | 0.9119 | 0.9321 | 0.9219 | 0.9705 | |
| | 0.0236 | 9.0 | 2709 | 0.1660 | 0.9259 | 0.9187 | 0.9223 | 0.9719 | |
| | 0.0124 | 10.0 | 3010 | 0.1878 | 0.8939 | 0.9496 | 0.9209 | 0.9705 | |
| | 0.0124 | 11.0 | 3311 | 0.2095 | 0.8874 | 0.9486 | 0.9170 | 0.9693 | |
| | 0.01 | 12.0 | 3612 | 0.2370 | 0.8814 | 0.9480 | 0.9135 | 0.9664 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.55.4 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.21.4 |
|
|
