| --- |
| library_name: transformers |
| language: |
| - lg |
| license: apache-2.0 |
| base_model: google-bert/bert-base-multilingual-cased |
| tags: |
| - named-entity-recognition |
| - luganda |
| - african-languages |
| - pii-detection |
| - token-classification |
| - generated_from_trainer |
| datasets: |
| - Beijuka/Luganda_Monolingual_PII_dataset |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: luganda-ner-bert-v7 |
| results: |
| - task: |
| name: Token Classification |
| type: token-classification |
| dataset: |
| name: Beijuka/Luganda_Monolingual_PII_dataset |
| type: Beijuka/Luganda_Monolingual_PII_dataset |
| args: 'split: train+validation+test' |
| metrics: |
| - name: Precision |
| type: precision |
| value: 0.8336713995943205 |
| - name: Recall |
| type: recall |
| value: 0.8162859980139027 |
| - name: F1 |
| type: f1 |
| value: 0.8248871048670346 |
| - name: Accuracy |
| type: accuracy |
| value: 0.9459025442866462 |
| --- |
| |
| <!-- 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. --> |
|
|
| # luganda-ner-bert-v7 |
|
|
| 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/Luganda_Monolingual_PII_dataset dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3195 |
| - Precision: 0.8337 |
| - Recall: 0.8163 |
| - F1: 0.8249 |
| - Accuracy: 0.9459 |
| |
| ## 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 with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 261 | 0.4382 | 0.5831 | 0.5124 | 0.5455 | 0.8761 | |
| | 0.4959 | 2.0 | 522 | 0.2885 | 0.7147 | 0.7289 | 0.7217 | 0.9171 | |
| | 0.4959 | 3.0 | 783 | 0.2778 | 0.7592 | 0.7200 | 0.7390 | 0.9308 | |
| | 0.1547 | 4.0 | 1044 | 0.2552 | 0.8016 | 0.7865 | 0.7940 | 0.9389 | |
| | 0.1547 | 5.0 | 1305 | 0.2718 | 0.7908 | 0.7885 | 0.7897 | 0.9389 | |
| | 0.061 | 6.0 | 1566 | 0.2881 | 0.8360 | 0.7795 | 0.8068 | 0.9426 | |
| | 0.061 | 7.0 | 1827 | 0.2908 | 0.8008 | 0.8143 | 0.8075 | 0.9446 | |
| | 0.023 | 8.0 | 2088 | 0.3195 | 0.8337 | 0.8163 | 0.8249 | 0.9459 | |
| | 0.023 | 9.0 | 2349 | 0.3190 | 0.8208 | 0.8143 | 0.8175 | 0.9476 | |
| | 0.0088 | 10.0 | 2610 | 0.3318 | 0.8354 | 0.7964 | 0.8155 | 0.9458 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.53.0 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.2 |
| |
