luganda-ner-bert-v7
This model is a fine-tuned version of 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