multilingual-google/mt5-base-lumasaba-ner-v1
This model is a fine-tuned version of google/mt5-base on the Beijuka/Multilingual_PII_NER_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.7358
- Precision: 0.7910
- Recall: 0.7946
- F1: 0.7928
- Accuracy: 0.8100
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 | 398 | 2.7430 | 0.3351 | 0.45 | 0.3841 | 0.3355 |
| 4.9558 | 2.0 | 796 | 2.3019 | 0.2968 | 0.4930 | 0.3705 | 0.3133 |
| 2.7275 | 3.0 | 1194 | 2.0554 | 0.4145 | 0.4320 | 0.4231 | 0.3836 |
| 2.3526 | 4.0 | 1592 | 1.9726 | 0.7027 | 0.3305 | 0.4495 | 0.3887 |
| 2.3526 | 5.0 | 1990 | 1.6121 | 0.5668 | 0.5273 | 0.5463 | 0.5036 |
| 2.1054 | 6.0 | 2388 | 1.5167 | 0.4953 | 0.5711 | 0.5305 | 0.5334 |
| 1.8628 | 7.0 | 2786 | 1.3548 | 0.5812 | 0.6125 | 0.5964 | 0.5917 |
| 1.633 | 8.0 | 3184 | 1.2491 | 0.592 | 0.6359 | 0.6132 | 0.6126 |
| 1.4669 | 9.0 | 3582 | 1.1306 | 0.6485 | 0.6617 | 0.6551 | 0.6539 |
| 1.4669 | 10.0 | 3980 | 1.0705 | 0.6427 | 0.6773 | 0.6596 | 0.6722 |
| 1.2985 | 11.0 | 4378 | 0.8972 | 0.7033 | 0.7445 | 0.7233 | 0.7229 |
| 1.1477 | 12.0 | 4776 | 0.9050 | 0.7087 | 0.7336 | 0.7209 | 0.7220 |
| 1.0512 | 13.0 | 5174 | 0.8057 | 0.7515 | 0.7609 | 0.7562 | 0.7582 |
| 0.9269 | 14.0 | 5572 | 0.7670 | 0.7545 | 0.7805 | 0.7673 | 0.7718 |
| 0.9269 | 15.0 | 5970 | 0.6996 | 0.7830 | 0.8063 | 0.7945 | 0.7901 |
| 0.8489 | 16.0 | 6368 | 0.7031 | 0.7842 | 0.8063 | 0.7951 | 0.7935 |
| 0.7588 | 17.0 | 6766 | 0.6762 | 0.7891 | 0.8156 | 0.8022 | 0.8059 |
| 0.7432 | 18.0 | 7164 | 0.6648 | 0.7901 | 0.8234 | 0.8064 | 0.8080 |
| 0.6983 | 19.0 | 7562 | 0.6598 | 0.7991 | 0.8234 | 0.8111 | 0.8114 |
| 0.6983 | 20.0 | 7960 | 0.6626 | 0.7937 | 0.8203 | 0.8068 | 0.8097 |
Framework versions
- Transformers 4.55.4
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4