luganda-ner-v6
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2031
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9713
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.2234 | 1.0 | 618 | 0.2186 | 0.0 | 0.0 | 0.0 | 0.9498 |
0.0884 | 2.0 | 1236 | 0.1490 | 0.0 | 0.0 | 0.0 | 0.9609 |
0.0686 | 3.0 | 1854 | 0.1606 | 0.0 | 0.0 | 0.0 | 0.9617 |
0.0484 | 4.0 | 2472 | 0.1728 | 0.0 | 0.0 | 0.0 | 0.9639 |
0.0233 | 5.0 | 3090 | 0.1682 | 0.0 | 0.0 | 0.0 | 0.9658 |
0.0196 | 6.0 | 3708 | 0.1738 | 0.0 | 0.0 | 0.0 | 0.9702 |
0.0135 | 7.0 | 4326 | 0.1744 | 0.0 | 0.0 | 0.0 | 0.9701 |
0.0122 | 8.0 | 4944 | 0.1979 | 0.0 | 0.0 | 0.0 | 0.9699 |
0.0062 | 9.0 | 5562 | 0.1992 | 0.0 | 0.0 | 0.0 | 0.9708 |
0.0047 | 10.0 | 6180 | 0.2031 | 0.0 | 0.0 | 0.0 | 0.9713 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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