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urdu-roberta-ner
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: 0.1387
- Precision: 0.7735
- Recall: 0.8129
- F1: 0.7927
- Accuracy: 0.9541
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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.165 | 1.0 | 2272 | 0.1521 | 0.7204 | 0.7960 | 0.7564 | 0.9454 |
0.1208 | 2.0 | 4544 | 0.1413 | 0.7577 | 0.8101 | 0.7830 | 0.9510 |
0.0977 | 3.0 | 6816 | 0.1387 | 0.7735 | 0.8129 | 0.7927 | 0.9541 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.13.3