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roberta_ner_personal_info
This model is a fine-tuned version of tner/roberta-large-ontonotes5 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0401
- Precision: 0.9334
- Recall: 0.9683
- F1: 0.9505
- Accuracy: 0.9915
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: 20
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 499 | 0.0443 | 0.9058 | 0.9348 | 0.9201 | 0.9884 |
| 0.2009 | 2.0 | 998 | 0.0410 | 0.9241 | 0.9604 | 0.9419 | 0.9904 |
| 0.0359 | 3.0 | 1497 | 0.0344 | 0.9400 | 0.9632 | 0.9515 | 0.9922 |
| 0.0206 | 4.0 | 1996 | 0.0392 | 0.9379 | 0.9648 | 0.9512 | 0.9916 |
| 0.0141 | 5.0 | 2495 | 0.0377 | 0.9403 | 0.9697 | 0.9547 | 0.9921 |
| 0.0103 | 6.0 | 2994 | 0.0392 | 0.9371 | 0.9681 | 0.9523 | 0.9918 |
| 0.0082 | 7.0 | 3493 | 0.0401 | 0.9334 | 0.9683 | 0.9505 | 0.9915 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
