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bert-base-portuguese-cased-finetuned-ner
This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0597
- Precision: 0.0484
- Recall: 0.0156
- F1: 0.0236
- Accuracy: 0.9851
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: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 77 | 0.1020 | 0.0 | 0.0 | 0.0 | 0.9817 |
| No log | 2.0 | 154 | 0.0695 | 0.0 | 0.0 | 0.0 | 0.9842 |
| No log | 3.0 | 231 | 0.0597 | 0.0484 | 0.0156 | 0.0236 | 0.9851 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
