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---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-ner-finetuned-pii
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-ner-finetuned-pii
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0076
- Precision: 0.9427
- Recall: 0.9727
- F1: 0.9575
- Accuracy: 0.9982
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0105 | 1.0 | 1324 | 0.0132 | 0.8641 | 0.9464 | 0.9033 | 0.9960 |
| 0.0056 | 2.0 | 2648 | 0.0080 | 0.9298 | 0.9643 | 0.9467 | 0.9978 |
| 0.0047 | 3.0 | 3972 | 0.0076 | 0.9427 | 0.9727 | 0.9575 | 0.9982 |
### Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1
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