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---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: pii_bert_model
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. -->
# pii_bert_model
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1020
- Precision: 0.9748
- Recall: 0.9744
- F1: 0.9745
## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 0.1362 | 1.0 | 150 | 0.1090 | 0.9663 | 0.9642 | 0.9645 |
| 0.0974 | 2.0 | 300 | 0.1192 | 0.9632 | 0.9619 | 0.9620 |
| 0.0736 | 3.0 | 450 | 0.0867 | 0.9696 | 0.9693 | 0.9693 |
| 0.0605 | 4.0 | 600 | 0.1111 | 0.9696 | 0.9682 | 0.9685 |
| 0.0445 | 5.0 | 750 | 0.0895 | 0.9729 | 0.9726 | 0.9726 |
| 0.0343 | 6.0 | 900 | 0.0952 | 0.9727 | 0.9719 | 0.9721 |
| 0.023 | 7.0 | 1050 | 0.0991 | 0.9745 | 0.9740 | 0.9741 |
| 0.0179 | 8.0 | 1200 | 0.1020 | 0.9748 | 0.9744 | 0.9745 |
### Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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