---
license: mit
base_model: dslim/bert-base-NER
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 is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0019
- Precision: 0.7429
- Recall: 0.7192
- F1: 0.7309
- Accuracy: 0.9995

## Model description

Model is fine tuned in a PII task in students essays

## Intended uses & limitations

More information needed

## Training and evaluation data

to be updated

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0023        | 1.0   | 724  | 0.0033          | 0.6791    | 0.4589 | 0.5477 | 0.9992   |
| 0.0014        | 2.0   | 1448 | 0.0021          | 0.7218    | 0.6575 | 0.6882 | 0.9994   |
| 0.001         | 3.0   | 2172 | 0.0019          | 0.7429    | 0.7192 | 0.7309 | 0.9995   |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1