---
license: apache-2.0
base_model: huggingface-course/bert-finetuned-ner
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
  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-finetuned-ner

This model is a fine-tuned version of [huggingface-course/bert-finetuned-ner](https://huggingface.co/huggingface-course/bert-finetuned-ner) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0731
- Precision: 0.9344
- Recall: 0.9524
- F1: 0.9433
- Accuracy: 0.9867

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0273        | 1.0   | 1756 | 0.0761          | 0.9250    | 0.9424 | 0.9336 | 0.9849   |
| 0.0183        | 2.0   | 3512 | 0.0671          | 0.9363    | 0.9505 | 0.9434 | 0.9865   |
| 0.0077        | 3.0   | 5268 | 0.0731          | 0.9344    | 0.9524 | 0.9433 | 0.9867   |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0