---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-ner-chunks
  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-chunks

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2207
- Precision: 0.8917
- Recall: 0.9214
- F1: 0.9063
- Accuracy: 0.9730

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.077         | 1.0   | 1756 | 0.0741          | 0.9068    | 0.9334 | 0.9199 | 0.9795   |
| 0.0443        | 2.0   | 3512 | 0.0649          | 0.9172    | 0.9428 | 0.9298 | 0.9841   |
| 0.0265        | 3.0   | 5268 | 0.0578          | 0.9250    | 0.9488 | 0.9368 | 0.9863   |
| 0.0109        | 4.0   | 7024 | 0.0651          | 0.9347    | 0.9492 | 0.9419 | 0.9866   |
| 0.005         | 5.0   | 8780 | 0.0692          | 0.9354    | 0.9502 | 0.9427 | 0.9869   |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0