---
base_model: bert-base-cased
license: apache-2.0
metrics:
- precision
- recall
- f1
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert-finetuned-ner4
  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-ner4

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: 0.0913
- Precision: 0.8712
- Recall: 0.8979
- F1: 0.8844
- Accuracy: 0.9850

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0612        | 1.0   | 2489  | 0.0625          | 0.8264    | 0.8552 | 0.8405 | 0.9816   |
| 0.0351        | 2.0   | 4978  | 0.0643          | 0.8474    | 0.8716 | 0.8594 | 0.9831   |
| 0.0189        | 3.0   | 7467  | 0.0651          | 0.8585    | 0.8995 | 0.8785 | 0.9843   |
| 0.0105        | 4.0   | 9956  | 0.0811          | 0.8690    | 0.8943 | 0.8815 | 0.9847   |
| 0.0047        | 5.0   | 12445 | 0.0913          | 0.8712    | 0.8979 | 0.8844 | 0.9850   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1