---
library_name: transformers
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
- wer
model-index:
- name: bert-finetuned-ner-tokenizer
  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-tokenizer

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: 0.0280
- Precision: 0.7896
- Recall: 0.8536
- F1: 0.8203
- Accuracy: 0.9919
- Wer: 0.0079

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:------:|
| 0.0515        | 1.0   | 768  | 0.0273          | 0.7510    | 0.8495 | 0.7972 | 0.9907   | 0.0089 |
| 0.0192        | 2.0   | 1536 | 0.0259          | 0.7567    | 0.8627 | 0.8062 | 0.9911   | 0.0086 |
| 0.0158        | 3.0   | 2304 | 0.0259          | 0.7828    | 0.8565 | 0.8180 | 0.9916   | 0.0082 |
| 0.0111        | 4.0   | 3072 | 0.0280          | 0.7896    | 0.8536 | 0.8203 | 0.9919   | 0.0079 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1