---
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-base-cased-finetuned
  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-base-cased-finetuned

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: 0.0218
- Precision: 0.8097
- Recall: 0.8573
- F1: 0.8328
- Accuracy: 0.9938
- Wer: 0.0062

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:------:|
| 0.0453        | 1.0   | 774  | 0.0182          | 0.7838    | 0.8731 | 0.8261 | 0.9935   | 0.0065 |
| 0.015         | 2.0   | 1548 | 0.0167          | 0.7852    | 0.8749 | 0.8276 | 0.9937   | 0.0063 |
| 0.0106        | 3.0   | 2322 | 0.0176          | 0.8110    | 0.8496 | 0.8299 | 0.9938   | 0.0062 |
| 0.0076        | 4.0   | 3096 | 0.0196          | 0.8353    | 0.8399 | 0.8376 | 0.9942   | 0.0058 |
| 0.0061        | 5.0   | 3870 | 0.0218          | 0.8097    | 0.8573 | 0.8328 | 0.9938   | 0.0062 |


### Framework versions

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