---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- text-classification
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1922
- Accuracy: 0.9640
- Precision: 0.926
- Recall: 0.7928
- F1: 0.8542

## 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: 5e-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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.1639        | 1.0   | 1097 | 0.1940          | 0.9389   | 0.8762    | 0.6301 | 0.7331 |
| 0.1069        | 2.0   | 2194 | 0.1561          | 0.9608   | 0.9478    | 0.7466 | 0.8352 |
| 0.0897        | 3.0   | 3291 | 0.1922          | 0.9640   | 0.926     | 0.7928 | 0.8542 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Tokenizers 0.19.1