---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: BERT_Text_classification_clean
  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_Text_classification_clean

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: 0.5208
- Accuracy: 0.9028
- F1: 0.8924
- Precision: 0.8990
- Recall: 0.8925

## 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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.6803        | 0.24  | 50   | 1.2419          | 0.7613   | 0.7374 | 0.7493    | 0.7460 |
| 0.6367        | 0.48  | 100  | 0.4523          | 0.8437   | 0.8358 | 0.8377    | 0.8357 |
| 0.2756        | 0.71  | 150  | 0.4543          | 0.8625   | 0.8550 | 0.8576    | 0.8544 |
| 0.2569        | 0.95  | 200  | 0.4377          | 0.8845   | 0.8715 | 0.8791    | 0.8727 |
| 0.1044        | 1.19  | 250  | 0.5032          | 0.8903   | 0.8793 | 0.8828    | 0.8795 |
| 0.0745        | 1.43  | 300  | 0.5342          | 0.8912   | 0.8791 | 0.8881    | 0.8798 |
| 0.0906        | 1.67  | 350  | 0.5484          | 0.8992   | 0.8880 | 0.8956    | 0.8886 |
| 0.0839        | 1.9   | 400  | 0.5337          | 0.8939   | 0.8827 | 0.8858    | 0.8830 |
| 0.0474        | 2.14  | 450  | 0.5237          | 0.8983   | 0.8876 | 0.8938    | 0.8879 |
| 0.0346        | 2.38  | 500  | 0.4822          | 0.9037   | 0.8939 | 0.9005    | 0.8939 |
| 0.0243        | 2.62  | 550  | 0.5014          | 0.9019   | 0.8916 | 0.8964    | 0.8917 |
| 0.0181        | 2.86  | 600  | 0.5208          | 0.9028   | 0.8924 | 0.8990    | 0.8925 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2