---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bert-base-uncased-finetuned-spam-real
  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-uncased-finetuned-spam-real

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: 0.0342
- Accuracy: 0.9942
- F1: 0.9945
- Precision: 0.9941
- Recall: 0.9949

## 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: 3.8529031222986405e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 15
- 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 | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.0418        | 1.0   | 4173  | 0.0471          | 0.9877   | 0.9882 | 0.9950    | 0.9815 |
| 0.0186        | 2.0   | 8346  | 0.0394          | 0.9935   | 0.9938 | 0.9938    | 0.9938 |
| 0.0096        | 3.0   | 12519 | 0.0342          | 0.9942   | 0.9945 | 0.9941    | 0.9949 |
| 0.0059        | 4.0   | 16692 | 0.0421          | 0.9934   | 0.9937 | 0.9958    | 0.9917 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2