---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-bert-1k
  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. -->

# finetuned-bert-1k

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an publically available ham and spam email dataset.
It achieves the following results on the training set:
- Loss: 0.0192
- Accuracy: 0.9970

## 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: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3058        | 1.0   | 63   | 0.0904          | 0.9782   |
| 0.0876        | 2.0   | 126  | 0.0659          | 0.9841   |
| 0.031         | 3.0   | 189  | 0.0192          | 0.9970   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3