---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: website_classification
  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. -->

# website_classification

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2909
- Accuracy: 0.9362
- F1: 0.9354
- Precision: 0.9380
- Recall: 0.9362

## 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 2.4251        | 1.0   | 71   | 1.8259          | 0.8688   | 0.8615 | 0.8645    | 0.8688 |
| 1.34          | 2.0   | 142  | 0.8796          | 0.9078   | 0.8978 | 0.8929    | 0.9078 |
| 0.6342        | 3.0   | 213  | 0.5158          | 0.9113   | 0.9052 | 0.9078    | 0.9113 |
| 0.3265        | 4.0   | 284  | 0.3381          | 0.9326   | 0.9268 | 0.9254    | 0.9326 |
| 0.165         | 5.0   | 355  | 0.3140          | 0.9255   | 0.9201 | 0.9215    | 0.9255 |
| 0.0939        | 6.0   | 426  | 0.2805          | 0.9291   | 0.9252 | 0.9279    | 0.9291 |
| 0.0568        | 7.0   | 497  | 0.2679          | 0.9362   | 0.9308 | 0.9290    | 0.9362 |
| 0.0337        | 8.0   | 568  | 0.2728          | 0.9291   | 0.9227 | 0.9217    | 0.9291 |
| 0.0216        | 9.0   | 639  | 0.2531          | 0.9362   | 0.9355 | 0.9379    | 0.9362 |
| 0.0141        | 10.0  | 710  | 0.2741          | 0.9326   | 0.9325 | 0.9362    | 0.9326 |
| 0.0108        | 11.0  | 781  | 0.2749          | 0.9291   | 0.9278 | 0.9302    | 0.9291 |
| 0.0086        | 12.0  | 852  | 0.2680          | 0.9291   | 0.9278 | 0.9302    | 0.9291 |
| 0.0074        | 13.0  | 923  | 0.2688          | 0.9326   | 0.9303 | 0.9317    | 0.9326 |
| 0.0065        | 14.0  | 994  | 0.2736          | 0.9362   | 0.9354 | 0.9380    | 0.9362 |
| 0.0057        | 15.0  | 1065 | 0.2780          | 0.9362   | 0.9354 | 0.9380    | 0.9362 |
| 0.0051        | 16.0  | 1136 | 0.2730          | 0.9362   | 0.9323 | 0.9321    | 0.9362 |
| 0.0047        | 17.0  | 1207 | 0.2793          | 0.9362   | 0.9344 | 0.9361    | 0.9362 |
| 0.0044        | 18.0  | 1278 | 0.2784          | 0.9362   | 0.9354 | 0.9380    | 0.9362 |
| 0.0039        | 19.0  | 1349 | 0.2799          | 0.9362   | 0.9354 | 0.9380    | 0.9362 |
| 0.0036        | 20.0  | 1420 | 0.2820          | 0.9362   | 0.9354 | 0.9380    | 0.9362 |
| 0.0035        | 21.0  | 1491 | 0.2836          | 0.9362   | 0.9354 | 0.9380    | 0.9362 |
| 0.0032        | 22.0  | 1562 | 0.2851          | 0.9362   | 0.9354 | 0.9380    | 0.9362 |
| 0.0032        | 23.0  | 1633 | 0.2863          | 0.9362   | 0.9354 | 0.9380    | 0.9362 |
| 0.0031        | 24.0  | 1704 | 0.2901          | 0.9362   | 0.9354 | 0.9380    | 0.9362 |
| 0.0029        | 25.0  | 1775 | 0.2896          | 0.9362   | 0.9354 | 0.9380    | 0.9362 |
| 0.0028        | 26.0  | 1846 | 0.2892          | 0.9362   | 0.9354 | 0.9380    | 0.9362 |
| 0.0027        | 27.0  | 1917 | 0.2891          | 0.9362   | 0.9354 | 0.9380    | 0.9362 |
| 0.0026        | 28.0  | 1988 | 0.2898          | 0.9362   | 0.9354 | 0.9380    | 0.9362 |
| 0.0027        | 29.0  | 2059 | 0.2909          | 0.9362   | 0.9354 | 0.9380    | 0.9362 |
| 0.0026        | 30.0  | 2130 | 0.2909          | 0.9362   | 0.9354 | 0.9380    | 0.9362 |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2