---
library_name: transformers
base_model: gerbejon/webpage_labeling_classifier
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: webpage_labeling_classifier
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9416466826538769
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# webpage_labeling_classifier

This model is a fine-tuned version of [gerbejon/webpage_labeling_classifier](https://huggingface.co/gerbejon/webpage_labeling_classifier) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1555
- Accuracy: 0.9416

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.2002        | 0.9968  | 78   | 0.1917          | 0.9281   |
| 0.2191        | 1.9936  | 156  | 0.2132          | 0.9097   |
| 0.2067        | 2.9904  | 234  | 0.2522          | 0.9065   |
| 0.1751        | 4.0     | 313  | 0.1931          | 0.9217   |
| 0.1346        | 4.9968  | 391  | 0.1933          | 0.9241   |
| 0.1448        | 5.9936  | 469  | 0.1816          | 0.9313   |
| 0.1389        | 6.9904  | 547  | 0.2027          | 0.9209   |
| 0.1387        | 8.0     | 626  | 0.1696          | 0.9384   |
| 0.1234        | 8.9968  | 704  | 0.1758          | 0.9345   |
| 0.1196        | 9.9936  | 782  | 0.1848          | 0.9305   |
| 0.1213        | 10.9904 | 860  | 0.1769          | 0.9400   |
| 0.1287        | 12.0    | 939  | 0.1421          | 0.9488   |
| 0.117         | 12.9968 | 1017 | 0.2046          | 0.9241   |
| 0.1433        | 13.9936 | 1095 | 0.1769          | 0.9369   |
| 0.0988        | 14.9904 | 1173 | 0.1494          | 0.9496   |
| 0.1136        | 16.0    | 1252 | 0.1571          | 0.9424   |
| 0.086         | 16.9968 | 1330 | 0.1712          | 0.9384   |
| 0.089         | 17.9936 | 1408 | 0.1437          | 0.9440   |
| 0.0991        | 18.9904 | 1486 | 0.1510          | 0.9448   |
| 0.0824        | 19.9361 | 1560 | 0.1555          | 0.9416   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1