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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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