| --- |
| 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 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.44.2 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.0 |
| - Tokenizers 0.19.1 |
|
|
