| --- |
| license: apache-2.0 |
| base_model: microsoft/beit-base-patch16-224-pt22k-ft22k |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: hushem_40x_beit_base_f3 |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: test |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.8837209302325582 |
| --- |
| |
| <!-- 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. --> |
|
|
| # hushem_40x_beit_base_f3 |
|
|
| This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9422 |
| - Accuracy: 0.8837 |
|
|
| ## 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: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.0594 | 1.0 | 108 | 0.4441 | 0.8372 | |
| | 0.0595 | 2.0 | 217 | 0.8725 | 0.8605 | |
| | 0.0173 | 3.0 | 325 | 0.5866 | 0.9070 | |
| | 0.0084 | 4.0 | 434 | 0.6360 | 0.8605 | |
| | 0.0005 | 5.0 | 542 | 0.6191 | 0.8837 | |
| | 0.0008 | 6.0 | 651 | 0.6635 | 0.9070 | |
| | 0.0008 | 7.0 | 759 | 0.8772 | 0.8837 | |
| | 0.0001 | 8.0 | 868 | 0.8012 | 0.9070 | |
| | 0.0 | 9.0 | 976 | 0.9139 | 0.8837 | |
| | 0.0001 | 9.95 | 1080 | 0.9422 | 0.8837 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.35.0 |
| - Pytorch 2.1.0+cu118 |
| - Datasets 2.14.6 |
| - Tokenizers 0.14.1 |
|
|
