| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: beit-large-patch16-224-finetuned-LungCancer-Classification-LC25000-AH-40-30-30 |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: Augmented-Final |
| split: train |
| args: Augmented-Final |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9995570321151717 |
| --- |
| |
| <!-- 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. --> |
|
|
| # beit-large-patch16-224-finetuned-LungCancer-Classification-LC25000-AH-40-30-30 |
|
|
| This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0011 |
| - Accuracy: 0.9996 |
|
|
| ## 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: 0.5 |
| - num_epochs: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.0508 | 0.99 | 93 | 0.0634 | 0.9756 | |
| | 0.0909 | 1.99 | 187 | 0.0222 | 0.9911 | |
| | 0.0641 | 3.0 | 281 | 0.0228 | 0.9914 | |
| | 0.0717 | 4.0 | 375 | 0.0050 | 0.9982 | |
| | 0.0012 | 4.96 | 465 | 0.0011 | 0.9996 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.30.2 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.13.1 |
| - Tokenizers 0.13.3 |
|
|
