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--- |
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license: apache-2.0 |
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base_model: google/vit-large-patch32-224-in21k |
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tags: |
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- image-classification |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-large-brain-xray |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: sartajbhuvaji/Brain-Tumor-Classification |
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type: imagefolder |
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config: default |
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split: Testing |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7741116751269036 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# vit-large-brain-xray |
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This model is a fine-tuned version of [google/vit-large-patch32-224-in21k](https://huggingface.co/google/vit-large-patch32-224-in21k) on the sartajbhuvaji/Brain-Tumor-Classification dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9050 |
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- Accuracy: 0.7741 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 4 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 0.352 | 0.5556 | 100 | 1.2267 | 0.6294 | |
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| 0.1612 | 1.1111 | 200 | 1.0895 | 0.7538 | |
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| 0.0473 | 1.6667 | 300 | 0.9050 | 0.7741 | |
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| 0.0525 | 2.2222 | 400 | 1.0663 | 0.7690 | |
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| 0.0123 | 2.7778 | 500 | 1.2450 | 0.7462 | |
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| 0.0066 | 3.3333 | 600 | 1.1283 | 0.7817 | |
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| 0.0126 | 3.8889 | 700 | 1.1717 | 0.7843 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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