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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-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-brain-tumour-v2 |
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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: essam24/brain-tumour-v2 |
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type: imagefolder |
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config: default |
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split: test |
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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: 0.8703703703703703 |
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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-brain-tumour-v2 |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the essam24/brain-tumour-v2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5359 |
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- Accuracy: 0.8704 |
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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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| 0.1236 | 0.5128 | 100 | 0.5990 | 0.8481 | |
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| 0.1695 | 1.0256 | 200 | 0.5359 | 0.8704 | |
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| 0.0186 | 1.5385 | 300 | 0.5705 | 0.8975 | |
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| 0.0368 | 2.0513 | 400 | 0.6136 | 0.8975 | |
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| 0.0036 | 2.5641 | 500 | 0.6122 | 0.9012 | |
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| 0.0029 | 3.0769 | 600 | 0.6067 | 0.9025 | |
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| 0.0027 | 3.5897 | 700 | 0.6449 | 0.9025 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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