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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224 |
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tags: |
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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-base-patch16-224-finetuned-brain-tumor-classification |
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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: imagefolder |
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type: imagefolder |
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config: default |
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split: validation |
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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: 0.8905191873589164 |
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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-base-patch16-224-finetuned-brain-tumor-classification |
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co./google/vit-base-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4348 |
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- Accuracy: 0.8905 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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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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| 3.1659 | 0.9897 | 48 | 2.4060 | 0.4086 | |
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| 1.8381 | 2.0 | 97 | 1.2904 | 0.6772 | |
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| 1.0781 | 2.9897 | 145 | 0.9211 | 0.7573 | |
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| 0.8049 | 4.0 | 194 | 0.7274 | 0.8036 | |
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| 0.6091 | 4.9897 | 242 | 0.6427 | 0.8330 | |
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| 0.4985 | 6.0 | 291 | 0.5519 | 0.8510 | |
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| 0.4077 | 6.9897 | 339 | 0.4921 | 0.8792 | |
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| 0.3583 | 8.0 | 388 | 0.4756 | 0.8826 | |
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| 0.3292 | 8.9897 | 436 | 0.4472 | 0.8883 | |
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| 0.338 | 9.8969 | 480 | 0.4348 | 0.8905 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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