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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Brain-Tumor-Classification
results: []
---
<!-- 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. -->
# Brain-Tumor-Classification
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0872
- Accuracy: 0.9758
## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 16
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2074 | 1.0 | 44 | 0.8060 | 0.8128 |
| 0.4897 | 2.0 | 88 | 0.3008 | 0.9274 |
| 0.2462 | 3.0 | 132 | 0.2464 | 0.9331 |
| 0.1937 | 4.0 | 176 | 0.1918 | 0.9502 |
| 0.1523 | 5.0 | 220 | 0.1699 | 0.9502 |
| 0.1371 | 6.0 | 264 | 0.1372 | 0.9644 |
| 0.1104 | 7.0 | 308 | 0.1121 | 0.9708 |
| 0.1097 | 8.0 | 352 | 0.1220 | 0.9651 |
| 0.1015 | 9.0 | 396 | 0.1053 | 0.9737 |
| 0.0841 | 10.0 | 440 | 0.1142 | 0.9708 |
| 0.0839 | 11.0 | 484 | 0.1073 | 0.9708 |
| 0.0771 | 12.0 | 528 | 0.1156 | 0.9665 |
| 0.074 | 13.0 | 572 | 0.1203 | 0.9644 |
| 0.0652 | 14.0 | 616 | 0.0706 | 0.9858 |
| 0.0694 | 15.0 | 660 | 0.0984 | 0.9744 |
| 0.0596 | 16.0 | 704 | 0.0872 | 0.9758 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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