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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: alzheimer_mri_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. -->
# alzheimer_mri_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: 0.3404
- Accuracy: 0.8770
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 128 | 0.8345 | 0.5996 |
| No log | 2.0 | 256 | 0.8245 | 0.6309 |
| No log | 3.0 | 384 | 0.7492 | 0.6543 |
| 0.8188 | 4.0 | 512 | 0.7173 | 0.6777 |
| 0.8188 | 5.0 | 640 | 0.6625 | 0.7168 |
| 0.8188 | 6.0 | 768 | 0.6182 | 0.7373 |
| 0.8188 | 7.0 | 896 | 0.5058 | 0.8027 |
| 0.5344 | 8.0 | 1024 | 0.5567 | 0.7764 |
| 0.5344 | 9.0 | 1152 | 0.4702 | 0.8193 |
| 0.5344 | 10.0 | 1280 | 0.4502 | 0.8242 |
| 0.5344 | 11.0 | 1408 | 0.4024 | 0.8408 |
| 0.3356 | 12.0 | 1536 | 0.4263 | 0.8516 |
| 0.3356 | 13.0 | 1664 | 0.3782 | 0.8535 |
| 0.3356 | 14.0 | 1792 | 0.3378 | 0.8604 |
| 0.3356 | 15.0 | 1920 | 0.3570 | 0.8701 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|