---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: amiguel/mri_classifier
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# amiguel/mri_classifier

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:
- Train Loss: 0.0075
- Validation Loss: 0.0023
- Train Accuracy: 1.0
- Epoch: 14

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 3e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.1501     | 0.0619          | 0.9845         | 0     |
| 0.0524     | 0.0825          | 0.9733         | 1     |
| 0.0324     | 0.1416          | 0.9494         | 2     |
| 0.0243     | 0.0327          | 0.9887         | 3     |
| 0.0258     | 0.0095          | 0.9986         | 4     |
| 0.0166     | 0.0069          | 0.9986         | 5     |
| 0.0342     | 0.0126          | 0.9958         | 6     |
| 0.0131     | 0.0057          | 0.9986         | 7     |
| 0.0120     | 0.0037          | 0.9986         | 8     |
| 0.0163     | 0.0055          | 0.9972         | 9     |
| 0.0083     | 0.0018          | 1.0            | 10    |
| 0.0128     | 0.0027          | 0.9986         | 11    |
| 0.0070     | 0.0020          | 1.0            | 12    |
| 0.0083     | 0.0014          | 1.0            | 13    |
| 0.0075     | 0.0023          | 1.0            | 14    |


### Framework versions

- Transformers 4.42.4
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1