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---
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
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