| --- |
| 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 |
| |
