---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: amiguel/cmm560_surface_corrosion_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/cmm560_surface_corrosion_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: 0.0340
- Validation Loss: 0.0958
- Train Accuracy: 0.9731
- 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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.3646     | 0.2100          | 0.8879         | 0     |
| 0.1923     | 0.1380          | 0.9731         | 1     |
| 0.1445     | 0.1082          | 0.9731         | 2     |
| 0.1066     | 0.0847          | 0.9776         | 3     |
| 0.0779     | 0.0656          | 0.9731         | 4     |
| 0.0758     | 0.0658          | 0.9776         | 5     |
| 0.0892     | 0.0499          | 0.9821         | 6     |
| 0.0701     | 0.1073          | 0.9731         | 7     |
| 0.0656     | 0.0655          | 0.9686         | 8     |
| 0.0527     | 0.0578          | 0.9776         | 9     |
| 0.0731     | 0.1136          | 0.9462         | 10    |
| 0.0508     | 0.0830          | 0.9641         | 11    |
| 0.0453     | 0.0762          | 0.9731         | 12    |
| 0.0541     | 0.0821          | 0.9686         | 13    |
| 0.0340     | 0.0958          | 0.9731         | 14    |


### Framework versions

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