transformers tf vit image-classification generated_from_keras_callback base_model:google/vit-base-patch32-384 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: google/vit-base-patch32-384
tags:
- generated_from_keras_callback
model-index:
- name: nj1867/roof_classification_new_dataset_4_march
  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. -->

# nj1867/roof_classification_new_dataset_4_march

This model is a fine-tuned version of [google/vit-base-patch32-384](https://huggingface.co/google/vit-base-patch32-384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1523
- Validation Loss: 0.7698
- Train Accuracy: 0.8375
- Epoch: 19

## 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 7440, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.0001}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 4.2343     | 4.0917          | 0.0437         | 0     |
| 3.7984     | 3.8481          | 0.1313         | 1     |
| 3.3245     | 3.5615          | 0.1062         | 2     |
| 2.8352     | 3.1190          | 0.3            | 3     |
| 2.3077     | 2.7024          | 0.4            | 4     |
| 1.8445     | 2.4423          | 0.4625         | 5     |
| 1.4533     | 2.0483          | 0.5813         | 6     |
| 1.1535     | 1.8203          | 0.65           | 7     |
| 0.9074     | 1.4581          | 0.725          | 8     |
| 0.7190     | 1.3655          | 0.7812         | 9     |
| 0.5880     | 1.2685          | 0.7875         | 10    |
| 0.4729     | 1.2005          | 0.7875         | 11    |
| 0.4004     | 0.9699          | 0.825          | 12    |
| 0.3349     | 0.9435          | 0.8313         | 13    |
| 0.2789     | 0.8993          | 0.8438         | 14    |
| 0.2179     | 0.8071          | 0.8625         | 15    |
| 0.2061     | 0.7852          | 0.8812         | 16    |
| 0.2124     | 0.7664          | 0.8625         | 17    |
| 0.1623     | 0.8276          | 0.8562         | 18    |
| 0.1523     | 0.7698          | 0.8375         | 19    |


### Framework versions

- Transformers 4.38.2
- TensorFlow 2.13.1
- Datasets 2.18.0
- Tokenizers 0.15.2
