---
license: apache-2.0
base_model: google/vit-base-patch16-384
tags:
- generated_from_keras_callback
model-index:
- name: Prahas10/roof-sample
  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. -->

# Prahas10/roof-sample

This model is a fine-tuned version of [google/vit-base-patch16-384](https://huggingface.co/google/vit-base-patch16-384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0745
- Validation Loss: 0.3751
- Train Accuracy: 0.9036
- Epoch: 9

## 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': 1930, '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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 2.4213     | 2.1960          | 0.3976         | 0     |
| 1.4980     | 1.6884          | 0.5542         | 1     |
| 0.8368     | 1.2810          | 0.6386         | 2     |
| 0.4281     | 1.0031          | 0.7108         | 3     |
| 0.2528     | 0.9361          | 0.7108         | 4     |
| 0.1838     | 1.1263          | 0.6145         | 5     |
| 0.4895     | 0.7904          | 0.8072         | 6     |
| 0.1850     | 0.5048          | 0.9277         | 7     |
| 0.0928     | 0.3762          | 0.9277         | 8     |
| 0.0745     | 0.3751          | 0.9036         | 9     |


### Framework versions

- Transformers 4.38.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.2