---
license: apache-2.0
base_model: google/vit-base-patch32-384
tags:
- generated_from_keras_callback
model-index:
- name: Prahas10/roof_classification
  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_classification

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: 0.0162
- Validation Loss: 0.2163
- Train Accuracy: 0.8916
- Epoch: 24

## 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': 4825, '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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 2.5019     | 2.0795          | 0.3735         | 0     |
| 1.7660     | 1.7259          | 0.4458         | 1     |
| 1.0922     | 1.0990          | 0.7590         | 2     |
| 0.6402     | 0.8232          | 0.8193         | 3     |
| 0.4725     | 0.6107          | 0.8675         | 4     |
| 0.2674     | 0.4986          | 0.9157         | 5     |
| 0.1794     | 0.5000          | 0.9157         | 6     |
| 0.2579     | 0.7721          | 0.7349         | 7     |
| 0.1269     | 0.3304          | 0.8675         | 8     |
| 0.0970     | 0.2980          | 0.8795         | 9     |
| 0.1181     | 0.4988          | 0.8193         | 10    |
| 0.1241     | 0.2899          | 0.8795         | 11    |
| 0.2311     | 0.4113          | 0.8795         | 12    |
| 0.0753     | 0.2964          | 0.9157         | 13    |
| 0.0637     | 0.4096          | 0.8675         | 14    |
| 0.0540     | 0.3032          | 0.9036         | 15    |
| 0.0334     | 0.2694          | 0.9277         | 16    |
| 0.0212     | 0.1793          | 0.9639         | 17    |
| 0.0241     | 0.3772          | 0.8554         | 18    |
| 0.0471     | 0.5727          | 0.8675         | 19    |
| 0.0652     | 0.3167          | 0.8916         | 20    |
| 0.0281     | 0.2690          | 0.9036         | 21    |
| 0.0478     | 0.2169          | 0.9277         | 22    |
| 0.0193     | 0.2091          | 0.9880         | 23    |
| 0.0162     | 0.2163          | 0.8916         | 24    |


### Framework versions

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