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

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: 0.1015
- Validation Loss: 0.3231
- Train Accuracy: 0.9083
- Epoch: 29

## 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': 4e-05, 'decay_steps': 138270, '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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 3.8367     | 2.9703          | 0.4403         | 0     |
| 1.3092     | 1.6169          | 0.7093         | 1     |
| 0.4529     | 1.4414          | 0.7112         | 2     |
| 0.2229     | 0.8445          | 0.8368         | 3     |
| 0.1451     | 0.7074          | 0.8556         | 4     |
| 0.1053     | 0.8585          | 0.7992         | 5     |
| 0.1175     | 1.0721          | 0.7389         | 6     |
| 0.1388     | 0.5802          | 0.8542         | 7     |
| 0.0647     | 0.3764          | 0.9083         | 8     |
| 0.1049     | 1.0484          | 0.7366         | 9     |
| 0.0740     | 0.6191          | 0.8321         | 10    |
| 0.0816     | 0.6273          | 0.8283         | 11    |
| 0.0981     | 0.2901          | 0.9172         | 12    |
| 0.0614     | 0.5081          | 0.8523         | 13    |
| 0.0548     | 0.4983          | 0.8612         | 14    |
| 0.0652     | 0.8008          | 0.7850         | 15    |
| 0.0857     | 0.5845          | 0.8415         | 16    |
| 0.0847     | 0.6887          | 0.8184         | 17    |
| 0.0645     | 0.6104          | 0.8405         | 18    |
| 0.0891     | 0.4770          | 0.8532         | 19    |
| 0.0532     | 0.5074          | 0.8500         | 20    |
| 0.0483     | 0.8208          | 0.7850         | 21    |
| 0.0498     | 0.2679          | 0.9083         | 22    |
| 0.0406     | 0.3261          | 0.9036         | 23    |
| 0.0578     | 0.6373          | 0.8340         | 24    |
| 0.1010     | 0.5037          | 0.8481         | 25    |
| 0.0583     | 0.2993          | 0.8984         | 26    |
| 0.0398     | 0.1538          | 0.9492         | 27    |
| 0.0492     | 0.4397          | 0.8641         | 28    |
| 0.1015     | 0.3231          | 0.9083         | 29    |


### Framework versions

- Transformers 4.41.1
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1