transformers tf vit image-classification generated_from_keras_callback base_model:google/vit-base-patch16-224-in21k license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: nj1867/roof_classification_35
  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_35

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: 0.2855
- Validation Loss: 0.5466
- Train Accuracy: 0.8413
- 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': 3e-05, 'decay_steps': 42240, '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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 3.4052     | 3.2118          | 0.3472         | 0     |
| 2.9771     | 2.8091          | 0.5122         | 1     |
| 2.5834     | 2.4653          | 0.6379         | 2     |
| 2.2565     | 2.2264          | 0.6794         | 3     |
| 1.9808     | 2.0136          | 0.6869         | 4     |
| 1.7365     | 1.7525          | 0.7934         | 5     |
| 1.5394     | 1.6366          | 0.7668         | 6     |
| 1.3621     | 1.5575          | 0.7519         | 7     |
| 1.1855     | 1.4560          | 0.7412         | 8     |
| 1.0507     | 1.0795          | 0.8477         | 9     |
| 0.9409     | 1.0760          | 0.8413         | 10    |
| 0.8775     | 1.1174          | 0.7827         | 11    |
| 0.7837     | 1.2030          | 0.7487         | 12    |
| 0.6933     | 0.8608          | 0.8413         | 13    |
| 0.6005     | 0.8497          | 0.8264         | 14    |
| 0.5648     | 0.7881          | 0.8381         | 15    |
| 0.5482     | 0.8070          | 0.8083         | 16    |
| 0.4783     | 0.6537          | 0.8530         | 17    |
| 0.4632     | 0.7237          | 0.8232         | 18    |
| 0.4047     | 0.5131          | 0.8818         | 19    |
| 0.3885     | 0.4548          | 0.9042         | 20    |
| 0.3793     | 0.5766          | 0.8584         | 21    |
| 0.3670     | 0.6578          | 0.8147         | 22    |
| 0.3202     | 0.8783          | 0.7551         | 23    |
| 0.3094     | 0.4762          | 0.8733         | 24    |
| 0.3193     | 0.5481          | 0.8498         | 25    |
| 0.3190     | 0.4589          | 0.8711         | 26    |
| 0.2742     | 0.4616          | 0.8637         | 27    |
| 0.2583     | 0.4354          | 0.8807         | 28    |
| 0.2855     | 0.5466          | 0.8413         | 29    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.14.0
- Datasets 2.15.0
- Tokenizers 0.15.0
