---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_keras_callback
model-index:
- name: TirathP/vit-base-patch16-224-finetuned-customData
  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. -->

# TirathP/vit-base-patch16-224-finetuned-customData

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.2775
- Validation Loss: 0.3297
- Validation Accuracy: 0.8571
- 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': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:---------------:|:-------------------:|:-----:|
| 1.1397     | 1.0223          | 0.5714              | 0     |
| 0.8312     | 0.8338          | 0.5714              | 1     |
| 0.7131     | 0.7099          | 0.5714              | 2     |
| 0.5754     | 0.6120          | 0.7143              | 3     |
| 0.4804     | 0.5374          | 0.7143              | 4     |
| 0.3934     | 0.4630          | 0.8571              | 5     |
| 0.4258     | 0.3979          | 0.8571              | 6     |
| 0.3739     | 0.3455          | 1.0                 | 7     |
| 0.3143     | 0.2909          | 1.0                 | 8     |
| 0.3113     | 0.2572          | 0.8571              | 9     |
| 0.3327     | 0.2623          | 0.8571              | 10    |
| 0.2227     | 0.2993          | 0.8571              | 11    |
| 0.2860     | 0.3299          | 0.8571              | 12    |
| 0.2081     | 0.3553          | 0.8571              | 13    |
| 0.2243     | 0.3360          | 0.8571              | 14    |
| 0.2246     | 0.2942          | 0.8571              | 15    |
| 0.2570     | 0.2131          | 0.8571              | 16    |
| 0.3173     | 0.1850          | 0.8571              | 17    |
| 0.1572     | 0.2134          | 0.8571              | 18    |
| 0.2775     | 0.3297          | 0.8571              | 19    |


### Framework versions

- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.14.4
- Tokenizers 0.13.3