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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: leopuv/cats_vs_dogs_classifier
results: []
datasets:
- lewtun/dog_food
---
<!-- 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. -->
# leopuv/cats_vs_dogs_classifier
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: 0.0285
- Train Accuracy: 0.9865
- Validation Loss: 0.0340
- Validation Accuracy: 0.9865
- 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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 80000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
### Training results
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.1739 | 0.9715 | 0.0787 | 0.9715 | 0 |
| 0.0744 | 0.984 | 0.0432 | 0.9840 | 1 |
| 0.0543 | 0.9895 | 0.0365 | 0.9895 | 2 |
| 0.0420 | 0.9885 | 0.0346 | 0.9885 | 3 |
| 0.0402 | 0.9855 | 0.0414 | 0.9855 | 4 |
| 0.0378 | 0.9885 | 0.0307 | 0.9885 | 5 |
| 0.0306 | 0.9855 | 0.0375 | 0.9855 | 6 |
| 0.0343 | 0.987 | 0.0402 | 0.9870 | 7 |
| 0.0283 | 0.9875 | 0.0381 | 0.9875 | 8 |
| 0.0285 | 0.9865 | 0.0340 | 0.9865 | 9 |
### Framework versions
- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.13.1
- Tokenizers 0.13.3 |