|
--- |
|
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 |
