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---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Imene/vit-base-patch16-384-wi5
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. -->
# Imene/vit-base-patch16-384-wi5
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: 0.4102
- Train Accuracy: 0.9755
- Train Top-3-accuracy: 0.9960
- Validation Loss: 1.9021
- Validation Accuracy: 0.4912
- Validation Top-3-accuracy: 0.7302
- Epoch: 8
## 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: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 3180, '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}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16
### Training results
| Train Loss | Train Accuracy | Train Top-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 4.2945 | 0.0568 | 0.1328 | 3.6233 | 0.1387 | 0.2916 | 0 |
| 3.1234 | 0.2437 | 0.4585 | 2.8657 | 0.3041 | 0.5330 | 1 |
| 2.4383 | 0.4182 | 0.6638 | 2.5499 | 0.3534 | 0.6048 | 2 |
| 1.9258 | 0.5698 | 0.7913 | 2.3046 | 0.4202 | 0.6583 | 3 |
| 1.4919 | 0.6963 | 0.8758 | 2.1349 | 0.4553 | 0.6784 | 4 |
| 1.1127 | 0.7992 | 0.9395 | 2.0878 | 0.4595 | 0.6809 | 5 |
| 0.8092 | 0.8889 | 0.9720 | 1.9460 | 0.4962 | 0.7210 | 6 |
| 0.5794 | 0.9419 | 0.9883 | 1.9478 | 0.4979 | 0.7201 | 7 |
| 0.4102 | 0.9755 | 0.9960 | 1.9021 | 0.4912 | 0.7302 | 8 |
### Framework versions
- Transformers 4.21.3
- TensorFlow 2.8.2
- Datasets 2.4.0
- Tokenizers 0.12.1
|