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---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Imene/vit-base-patch16-224-wi2
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-patch16-224-wi2
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: 0.3098
- Train Accuracy: 0.9821
- Train Top-5-accuracy: 0.9971
- Validation Loss: 3.0737
- Validation Accuracy: 0.2491
- Validation Top-5-accuracy: 0.4476
- 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: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0003, 'decay_steps': 1750, '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': 0.001}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16
### Training results
| Train Loss | Train Accuracy | Train Top-5-accuracy | Validation Loss | Validation Accuracy | Validation Top-5-accuracy | Epoch |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 4.4859 | 0.0195 | 0.0579 | 4.2995 | 0.0368 | 0.0865 | 0 |
| 4.1729 | 0.0355 | 0.0987 | 4.0916 | 0.0472 | 0.1266 | 1 |
| 3.9541 | 0.0666 | 0.1641 | 3.8050 | 0.0781 | 0.2035 | 2 |
| 3.5823 | 0.1247 | 0.2615 | 3.4015 | 0.1429 | 0.2950 | 3 |
| 3.0156 | 0.1913 | 0.3987 | 3.0598 | 0.1880 | 0.3916 | 4 |
| 2.4618 | 0.3077 | 0.5572 | 2.9869 | 0.2056 | 0.4129 | 5 |
| 1.8979 | 0.4541 | 0.7165 | 2.9507 | 0.2298 | 0.4425 | 6 |
| 1.2075 | 0.6914 | 0.8886 | 3.0106 | 0.2394 | 0.4425 | 7 |
| 0.6026 | 0.9097 | 0.9810 | 3.0739 | 0.2428 | 0.4413 | 8 |
| 0.3098 | 0.9821 | 0.9971 | 3.0737 | 0.2491 | 0.4476 | 9 |
### Framework versions
- Transformers 4.21.3
- TensorFlow 2.8.2
- Datasets 2.4.0
- Tokenizers 0.12.1
|