vit_food101 / README.md
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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: saffin/vit_food101
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. -->
# saffin/vit_food101
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: 0.3672
- Validation Loss: 0.3778
- Train Accuracy: 0.899
- Epoch: 4
## 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': 20000, '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 | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 2.7897 | 1.6408 | 0.818 | 0 |
| 1.2215 | 0.8019 | 0.895 | 1 |
| 0.6917 | 0.5261 | 0.898 | 2 |
| 0.4765 | 0.4082 | 0.905 | 3 |
| 0.3672 | 0.3778 | 0.899 | 4 |
### Framework versions
- Transformers 4.31.0
- TensorFlow 2.8.0
- Datasets 2.18.0
- Tokenizers 0.13.3