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---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: Entrnal_5class_agumm_last_newV7_model
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. -->
# Entrnal_5class_agumm_last_newV7_model
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: 0.0959
- Train Accuracy: 0.9365
- Train Top-3-accuracy: 0.9913
- Validation Loss: 0.3424
- Validation Accuracy: 0.9390
- Validation Top-3-accuracy: 0.9917
- 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 620, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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 | Train Top-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 1.1895 | 0.4833 | 0.8342 | 0.8125 | 0.6525 | 0.9200 | 0 |
| 0.5511 | 0.7329 | 0.9448 | 0.4587 | 0.7829 | 0.9601 | 1 |
| 0.3174 | 0.8164 | 0.9677 | 0.3909 | 0.8395 | 0.9735 | 2 |
| 0.2299 | 0.8576 | 0.9772 | 0.3711 | 0.8709 | 0.9802 | 3 |
| 0.1699 | 0.8824 | 0.9824 | 0.3564 | 0.8920 | 0.9842 | 4 |
| 0.1344 | 0.9003 | 0.9856 | 0.3389 | 0.9073 | 0.9865 | 5 |
| 0.1187 | 0.9131 | 0.9875 | 0.3391 | 0.9183 | 0.9884 | 6 |
| 0.1060 | 0.9229 | 0.9891 | 0.3424 | 0.9267 | 0.9898 | 7 |
| 0.0992 | 0.9304 | 0.9903 | 0.3426 | 0.9334 | 0.9908 | 8 |
| 0.0959 | 0.9365 | 0.9913 | 0.3424 | 0.9390 | 0.9917 | 9 |
### Framework versions
- Transformers 4.44.2
- TensorFlow 2.15.1
- Datasets 3.0.0
- Tokenizers 0.19.1
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