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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_eyes_data_6_true_agoiment211_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_eyes_data_6_true_agoiment211_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: 0.1455
- Train Accuracy: 0.9282
- Train Top-3-accuracy: 0.9908
- Validation Loss: 0.3319
- Validation Accuracy: 0.9322
- Validation Top-3-accuracy: 0.9914
- Epoch: 6
## 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': 434, '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 |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 1.1623 | 0.5608 | 0.8521 | 0.7419 | 0.7200 | 0.9394 | 0 |
| 0.5255 | 0.7824 | 0.9588 | 0.4509 | 0.8190 | 0.9701 | 1 |
| 0.3218 | 0.8454 | 0.9759 | 0.3839 | 0.8644 | 0.9803 | 2 |
| 0.2230 | 0.8794 | 0.9830 | 0.3494 | 0.8923 | 0.9852 | 3 |
| 0.1755 | 0.9022 | 0.9868 | 0.3445 | 0.9104 | 0.9882 | 4 |
| 0.1539 | 0.9173 | 0.9892 | 0.3343 | 0.9231 | 0.9901 | 5 |
| 0.1455 | 0.9282 | 0.9908 | 0.3319 | 0.9322 | 0.9914 | 6 |
### Framework versions
- Transformers 4.44.2
- TensorFlow 2.15.1
- Datasets 3.0.0
- Tokenizers 0.19.1
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