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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: VIT_fourclass_Jun25
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. -->
# VIT_fourclass_Jun25
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: 0.0938
- Validation Loss: 2.3960
- Train Accuracy: 0.51
- Epoch: 14
## 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': 'SGD', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': np.float32(0.01), 'momentum': 0.0, 'nesterov': False}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.9196 | 1.2060 | 0.38 | 0 |
| 0.3792 | 1.4807 | 0.48 | 1 |
| 0.2729 | 1.7396 | 0.45 | 2 |
| 0.2006 | 2.4379 | 0.29 | 3 |
| 0.1996 | 2.4795 | 0.36 | 4 |
| 0.1734 | 2.7916 | 0.35 | 5 |
| 0.1860 | 4.1270 | 0.09 | 6 |
| 0.1490 | 2.7235 | 0.37 | 7 |
| 0.1077 | 3.5380 | 0.26 | 8 |
| 0.1173 | 2.7697 | 0.42 | 9 |
| 0.1526 | 2.7868 | 0.42 | 10 |
| 0.1161 | 3.1132 | 0.36 | 11 |
| 0.1093 | 3.5738 | 0.33 | 12 |
| 0.0884 | 3.1227 | 0.37 | 13 |
| 0.0938 | 2.3960 | 0.51 | 14 |
### Framework versions
- Transformers 4.52.4
- TensorFlow 2.18.0
- Datasets 3.6.0
- Tokenizers 0.21.1
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