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---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-dmae-va-U
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# vit-base-patch16-224-dmae-va-U
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:
- Loss: 0.0534
- Accuracy: 0.9908
## 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:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.9 | 7 | 1.4319 | 0.2569 |
| 1.3911 | 1.94 | 15 | 1.2133 | 0.4771 |
| 1.3911 | 2.97 | 23 | 0.9487 | 0.6055 |
| 1.0766 | 4.0 | 31 | 0.6542 | 0.7156 |
| 0.6974 | 4.9 | 38 | 0.4644 | 0.8716 |
| 0.6974 | 5.94 | 46 | 0.3919 | 0.8716 |
| 0.421 | 6.97 | 54 | 0.3094 | 0.8716 |
| 0.2513 | 8.0 | 62 | 0.2334 | 0.8991 |
| 0.2513 | 8.9 | 69 | 0.1915 | 0.9174 |
| 0.1931 | 9.94 | 77 | 0.2431 | 0.8807 |
| 0.1757 | 10.97 | 85 | 0.1608 | 0.9450 |
| 0.1757 | 12.0 | 93 | 0.1424 | 0.9266 |
| 0.1442 | 12.9 | 100 | 0.1280 | 0.9450 |
| 0.1085 | 13.94 | 108 | 0.1055 | 0.9541 |
| 0.1085 | 14.97 | 116 | 0.1080 | 0.9541 |
| 0.1056 | 16.0 | 124 | 0.0997 | 0.9633 |
| 0.1056 | 16.9 | 131 | 0.1185 | 0.9633 |
| 0.0926 | 17.94 | 139 | 0.0773 | 0.9633 |
| 0.103 | 18.97 | 147 | 0.1279 | 0.9633 |
| 0.103 | 20.0 | 155 | 0.1043 | 0.9633 |
| 0.0938 | 20.9 | 162 | 0.0824 | 0.9817 |
| 0.0891 | 21.94 | 170 | 0.1449 | 0.9541 |
| 0.0891 | 22.97 | 178 | 0.1366 | 0.9633 |
| 0.0754 | 24.0 | 186 | 0.1148 | 0.9358 |
| 0.0882 | 24.9 | 193 | 0.1992 | 0.9358 |
| 0.0882 | 25.94 | 201 | 0.0743 | 0.9817 |
| 0.078 | 26.97 | 209 | 0.0668 | 0.9725 |
| 0.0666 | 28.0 | 217 | 0.0534 | 0.9908 |
| 0.0666 | 28.9 | 224 | 0.0499 | 0.9908 |
| 0.0514 | 29.94 | 232 | 0.0433 | 0.9725 |
| 0.062 | 30.97 | 240 | 0.0840 | 0.9633 |
| 0.062 | 32.0 | 248 | 0.0513 | 0.9725 |
| 0.0712 | 32.9 | 255 | 0.0482 | 0.9817 |
| 0.0712 | 33.94 | 263 | 0.0553 | 0.9817 |
| 0.0703 | 34.97 | 271 | 0.0602 | 0.9725 |
| 0.0553 | 36.0 | 279 | 0.0595 | 0.9725 |
| 0.0553 | 36.13 | 280 | 0.0595 | 0.9725 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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