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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: dental_classification_model_010424_1
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. -->
# dental_classification_model_010424_1
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:
- Loss: 0.5468
- Accuracy: 0.8293
## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9173 | 0.99 | 41 | 1.9026 | 0.2825 |
| 1.7055 | 2.0 | 83 | 1.6619 | 0.3882 |
| 1.5398 | 2.99 | 124 | 1.5061 | 0.4849 |
| 1.3415 | 4.0 | 166 | 1.3317 | 0.5801 |
| 1.1753 | 4.99 | 207 | 1.2437 | 0.5876 |
| 1.017 | 6.0 | 249 | 1.1052 | 0.6390 |
| 0.8724 | 6.99 | 290 | 0.9521 | 0.6873 |
| 0.8207 | 8.0 | 332 | 0.9114 | 0.7115 |
| 0.7706 | 8.99 | 373 | 0.8574 | 0.7130 |
| 0.6788 | 10.0 | 415 | 0.7974 | 0.7523 |
| 0.63 | 10.99 | 456 | 0.7611 | 0.7659 |
| 0.5633 | 12.0 | 498 | 0.7764 | 0.7553 |
| 0.5581 | 12.99 | 539 | 0.7370 | 0.7779 |
| 0.5117 | 14.0 | 581 | 0.6945 | 0.7689 |
| 0.4933 | 14.99 | 622 | 0.7066 | 0.7719 |
| 0.4787 | 16.0 | 664 | 0.6405 | 0.8006 |
| 0.4169 | 16.99 | 705 | 0.6443 | 0.8036 |
| 0.3756 | 18.0 | 747 | 0.5991 | 0.8187 |
| 0.3629 | 18.99 | 788 | 0.5774 | 0.8202 |
| 0.3719 | 20.0 | 830 | 0.5451 | 0.8369 |
| 0.4216 | 20.99 | 871 | 0.5623 | 0.8338 |
| 0.3739 | 22.0 | 913 | 0.5995 | 0.8066 |
| 0.3096 | 22.99 | 954 | 0.5330 | 0.8353 |
| 0.3002 | 24.0 | 996 | 0.5109 | 0.8323 |
| 0.3372 | 24.99 | 1037 | 0.5468 | 0.8293 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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