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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
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
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: 0.5797
- Accuracy: 0.8354
## 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8845 | 0.99 | 40 | 1.8553 | 0.3106 |
| 1.6458 | 1.99 | 80 | 1.6211 | 0.4363 |
| 1.4423 | 2.98 | 120 | 1.4076 | 0.5202 |
| 1.2767 | 4.0 | 161 | 1.2806 | 0.5714 |
| 1.0687 | 4.99 | 201 | 1.0996 | 0.6537 |
| 0.9687 | 5.99 | 241 | 1.0288 | 0.6677 |
| 0.8714 | 6.98 | 281 | 0.9370 | 0.7252 |
| 0.7841 | 8.0 | 322 | 0.8287 | 0.7484 |
| 0.6814 | 8.99 | 362 | 0.8141 | 0.7376 |
| 0.5964 | 9.99 | 402 | 0.7433 | 0.7919 |
| 0.5995 | 10.98 | 442 | 0.7075 | 0.7904 |
| 0.5222 | 12.0 | 483 | 0.6613 | 0.8043 |
| 0.5173 | 12.99 | 523 | 0.6485 | 0.8090 |
| 0.4776 | 13.99 | 563 | 0.6196 | 0.8230 |
| 0.4679 | 14.98 | 603 | 0.5795 | 0.8416 |
| 0.4123 | 16.0 | 644 | 0.6202 | 0.8168 |
| 0.4179 | 16.99 | 684 | 0.6037 | 0.8230 |
| 0.4139 | 17.99 | 724 | 0.5797 | 0.8354 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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