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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: dental_classification_model_010424 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# dental_classification_model_010424 |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5797 |
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- Accuracy: 0.8354 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.8845 | 0.99 | 40 | 1.8553 | 0.3106 | |
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| 1.6458 | 1.99 | 80 | 1.6211 | 0.4363 | |
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| 1.4423 | 2.98 | 120 | 1.4076 | 0.5202 | |
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| 1.2767 | 4.0 | 161 | 1.2806 | 0.5714 | |
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| 1.0687 | 4.99 | 201 | 1.0996 | 0.6537 | |
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| 0.9687 | 5.99 | 241 | 1.0288 | 0.6677 | |
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| 0.8714 | 6.98 | 281 | 0.9370 | 0.7252 | |
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| 0.7841 | 8.0 | 322 | 0.8287 | 0.7484 | |
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| 0.6814 | 8.99 | 362 | 0.8141 | 0.7376 | |
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| 0.5964 | 9.99 | 402 | 0.7433 | 0.7919 | |
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| 0.5995 | 10.98 | 442 | 0.7075 | 0.7904 | |
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| 0.5222 | 12.0 | 483 | 0.6613 | 0.8043 | |
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| 0.5173 | 12.99 | 523 | 0.6485 | 0.8090 | |
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| 0.4776 | 13.99 | 563 | 0.6196 | 0.8230 | |
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| 0.4679 | 14.98 | 603 | 0.5795 | 0.8416 | |
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| 0.4123 | 16.0 | 644 | 0.6202 | 0.8168 | |
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| 0.4179 | 16.99 | 684 | 0.6037 | 0.8230 | |
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| 0.4139 | 17.99 | 724 | 0.5797 | 0.8354 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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