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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_1 |
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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_1 |
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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: 0.5468 |
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- Accuracy: 0.8293 |
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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: 30 |
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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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| 1.9173 | 0.99 | 41 | 1.9026 | 0.2825 | |
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| 1.7055 | 2.0 | 83 | 1.6619 | 0.3882 | |
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| 1.5398 | 2.99 | 124 | 1.5061 | 0.4849 | |
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| 1.3415 | 4.0 | 166 | 1.3317 | 0.5801 | |
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| 1.1753 | 4.99 | 207 | 1.2437 | 0.5876 | |
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| 1.017 | 6.0 | 249 | 1.1052 | 0.6390 | |
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| 0.8724 | 6.99 | 290 | 0.9521 | 0.6873 | |
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| 0.8207 | 8.0 | 332 | 0.9114 | 0.7115 | |
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| 0.7706 | 8.99 | 373 | 0.8574 | 0.7130 | |
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| 0.6788 | 10.0 | 415 | 0.7974 | 0.7523 | |
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| 0.63 | 10.99 | 456 | 0.7611 | 0.7659 | |
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| 0.5633 | 12.0 | 498 | 0.7764 | 0.7553 | |
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| 0.5581 | 12.99 | 539 | 0.7370 | 0.7779 | |
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| 0.5117 | 14.0 | 581 | 0.6945 | 0.7689 | |
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| 0.4933 | 14.99 | 622 | 0.7066 | 0.7719 | |
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| 0.4787 | 16.0 | 664 | 0.6405 | 0.8006 | |
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| 0.4169 | 16.99 | 705 | 0.6443 | 0.8036 | |
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| 0.3756 | 18.0 | 747 | 0.5991 | 0.8187 | |
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| 0.3629 | 18.99 | 788 | 0.5774 | 0.8202 | |
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| 0.3719 | 20.0 | 830 | 0.5451 | 0.8369 | |
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| 0.4216 | 20.99 | 871 | 0.5623 | 0.8338 | |
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| 0.3739 | 22.0 | 913 | 0.5995 | 0.8066 | |
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| 0.3096 | 22.99 | 954 | 0.5330 | 0.8353 | |
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| 0.3002 | 24.0 | 996 | 0.5109 | 0.8323 | |
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| 0.3372 | 24.99 | 1037 | 0.5468 | 0.8293 | |
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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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