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dental_classification_model_010424

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  1. README.md +80 -0
  2. model.safetensors +1 -1
  3. runs/Apr01_06-08-22_cb5942b2f4ba/events.out.tfevents.1711951703.cb5942b2f4ba.1079.0 +2 -2
README.md ADDED
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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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+
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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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+
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+ # dental_classification_model_010424
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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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