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--- |
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license: apache-2.0 |
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base_model: DunnBC22/vit-base-patch16-224-in21k_covid_19_ct_scans |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: vit-base-patch16-224-in21k_covid_19_ct_scans-finetuned-RCC |
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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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# vit-base-patch16-224-in21k_covid_19_ct_scans-finetuned-RCC |
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This model is a fine-tuned version of [DunnBC22/vit-base-patch16-224-in21k_covid_19_ct_scans](https://huggingface.co/DunnBC22/vit-base-patch16-224-in21k_covid_19_ct_scans) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3235 |
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- Accuracy: 0.9032 |
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- Precision: 0.9032 |
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- Recall: 1.0 |
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- F1: 0.4746 |
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- Auc: 0.5 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Auc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:---:| |
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| No log | 1.0 | 7 | 0.3327 | 0.9032 | 0.9032 | 1.0 | 0.4746 | 0.5 | |
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| 0.3866 | 2.0 | 14 | 0.3213 | 0.9032 | 0.9032 | 1.0 | 0.4746 | 0.5 | |
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| 0.2647 | 3.0 | 21 | 0.3226 | 0.9032 | 0.9032 | 1.0 | 0.4746 | 0.5 | |
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| 0.2647 | 4.0 | 28 | 0.3246 | 0.9032 | 0.9032 | 1.0 | 0.4746 | 0.5 | |
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| 0.2593 | 5.0 | 35 | 0.3235 | 0.9032 | 0.9032 | 1.0 | 0.4746 | 0.5 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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