synergyai-jaeung
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README.md
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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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model.safetensors
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