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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: convnextv2-large-1k-224-finetuned-LungCancer-Classification-LC25000-AH-60-20-20 |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: Augmented-Final |
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split: train |
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args: Augmented-Final |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9996666666666667 |
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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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# convnextv2-large-1k-224-finetuned-LungCancer-Classification-LC25000-AH-60-20-20 |
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This model is a fine-tuned version of [facebook/convnextv2-large-1k-224](https://huggingface.co/facebook/convnextv2-large-1k-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0043 |
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- Accuracy: 0.9997 |
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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: 2 |
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- total_train_batch_size: 32 |
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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: 0.9 |
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- num_epochs: 12 |
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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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| 0.4332 | 1.0 | 281 | 0.3824 | 0.947 | |
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| 0.1558 | 2.0 | 563 | 0.1292 | 0.9737 | |
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| 0.1161 | 3.0 | 844 | 0.0556 | 0.9887 | |
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| 0.2337 | 4.0 | 1126 | 0.0683 | 0.982 | |
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| 0.1285 | 5.0 | 1407 | 0.0293 | 0.9923 | |
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| 0.047 | 6.0 | 1689 | 0.0987 | 0.975 | |
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| 0.0741 | 7.0 | 1970 | 0.0373 | 0.988 | |
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| 0.153 | 8.0 | 2252 | 0.0043 | 0.9997 | |
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| 0.0244 | 9.0 | 2533 | 0.0696 | 0.981 | |
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| 0.0646 | 10.0 | 2815 | 0.0120 | 0.995 | |
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| 0.0025 | 11.0 | 3096 | 0.0076 | 0.9977 | |
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| 0.0611 | 11.98 | 3372 | 0.0024 | 0.9997 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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