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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-40-30-30 |
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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: 0.9433001107419712 |
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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-40-30-30 |
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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: 0.1791 |
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- Accuracy: 0.9433 |
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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: 0.0005 |
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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: 0.5 |
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- num_epochs: 5 |
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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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| 0.254 | 0.99 | 93 | 0.1791 | 0.9433 | |
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| 0.4225 | 1.99 | 187 | 0.4341 | 0.8297 | |
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| 0.4801 | 3.0 | 281 | 0.4158 | 0.8890 | |
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| 0.2558 | 4.0 | 375 | 0.2540 | 0.8952 | |
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| 0.1809 | 4.96 | 465 | 0.1753 | 0.9358 | |
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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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