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---
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license: apache-2.0
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base_model: google/efficientnet-b0
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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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model-index:
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- name: SkinCancerClassifier_Plain-V1
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/jhoppanne-myself/finalProject/runs/ow4dk70u)
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/jhoppanne-myself/finalProject/runs/ow4dk70u)
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/jhoppanne-myself/finalProject/runs/ow4dk70u)
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/jhoppanne-myself/finalProject/runs/8hxuz0bh)
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# SkinCancerClassifier_Plain-V1
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This model is a fine-tuned version of [google/efficientnet-b0](https://huggingface.co/google/efficientnet-b0) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 1.0790
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- eval_accuracy: 0.7792
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- eval_runtime: 1.5074
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- eval_samples_per_second: 159.219
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- eval_steps_per_second: 5.307
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- epoch: 104.5667
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- step: 3137
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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: 1e-06
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 2000
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### Framework versions
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- Transformers 4.42.2
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- Pytorch 2.3.0
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- Datasets 2.15.0
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- Tokenizers 0.19.1
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