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---
license: apache-2.0
base_model: google/efficientnet-b0
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: SkinCancerClassifier_Plain-V1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<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)
[<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)
[<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)
[<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)
# SkinCancerClassifier_Plain-V1
This model is a fine-tuned version of [google/efficientnet-b0](https://huggingface.co/google/efficientnet-b0) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.0790
- eval_accuracy: 0.7792
- eval_runtime: 1.5074
- eval_samples_per_second: 159.219
- eval_steps_per_second: 5.307
- epoch: 104.5667
- step: 3137
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2000
### Framework versions
- Transformers 4.42.2
- Pytorch 2.3.0
- Datasets 2.15.0
- Tokenizers 0.19.1
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