This is a fine-tuned ViT (Google) that serves more as an exploration of vision transformers in medicine for my learning than as anything specific. I fine-tuned this model on a dataset of ~7000 images of breast cancer slides labelled as 'benign' or 'cancerous'.
I used the Transformers library and the out-of-the-box ViTForImageClassification configuration.
Despite this being an incredibly barebones fine-tune, I hope you fine it useful! Any recommendations are welcome!
Intended uses & limitations
This is a super basic fine tuned model. Please evaluate its performance for yourself do determine whether it can be useful for you. In a big picture sense, this model can tell apart benign and cancerous breast tissue samples.
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 0.0002
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
