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wjworld/open_clip_quilt1m_ft_cy_1
open_clip_quilt1m_ft_cy_1 is a zero-shot image classification model from wjworld. Use it for the zero-shot image classification task on the model card, and read the license before you ship it in a product. It is set up for open_clip. The card lists the license as mit.
This model is finetuned based on the Quilt-1M VIT-B-32 model using Chaoyang Dataset. The training csv file is : /dataset/chaoyang/chaoyangtrainmultiannos.csv For this model, I insert the multi-labels into the prompts.…
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From the Hugging Face model README
This model is finetuned based on the Quilt-1M VIT-B-32 model using Chaoyang Dataset.
The training csv file is : /dataset/chaoyang/chaoyang_train_multi_annos.csv
For this model, I insert the multi-labels into the prompts. Since the "normal" and "serrated" are the adj, so I add the nouns for better expression.
The Paired Text used for training as listed below:
normal: "normal histology" serrated: "serrated polyps" adenocarcinomas: "adenocarcinomas" adenomas: "adenomas"
So for different combinations, replacing the labels with corresponding words.
"normal histology, normal histology, normal histology"
"serrated polyps, serrated polyps, serrated polyps"
"adenocarcinomas, adenocarcinomas, adenocarcinomas"
"adenomas, adenomas, adenomas"
"adenomas, normal histology, adenomas"
The model is finetuned with Chaoyang Dataset with 64 epochs, but I choose the 32th checkpoint as the final model according to the plot of loss. I.e., the loss began kept stable.