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license: apache-2.0
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tags:
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- generated_from_keras_callback
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model-index:
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- name: Guldeniz/vit-base-patch16-224-in21k-lung_and_colon
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results: []
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---
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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# Guldeniz/vit-base-patch16-224-in21k-lung_and_colon
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on
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It achieves the following results on the evaluation set:
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- Train Loss: 0.0088
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- Train Accuracy: 1.0
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- Transformers 4.26.1
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- TensorFlow 2.12.0
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- Datasets 2.10.1
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- Tokenizers 0.13.3
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license: apache-2.0
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tags:
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- generated_from_keras_callback
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- vision_transformer
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model-index:
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- name: Guldeniz/vit-base-patch16-224-in21k-lung_and_colon
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results: []
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language:
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- en
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metrics:
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- accuracy
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library_name: transformers
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pipeline_tag: image-classification
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---
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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# Guldeniz/vit-base-patch16-224-in21k-lung_and_colon
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on Lung and Colon Histopathological Images dataset. This dataset can be reach via [Kaggle](https://www.kaggle.com/datasets/andrewmvd/lung-and-colon-cancer-histopathological-images).
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It achieves the following results on the evaluation set:
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- Train Loss: 0.0088
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- Train Accuracy: 1.0
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- Transformers 4.26.1
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- TensorFlow 2.12.0
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- Datasets 2.10.1
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- Tokenizers 0.13.3
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