Model Card: Fine Tuned Vision Transformer (ViT) for NSFW Image Classification Model Description The Fine Tuned Vision Transformer (ViT) is a variant of the transformer encoder architecture, similar to BERT, that has been adapted for image classification tasks. This specific model, named "google/vit base patch16 224 in21k," is pre trained on a substantial collection of images in a supervised manner, leveraging the ImageNet 21k dataset. The images in the pre training dataset are resized to a resolution of 224x224 pixels, making it suitable for a wide range of image recognition tasks. During the training phase, meticulous attention was given to hyperparameter settings to ensure optimal model performance. The model was fine tuned with a judiciously chosen batch size of 16. This choice not only balanced computational efficiency but also allowed for the model to effectively process and learn from a diverse array of images. To facilitate this fine tuning process, a learning rate of 5e 5 was employed. The learning rate serves as a critical tuning parameter that dictates the magnitude of adjustments made to the model's parameters during training. In this case, a learning rate of 5e 5 was se…
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