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README.md
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license: apache-2.0
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base_model: google/vit-base-patch16-224-in21k
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tags:
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- image-classification
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- zero-shot-image-classification
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- generated_from_trainer
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datasets:
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- imagefolder
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metrics:
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- accuracy
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model-index:
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- name: vit-finetune-scrap
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results:
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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: d071696/scraps1
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type: imagefolder
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config: default
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split: train
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9333333333333333
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# vit-finetune-scrap
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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 the
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It achieves the following results on the evaluation set:
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- Loss: 1.6026
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- Accuracy: 0.9333
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## Model description
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license: apache-2.0
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base_model: google/vit-base-patch16-224-in21k
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tags:
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- generated_from_trainer
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datasets:
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- imagefolder
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model-index:
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- name: vit-finetune-scrap
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# vit-finetune-scrap
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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 the imagefolder dataset.
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## Model description
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model.safetensors
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runs/Mar22_11-09-00_X5C922065N/events.out.tfevents.1711102143.X5C922065N.52576.13
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