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update model card README.md
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README.md
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---
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license: apache-2.0
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tags:
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- image-classification
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- vision
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- generated_from_trainer
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datasets:
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metrics:
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- accuracy
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model-index:
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name: Image Classification
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type: image-classification
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dataset:
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name:
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type:
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config:
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split: train
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args:
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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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-base-mnist
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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: 0.
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- Accuracy: 0.
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## Model description
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### Training results
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| Training Loss | Epoch | Step
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### Framework versions
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- mnist
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metrics:
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- accuracy
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model-index:
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name: Image Classification
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type: image-classification
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dataset:
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name: mnist
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type: mnist
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config: mnist
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split: train
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args: mnist
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9948888888888889
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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-base-mnist
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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 mnist dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0236
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- Accuracy: 0.9949
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 0.3717 | 1.0 | 6375 | 0.0522 | 0.9893 |
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| 0.3453 | 2.0 | 12750 | 0.0370 | 0.9906 |
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| 0.3736 | 3.0 | 19125 | 0.0308 | 0.9916 |
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| 0.3224 | 4.0 | 25500 | 0.0269 | 0.9939 |
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| 0.2846 | 5.0 | 31875 | 0.0236 | 0.9949 |
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### Framework versions
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