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README.md
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tags:
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- generated_from_trainer
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datasets:
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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 [d071696/vit-finetune-scrap](https://huggingface.co/d071696/vit-finetune-scrap) on the
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## Model description
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### Training results
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### Framework versions
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tags:
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- generated_from_trainer
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datasets:
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- arrow
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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: arrow
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type: arrow
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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: 0.954983922829582
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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 [d071696/vit-finetune-scrap](https://huggingface.co/d071696/vit-finetune-scrap) on the arrow dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1805
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- Accuracy: 0.9550
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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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| 0.1672 | 0.64 | 100 | 0.2250 | 0.9486 |
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| 0.1277 | 1.28 | 200 | 0.2467 | 0.9373 |
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| 0.0253 | 1.92 | 300 | 0.1588 | 0.9550 |
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| 0.0224 | 2.56 | 400 | 0.1691 | 0.9534 |
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| 0.0321 | 3.21 | 500 | 0.1751 | 0.9566 |
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| 0.0112 | 3.85 | 600 | 0.1805 | 0.9550 |
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### Framework versions
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model.safetensors
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