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README.md
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# vit-base-highways-2
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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:
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- Accuracy: 0.
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## Model description
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs:
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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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### Framework versions
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- Transformers 4.
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- Pytorch 1.
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- Datasets 2.
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- Tokenizers 0.13.2
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# vit-base-highways-2
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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 None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.5075
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- Accuracy: 0.7
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## Model description
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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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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| 0.018 | 4.17 | 100 | 1.2669 | 0.7 |
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| 0.0326 | 8.33 | 200 | 1.5075 | 0.7 |
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### Framework versions
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- Transformers 4.27.2
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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