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update model card README.md
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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: histo_train_vit
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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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# histo_train_vit
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the
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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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- mixed_precision_training: Native AMP
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### Training results
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### Framework versions
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- Transformers 4.
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- Pytorch 1.13.
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- Datasets 2.1
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- Tokenizers 0.13.2
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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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metrics:
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- accuracy
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model-index:
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- name: histo_train_vit
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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: imagefolder
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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: 0.825
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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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# histo_train_vit
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7340
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- Accuracy: 0.825
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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: 20
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- mixed_precision_training: Native AMP
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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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| 1.0481 | 1.67 | 10 | 0.4926 | 0.825 |
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| 0.3714 | 3.33 | 20 | 0.3388 | 0.9 |
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| 0.0642 | 5.0 | 30 | 0.3255 | 0.875 |
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| 0.0199 | 6.67 | 40 | 0.4111 | 0.875 |
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| 0.0074 | 8.33 | 50 | 0.3334 | 0.925 |
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| 0.0024 | 10.0 | 60 | 0.3710 | 0.9 |
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| 0.0131 | 11.67 | 70 | 0.5366 | 0.85 |
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| 0.0067 | 13.33 | 80 | 0.5172 | 0.875 |
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| 0.0152 | 15.0 | 90 | 0.4835 | 0.9 |
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| 0.0058 | 16.67 | 100 | 0.3979 | 0.875 |
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| 0.0005 | 18.33 | 110 | 0.5964 | 0.825 |
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| 0.0008 | 20.0 | 120 | 0.7340 | 0.825 |
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### Framework versions
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- Transformers 4.27.3
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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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