update model card README.md
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README.md
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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: swin-tiny-patch4-window7-224-arty-bg-classifier
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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: 0.9786450662739322
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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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This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size:
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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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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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| 0.199 | 0.94 | 20 | 0.1321 | 0.9507 |
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| 0.1198 | 1.88 | 40 | 0.0844 | 0.9691 |
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| 0.1013 | 2.82 | 60 | 0.0707 | 0.9735 |
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| 0.0734 | 3.76 | 80 | 0.0581 | 0.9772 |
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| 0.0666 | 4.71 | 100 | 0.0518 | 0.9786 |
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### Framework versions
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- Transformers 4.29.1
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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: swin-tiny-patch4-window7-224-arty-bg-classifier
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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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This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 0.0086
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- eval_accuracy: 0.9975
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- eval_runtime: 102.2105
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- eval_samples_per_second: 127.639
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- eval_steps_per_second: 1.331
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- epoch: 1.84
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- step: 250
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 96
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- eval_batch_size: 96
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 384
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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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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 5
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### Framework versions
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- Transformers 4.29.1
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