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README.md
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---
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license: apache-2.0
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base_model: google/vit-base-patch16-224
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: WS800_ViT_42895082
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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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should probably proofread and complete it, then remove this comment. -->
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# WS800_ViT_42895082
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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 an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0776
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- Accuracy: 0.9875
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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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: 20
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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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| No log | 1.0 | 5 | 0.6859 | 0.925 |
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| No log | 2.0 | 10 | 0.6328 | 0.975 |
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| No log | 3.0 | 15 | 0.5301 | 0.975 |
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| No log | 4.0 | 20 | 0.4404 | 0.9625 |
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| No log | 5.0 | 25 | 0.3480 | 0.975 |
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| No log | 6.0 | 30 | 0.2758 | 0.975 |
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| No log | 7.0 | 35 | 0.2179 | 0.9875 |
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| No log | 8.0 | 40 | 0.1789 | 0.9875 |
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| No log | 9.0 | 45 | 0.1505 | 0.9875 |
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| 0.3788 | 10.0 | 50 | 0.1296 | 0.9875 |
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| 0.3788 | 11.0 | 55 | 0.1145 | 0.9875 |
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| 0.3788 | 12.0 | 60 | 0.1034 | 0.9875 |
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| 0.3788 | 13.0 | 65 | 0.0954 | 0.9875 |
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| 0.3788 | 14.0 | 70 | 0.0895 | 0.9875 |
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| 0.3788 | 15.0 | 75 | 0.0853 | 0.9875 |
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| 0.3788 | 16.0 | 80 | 0.0822 | 0.9875 |
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| 0.3788 | 17.0 | 85 | 0.0801 | 0.9875 |
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| 0.3788 | 18.0 | 90 | 0.0787 | 0.9875 |
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| 0.3788 | 19.0 | 95 | 0.0779 | 0.9875 |
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| 0.0547 | 20.0 | 100 | 0.0776 | 0.9875 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.1.2+cu118
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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