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update model card README.md
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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- image_folder
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metrics:
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- accuracy
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model-index:
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- name: violation-classification-bantai-vit-v100ep
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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: image_folder
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type: image_folder
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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: 0.896066402020931
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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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# violation-classification-bantai-vit-v100ep
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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 image_folder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2943
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- Accuracy: 0.8961
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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: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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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: 100
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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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| 1.2596 | 1.0 | 101 | 1.2230 | 0.5615 |
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| 0.8527 | 2.0 | 202 | 0.8234 | 0.6840 |
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| 0.6375 | 3.0 | 303 | 0.6001 | 0.7846 |
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| 0.555 | 4.0 | 404 | 0.5038 | 0.8178 |
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| 0.4433 | 5.0 | 505 | 0.4338 | 0.8436 |
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| 0.406 | 6.0 | 606 | 0.3765 | 0.8661 |
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| 0.3517 | 7.0 | 707 | 0.3466 | 0.8793 |
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| 0.312 | 8.0 | 808 | 0.3011 | 0.8970 |
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| 0.2842 | 9.0 | 909 | 0.2943 | 0.8961 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.10.0+cu111
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- Datasets 2.0.0
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- Tokenizers 0.11.6
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