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---
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license: apache-2.0
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base_model: microsoft/beit-base-patch16-224
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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: beit-base-patch16-224-OT
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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: validation
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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: 0.8225806451612904
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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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# beit-base-patch16-224-OT
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This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-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: 0.4801
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- Accuracy: 0.8226
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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: 40
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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 | 0.89 | 4 | 1.7603 | 0.1452 |
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| No log | 2.0 | 9 | 1.6852 | 0.1452 |
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| 1.7571 | 2.89 | 13 | 1.5655 | 0.1452 |
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| 1.7571 | 4.0 | 18 | 1.3816 | 0.1452 |
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| 1.5255 | 4.89 | 22 | 1.2599 | 0.3226 |
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| 1.5255 | 6.0 | 27 | 1.1534 | 0.4839 |
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| 1.2245 | 6.89 | 31 | 1.0641 | 0.4839 |
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| 1.2245 | 8.0 | 36 | 1.0372 | 0.4355 |
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| 1.0438 | 8.89 | 40 | 0.9988 | 0.4355 |
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| 1.0438 | 10.0 | 45 | 0.9260 | 0.5161 |
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| 1.0438 | 10.89 | 49 | 0.9085 | 0.7097 |
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| 0.9727 | 12.0 | 54 | 0.8433 | 0.7258 |
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| 0.9727 | 12.89 | 58 | 0.7529 | 0.7742 |
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| 0.8469 | 14.0 | 63 | 0.7187 | 0.7581 |
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| 0.8469 | 14.89 | 67 | 0.6806 | 0.7258 |
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| 0.6908 | 16.0 | 72 | 0.6576 | 0.7581 |
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| 0.6908 | 16.89 | 76 | 0.5742 | 0.7903 |
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| 0.6064 | 18.0 | 81 | 0.6447 | 0.7581 |
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| 0.6064 | 18.89 | 85 | 0.5602 | 0.7742 |
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| 0.5303 | 20.0 | 90 | 0.4943 | 0.7903 |
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| 0.5303 | 20.89 | 94 | 0.5304 | 0.7903 |
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| 0.5303 | 22.0 | 99 | 0.4801 | 0.8226 |
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| 0.4903 | 22.89 | 103 | 0.4849 | 0.8226 |
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| 0.4903 | 24.0 | 108 | 0.5710 | 0.7742 |
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| 0.4261 | 24.89 | 112 | 0.4803 | 0.7903 |
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| 0.4261 | 26.0 | 117 | 0.5671 | 0.7258 |
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| 0.4122 | 26.89 | 121 | 0.4585 | 0.8065 |
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| 0.4122 | 28.0 | 126 | 0.5910 | 0.7097 |
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| 0.3739 | 28.89 | 130 | 0.5821 | 0.7581 |
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| 0.3739 | 30.0 | 135 | 0.5329 | 0.7742 |
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| 0.3739 | 30.89 | 139 | 0.4423 | 0.8226 |
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| 0.3896 | 32.0 | 144 | 0.4716 | 0.7581 |
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| 0.3896 | 32.89 | 148 | 0.4786 | 0.7903 |
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| 0.3472 | 34.0 | 153 | 0.4538 | 0.7903 |
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| 0.3472 | 34.89 | 157 | 0.4553 | 0.7903 |
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| 0.3349 | 35.56 | 160 | 0.4528 | 0.7903 |
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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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