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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-DMAE-5e-5
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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: 0.8043478260869565
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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-DMAE-5e-5
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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: 0.6236
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- Accuracy: 0.8043
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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 | 0.86 | 3 | 1.3816 | 0.4565 |
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| No log | 2.0 | 7 | 1.3504 | 0.4565 |
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| 1.3654 | 2.86 | 10 | 1.3075 | 0.4565 |
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| 1.3654 | 4.0 | 14 | 1.2444 | 0.4565 |
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| 1.3654 | 4.86 | 17 | 1.2089 | 0.4565 |
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| 1.2386 | 6.0 | 21 | 1.1711 | 0.4565 |
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| 1.2386 | 6.86 | 24 | 1.1492 | 0.4565 |
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| 1.2386 | 8.0 | 28 | 1.1050 | 0.4783 |
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| 1.132 | 8.86 | 31 | 1.0928 | 0.6522 |
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| 1.132 | 10.0 | 35 | 1.0230 | 0.6739 |
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| 1.132 | 10.86 | 38 | 0.9864 | 0.6522 |
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| 1.015 | 12.0 | 42 | 1.0060 | 0.6739 |
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| 1.015 | 12.86 | 45 | 0.8790 | 0.7174 |
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| 1.015 | 14.0 | 49 | 0.8533 | 0.6739 |
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| 0.9217 | 14.86 | 52 | 0.8203 | 0.6957 |
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| 0.9217 | 16.0 | 56 | 0.8152 | 0.6739 |
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| 0.9217 | 16.86 | 59 | 0.8598 | 0.6522 |
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| 0.7989 | 18.0 | 63 | 0.7979 | 0.6957 |
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| 0.7989 | 18.86 | 66 | 0.7555 | 0.6739 |
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| 0.7309 | 20.0 | 70 | 0.7019 | 0.7609 |
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| 0.7309 | 20.86 | 73 | 0.7254 | 0.7174 |
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| 0.7309 | 22.0 | 77 | 0.7268 | 0.6739 |
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| 0.6267 | 22.86 | 80 | 0.7096 | 0.6739 |
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| 0.6267 | 24.0 | 84 | 0.7568 | 0.6739 |
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| 0.6267 | 24.86 | 87 | 0.6565 | 0.7391 |
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| 0.564 | 26.0 | 91 | 0.7035 | 0.7391 |
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| 0.564 | 26.86 | 94 | 0.7081 | 0.7391 |
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| 0.564 | 28.0 | 98 | 0.6236 | 0.8043 |
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| 0.5625 | 28.86 | 101 | 0.6091 | 0.8043 |
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| 0.5625 | 30.0 | 105 | 0.6523 | 0.7609 |
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| 0.5625 | 30.86 | 108 | 0.6235 | 0.7826 |
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| 0.5185 | 32.0 | 112 | 0.5974 | 0.7826 |
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| 0.5185 | 32.86 | 115 | 0.5944 | 0.7826 |
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| 0.5185 | 34.0 | 119 | 0.6005 | 0.7826 |
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| 0.5005 | 34.29 | 120 | 0.6005 | 0.7826 |
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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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