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---
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license: apache-2.0
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base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
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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: Boya1_RMSProp_1-e5_20Epoch_09Momentum_Beit-base-patch16_fold5
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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: test
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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: 0.649850827230811
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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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# Boya1_RMSProp_1-e5_20Epoch_09Momentum_Beit-base-patch16_fold5
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This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.1823
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- Accuracy: 0.6499
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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: 0.0001
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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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- 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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| 1.1635 | 1.0 | 924 | 1.1860 | 0.5948 |
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| 1.0619 | 2.0 | 1848 | 1.0310 | 0.6455 |
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| 0.646 | 3.0 | 2772 | 1.0620 | 0.6509 |
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| 0.3294 | 4.0 | 3696 | 1.2169 | 0.6599 |
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| 0.2648 | 5.0 | 4620 | 1.4374 | 0.6455 |
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| 0.1957 | 6.0 | 5544 | 1.7164 | 0.6420 |
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| 0.131 | 7.0 | 6468 | 2.0272 | 0.6488 |
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| 0.0817 | 8.0 | 7392 | 2.2750 | 0.6447 |
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| 0.0483 | 9.0 | 8316 | 2.4384 | 0.6431 |
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| 0.0451 | 10.0 | 9240 | 2.6186 | 0.6447 |
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| 0.0224 | 11.0 | 10164 | 2.7368 | 0.6463 |
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| 0.0134 | 12.0 | 11088 | 2.9439 | 0.6477 |
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| 0.0023 | 13.0 | 12012 | 2.9691 | 0.6520 |
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| 0.0074 | 14.0 | 12936 | 3.0721 | 0.6450 |
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| 0.0231 | 15.0 | 13860 | 3.1373 | 0.6499 |
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| 0.0004 | 16.0 | 14784 | 3.2089 | 0.6474 |
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| 0.0062 | 17.0 | 15708 | 3.1483 | 0.6493 |
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| 0.0132 | 18.0 | 16632 | 3.1830 | 0.6515 |
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| 0.0034 | 19.0 | 17556 | 3.1843 | 0.6474 |
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| 0.0796 | 20.0 | 18480 | 3.1823 | 0.6499 |
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### Framework versions
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- Transformers 4.35.0
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- Pytorch 2.1.0
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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