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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_fold1
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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: 0.6532717893021993
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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_fold1
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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: 3.0645
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- Accuracy: 0.6533
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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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| 1.1014 | 1.0 | 924 | 1.1155 | 0.6131 |
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| 0.917 | 2.0 | 1848 | 1.0767 | 0.6242 |
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| 0.7533 | 3.0 | 2772 | 1.0565 | 0.6473 |
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| 0.493 | 4.0 | 3696 | 1.1952 | 0.6530 |
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| 0.482 | 5.0 | 4620 | 1.3688 | 0.6473 |
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| 0.1989 | 6.0 | 5544 | 1.6284 | 0.6435 |
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| 0.1622 | 7.0 | 6468 | 2.0114 | 0.6373 |
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| 0.0666 | 8.0 | 7392 | 2.2124 | 0.6541 |
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| 0.0417 | 9.0 | 8316 | 2.4424 | 0.6389 |
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| 0.0196 | 10.0 | 9240 | 2.5614 | 0.6397 |
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| 0.0323 | 11.0 | 10164 | 2.8070 | 0.6443 |
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| 0.0014 | 12.0 | 11088 | 2.8503 | 0.6506 |
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| 0.001 | 13.0 | 12012 | 2.8885 | 0.6497 |
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| 0.0706 | 14.0 | 12936 | 3.0224 | 0.6462 |
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| 0.0003 | 15.0 | 13860 | 3.0064 | 0.6465 |
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| 0.0013 | 16.0 | 14784 | 3.0115 | 0.6552 |
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| 0.0316 | 17.0 | 15708 | 3.0514 | 0.6563 |
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| 0.0002 | 18.0 | 16632 | 3.0348 | 0.6568 |
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| 0.0 | 19.0 | 17556 | 3.0737 | 0.6508 |
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| 0.0494 | 20.0 | 18480 | 3.0645 | 0.6533 |
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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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