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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_SGD_1-e3_20Epoch_09Momentum_Beit-base-patch16_fold2
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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: 0.41702702702702704
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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_SGD_1-e3_20Epoch_09Momentum_Beit-base-patch16_fold2
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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: 1.8092
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- Accuracy: 0.4170
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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: 0.001
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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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| 2.364 | 1.0 | 923 | 2.4299 | 0.2108 |
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| 2.3719 | 2.0 | 1846 | 2.2817 | 0.2649 |
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| 2.2408 | 3.0 | 2769 | 2.1860 | 0.2889 |
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| 2.1829 | 4.0 | 3692 | 2.1102 | 0.3143 |
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| 2.0369 | 5.0 | 4615 | 2.0577 | 0.3241 |
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| 2.061 | 6.0 | 5538 | 2.0066 | 0.3419 |
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| 1.9167 | 7.0 | 6461 | 1.9797 | 0.3568 |
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| 2.0057 | 8.0 | 7384 | 1.9411 | 0.3673 |
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| 2.0098 | 9.0 | 8307 | 1.9258 | 0.3722 |
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| 1.9046 | 10.0 | 9230 | 1.9019 | 0.3822 |
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| 1.862 | 11.0 | 10153 | 1.8785 | 0.3922 |
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| 1.8051 | 12.0 | 11076 | 1.8624 | 0.3973 |
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| 1.8752 | 13.0 | 11999 | 1.8478 | 0.3981 |
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| 1.9831 | 14.0 | 12922 | 1.8389 | 0.4032 |
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| 1.8913 | 15.0 | 13845 | 1.8338 | 0.4051 |
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| 1.9373 | 16.0 | 14768 | 1.8269 | 0.4086 |
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| 1.8457 | 17.0 | 15691 | 1.8202 | 0.4089 |
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| 1.7936 | 18.0 | 16614 | 1.8117 | 0.4159 |
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| 1.7608 | 19.0 | 17537 | 1.8101 | 0.4168 |
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| 1.9672 | 20.0 | 18460 | 1.8092 | 0.4170 |
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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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