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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_3Class_RMSprop_1-e5_20Epoch_Beit-base-patch16_fold4
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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: 0.8233062330623306
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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_3Class_RMSprop_1-e5_20Epoch_Beit-base-patch16_fold4
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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: 1.8083
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- Accuracy: 0.8233
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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: 1e-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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- 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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| 0.3492 | 1.0 | 923 | 0.4516 | 0.8087 |
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| 0.3947 | 2.0 | 1846 | 0.4372 | 0.8144 |
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| 0.3321 | 3.0 | 2769 | 0.4856 | 0.8220 |
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| 0.1372 | 4.0 | 3692 | 0.6093 | 0.8271 |
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| 0.2202 | 5.0 | 4615 | 0.8876 | 0.8184 |
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| 0.0611 | 6.0 | 5538 | 1.1112 | 0.8222 |
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| 0.0654 | 7.0 | 6461 | 1.2516 | 0.8241 |
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| 0.0494 | 8.0 | 7384 | 1.5011 | 0.8209 |
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| 0.0614 | 9.0 | 8307 | 1.3879 | 0.8190 |
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| 0.1723 | 10.0 | 9230 | 1.5852 | 0.8160 |
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| 0.0314 | 11.0 | 10153 | 1.7058 | 0.8209 |
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| 0.006 | 12.0 | 11076 | 1.7427 | 0.8233 |
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| 0.0603 | 13.0 | 11999 | 1.6775 | 0.8206 |
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| 0.0734 | 14.0 | 12922 | 1.7302 | 0.8257 |
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| 0.0185 | 15.0 | 13845 | 1.7895 | 0.8236 |
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| 0.0006 | 16.0 | 14768 | 1.7889 | 0.8220 |
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| 0.0006 | 17.0 | 15691 | 1.8447 | 0.8198 |
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| 0.0003 | 18.0 | 16614 | 1.8183 | 0.8184 |
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| 0.0002 | 19.0 | 17537 | 1.8137 | 0.8176 |
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| 0.0 | 20.0 | 18460 | 1.8083 | 0.8233 |
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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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