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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_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: 0.8259571001900624
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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_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: 1.7955
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- Accuracy: 0.8260
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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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| 0.4439 | 1.0 | 924 | 0.4590 | 0.8091 |
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| 0.3875 | 2.0 | 1848 | 0.4469 | 0.8227 |
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| 0.2939 | 3.0 | 2772 | 0.5412 | 0.8154 |
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| 0.1247 | 4.0 | 3696 | 0.6692 | 0.8213 |
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| 0.1513 | 5.0 | 4620 | 0.8256 | 0.8227 |
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| 0.1409 | 6.0 | 5544 | 1.1386 | 0.8181 |
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| 0.0278 | 7.0 | 6468 | 1.3459 | 0.8189 |
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| 0.013 | 8.0 | 7392 | 1.5383 | 0.8175 |
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| 0.0037 | 9.0 | 8316 | 1.5542 | 0.8254 |
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| 0.0119 | 10.0 | 9240 | 1.6982 | 0.8178 |
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| 0.0008 | 11.0 | 10164 | 1.7834 | 0.8178 |
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| 0.0799 | 12.0 | 11088 | 1.6908 | 0.8230 |
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| 0.0845 | 13.0 | 12012 | 1.7310 | 0.8200 |
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| 0.0588 | 14.0 | 12936 | 1.7389 | 0.8235 |
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| 0.0004 | 15.0 | 13860 | 1.8086 | 0.8246 |
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| 0.0004 | 16.0 | 14784 | 1.8040 | 0.8262 |
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| 0.0009 | 17.0 | 15708 | 1.7272 | 0.8243 |
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| 0.0021 | 18.0 | 16632 | 1.7738 | 0.8238 |
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| 0.0559 | 19.0 | 17556 | 1.8013 | 0.8254 |
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| 0.0 | 20.0 | 18480 | 1.7955 | 0.8260 |
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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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