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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_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: 0.4277190127474912
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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_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: 1.7637
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- Accuracy: 0.4277
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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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| 2.3338 | 1.0 | 924 | 2.4489 | 0.2086 |
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| 2.3427 | 2.0 | 1848 | 2.3125 | 0.2517 |
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| 2.1284 | 3.0 | 2772 | 2.2064 | 0.2853 |
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| 2.0324 | 4.0 | 3696 | 2.1236 | 0.3106 |
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| 1.929 | 5.0 | 4620 | 2.0514 | 0.3369 |
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| 1.9691 | 6.0 | 5544 | 1.9984 | 0.3537 |
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| 2.0646 | 7.0 | 6468 | 1.9525 | 0.3653 |
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| 1.8686 | 8.0 | 7392 | 1.9172 | 0.3813 |
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| 1.972 | 9.0 | 8316 | 1.8843 | 0.3916 |
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| 2.0678 | 10.0 | 9240 | 1.8632 | 0.3973 |
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| 1.8342 | 11.0 | 10164 | 1.8414 | 0.3976 |
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| 1.9641 | 12.0 | 11088 | 1.8250 | 0.4057 |
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| 1.6663 | 13.0 | 12012 | 1.8107 | 0.4093 |
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| 1.7839 | 14.0 | 12936 | 1.7966 | 0.4193 |
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| 1.7724 | 15.0 | 13860 | 1.7857 | 0.4258 |
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| 1.7746 | 16.0 | 14784 | 1.7787 | 0.4245 |
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| 1.9266 | 17.0 | 15708 | 1.7714 | 0.4261 |
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| 1.8612 | 18.0 | 16632 | 1.7673 | 0.4280 |
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| 1.7224 | 19.0 | 17556 | 1.7664 | 0.4291 |
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| 1.7078 | 20.0 | 18480 | 1.7637 | 0.4277 |
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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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