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---
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license: apache-2.0
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base_model: facebook/deit-tiny-patch16-224
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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_Adamax_1-e4_20Epoch_Deit-tiny-patch16_fold3
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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: 0.5695346320346321
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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_Adamax_1-e4_20Epoch_Deit-tiny-patch16_fold3
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This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.5040
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- Accuracy: 0.5695
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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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| 1.3705 | 1.0 | 923 | 1.4925 | 0.4968 |
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| 1.1741 | 2.0 | 1846 | 1.3247 | 0.5411 |
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| 1.1089 | 3.0 | 2769 | 1.2524 | 0.5777 |
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| 0.8912 | 4.0 | 3692 | 1.2699 | 0.5712 |
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| 0.6118 | 5.0 | 4615 | 1.3695 | 0.5725 |
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| 0.4514 | 6.0 | 5538 | 1.5162 | 0.5690 |
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| 0.3342 | 7.0 | 6461 | 1.6732 | 0.5641 |
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| 0.1558 | 8.0 | 7384 | 1.8402 | 0.5668 |
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| 0.139 | 9.0 | 8307 | 2.0769 | 0.5676 |
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| 0.0399 | 10.0 | 9230 | 2.4530 | 0.5582 |
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| 0.0251 | 11.0 | 10153 | 2.6195 | 0.5630 |
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| 0.0197 | 12.0 | 11076 | 2.8679 | 0.5598 |
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| 0.0022 | 13.0 | 11999 | 3.0450 | 0.5593 |
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| 0.0102 | 14.0 | 12922 | 3.1628 | 0.5614 |
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| 0.0226 | 15.0 | 13845 | 3.2622 | 0.5655 |
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| 0.0004 | 16.0 | 14768 | 3.3164 | 0.5668 |
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| 0.0003 | 17.0 | 15691 | 3.3759 | 0.5703 |
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| 0.0002 | 18.0 | 16614 | 3.4406 | 0.5687 |
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| 0.0002 | 19.0 | 17537 | 3.4891 | 0.5695 |
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| 0.0004 | 20.0 | 18460 | 3.5040 | 0.5695 |
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### Framework versions
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- Transformers 4.40.1
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- Pytorch 2.1.0
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- Datasets 2.19.0
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- Tokenizers 0.19.1
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