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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_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: 0.5623306233062331
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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_fold4
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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: 3.5379
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- Accuracy: 0.5623
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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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| 1.4184 | 1.0 | 923 | 1.5125 | 0.4894 |
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| 1.1581 | 2.0 | 1846 | 1.3440 | 0.5398 |
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| 1.0675 | 3.0 | 2769 | 1.2921 | 0.5683 |
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| 0.9984 | 4.0 | 3692 | 1.3169 | 0.5756 |
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| 0.6437 | 5.0 | 4615 | 1.3971 | 0.5629 |
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| 0.491 | 6.0 | 5538 | 1.5307 | 0.5547 |
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| 0.3697 | 7.0 | 6461 | 1.6679 | 0.5615 |
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| 0.2372 | 8.0 | 7384 | 1.9476 | 0.5461 |
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| 0.0824 | 9.0 | 8307 | 2.1631 | 0.5531 |
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| 0.0471 | 10.0 | 9230 | 2.4822 | 0.5485 |
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| 0.0645 | 11.0 | 10153 | 2.7301 | 0.5523 |
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| 0.0461 | 12.0 | 11076 | 2.8827 | 0.5588 |
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| 0.0021 | 13.0 | 11999 | 3.1615 | 0.5575 |
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| 0.0011 | 14.0 | 12922 | 3.1796 | 0.5612 |
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| 0.0141 | 15.0 | 13845 | 3.2737 | 0.5566 |
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| 0.0004 | 16.0 | 14768 | 3.3570 | 0.5593 |
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| 0.0004 | 17.0 | 15691 | 3.4150 | 0.5621 |
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| 0.0003 | 18.0 | 16614 | 3.4800 | 0.5615 |
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| 0.0002 | 19.0 | 17537 | 3.5180 | 0.5615 |
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| 0.0002 | 20.0 | 18460 | 3.5379 | 0.5623 |
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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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