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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_SGD_1-e3_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: 0.42884199134199136
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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_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: 1.7155
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- Accuracy: 0.4288
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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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| 2.4106 | 1.0 | 923 | 2.4578 | 0.2002 |
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| 2.3587 | 2.0 | 1846 | 2.2972 | 0.2516 |
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| 2.1274 | 3.0 | 2769 | 2.1627 | 0.3055 |
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| 2.1583 | 4.0 | 3692 | 2.0604 | 0.3279 |
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| 1.9036 | 5.0 | 4615 | 1.9842 | 0.3458 |
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| 1.7721 | 6.0 | 5538 | 1.9243 | 0.3582 |
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| 1.9867 | 7.0 | 6461 | 1.8782 | 0.3726 |
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| 1.8532 | 8.0 | 7384 | 1.8428 | 0.3891 |
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| 1.8503 | 9.0 | 8307 | 1.8165 | 0.4004 |
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| 1.79 | 10.0 | 9230 | 1.7943 | 0.4037 |
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| 1.7717 | 11.0 | 10153 | 1.7761 | 0.4091 |
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| 1.7696 | 12.0 | 11076 | 1.7613 | 0.4148 |
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| 1.7298 | 13.0 | 11999 | 1.7507 | 0.4191 |
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| 1.7468 | 14.0 | 12922 | 1.7401 | 0.4210 |
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| 1.6085 | 15.0 | 13845 | 1.7322 | 0.4229 |
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| 1.7188 | 16.0 | 14768 | 1.7257 | 0.4278 |
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| 1.7307 | 17.0 | 15691 | 1.7212 | 0.4259 |
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| 1.5257 | 18.0 | 16614 | 1.7177 | 0.4275 |
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| 1.6729 | 19.0 | 17537 | 1.7160 | 0.4294 |
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| 1.7293 | 20.0 | 18460 | 1.7155 | 0.4288 |
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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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