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---
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base_model: MBZUAI/swiftformer-xs
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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: swiftformer-xs-DMAE
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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: validation
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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: 0.10869565217391304
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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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# swiftformer-xs-DMAE
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This model is a fine-tuned version of [MBZUAI/swiftformer-xs](https://huggingface.co/MBZUAI/swiftformer-xs) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 113.8184
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- Accuracy: 0.1087
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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: 0.0003
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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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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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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: 40
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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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| No log | 0.86 | 3 | 113.8184 | 0.1087 |
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| No log | 2.0 | 7 | 113.8094 | 0.1087 |
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| 114.0867 | 2.86 | 10 | 113.7944 | 0.1087 |
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| 114.0867 | 4.0 | 14 | 113.7881 | 0.1087 |
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| 114.0867 | 4.86 | 17 | 113.7100 | 0.1087 |
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| 113.3425 | 6.0 | 21 | 113.5884 | 0.1087 |
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| 113.3425 | 6.86 | 24 | 113.4998 | 0.1087 |
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| 113.3425 | 8.0 | 28 | 113.0578 | 0.1087 |
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| 111.228 | 8.86 | 31 | 112.8053 | 0.1087 |
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| 111.228 | 10.0 | 35 | 112.5202 | 0.1087 |
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| 111.228 | 10.86 | 38 | 112.5811 | 0.1087 |
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| 114.9647 | 12.0 | 42 | 112.6090 | 0.1087 |
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| 114.9647 | 12.86 | 45 | 112.4973 | 0.1087 |
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| 114.9647 | 14.0 | 49 | 111.9761 | 0.1087 |
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| 110.7738 | 14.86 | 52 | 111.8117 | 0.1087 |
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| 110.7738 | 16.0 | 56 | 111.6589 | 0.1087 |
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| 110.7738 | 16.86 | 59 | 111.5367 | 0.1087 |
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| 111.0505 | 18.0 | 63 | 111.7016 | 0.1087 |
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| 111.0505 | 18.86 | 66 | 111.9068 | 0.1087 |
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| 111.4545 | 20.0 | 70 | 111.6203 | 0.1087 |
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| 111.4545 | 20.86 | 73 | 111.1266 | 0.1087 |
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| 111.4545 | 22.0 | 77 | 110.2879 | 0.1087 |
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| 111.2779 | 22.86 | 80 | 109.8523 | 0.1087 |
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| 111.2779 | 24.0 | 84 | 109.5283 | 0.1087 |
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| 111.2779 | 24.86 | 87 | 109.9590 | 0.1087 |
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| 110.5166 | 26.0 | 91 | 109.9752 | 0.1087 |
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| 110.5166 | 26.86 | 94 | 109.5435 | 0.1087 |
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| 110.5166 | 28.0 | 98 | 109.5712 | 0.1087 |
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| 108.66 | 28.86 | 101 | 108.8924 | 0.1087 |
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| 108.66 | 30.0 | 105 | 108.3990 | 0.1087 |
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| 108.66 | 30.86 | 108 | 108.7050 | 0.1087 |
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| 109.688 | 32.0 | 112 | 108.7237 | 0.1087 |
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| 109.688 | 32.86 | 115 | 109.0679 | 0.1087 |
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| 109.688 | 34.0 | 119 | 108.5750 | 0.1087 |
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| 109.4549 | 34.29 | 120 | 108.5167 | 0.1087 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.1.2+cu118
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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