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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-ve-U13-b-80
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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: 0.8260869565217391
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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-ve-U13-b-80
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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: 0.7132
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- Accuracy: 0.8261
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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: 0.0002
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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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: 80
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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 | 0.92 | 6 | 1.3859 | 0.2391 |
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| 1.3857 | 2.0 | 13 | 1.3834 | 0.2826 |
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| 1.3857 | 2.92 | 19 | 1.3789 | 0.1957 |
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| 1.3767 | 4.0 | 26 | 1.3666 | 0.1522 |
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| 1.3226 | 4.92 | 32 | 1.3565 | 0.1522 |
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| 1.3226 | 6.0 | 39 | 1.3902 | 0.1087 |
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| 1.1987 | 6.92 | 45 | 1.3712 | 0.2174 |
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| 1.1075 | 8.0 | 52 | 1.3197 | 0.3478 |
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| 1.1075 | 8.92 | 58 | 1.3649 | 0.3696 |
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| 0.9988 | 10.0 | 65 | 1.2583 | 0.3696 |
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| 0.8863 | 10.92 | 71 | 1.2484 | 0.3696 |
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| 0.8863 | 12.0 | 78 | 1.2869 | 0.4130 |
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| 0.8228 | 12.92 | 84 | 1.1678 | 0.4783 |
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| 0.7456 | 14.0 | 91 | 1.0275 | 0.6739 |
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| 0.7456 | 14.92 | 97 | 0.9702 | 0.7174 |
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| 0.6595 | 16.0 | 104 | 0.9103 | 0.6957 |
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| 0.5995 | 16.92 | 110 | 0.8506 | 0.7391 |
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| 0.5995 | 18.0 | 117 | 0.8514 | 0.7174 |
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| 0.5826 | 18.92 | 123 | 0.8964 | 0.7391 |
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| 0.4818 | 20.0 | 130 | 0.8550 | 0.7609 |
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| 0.4818 | 20.92 | 136 | 0.7132 | 0.8261 |
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| 0.4553 | 22.0 | 143 | 0.6973 | 0.7826 |
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| 0.4553 | 22.92 | 149 | 0.7496 | 0.7391 |
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| 0.4276 | 24.0 | 156 | 0.9087 | 0.6957 |
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| 0.3375 | 24.92 | 162 | 0.7787 | 0.8261 |
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| 0.3375 | 26.0 | 169 | 0.7132 | 0.8043 |
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| 0.3199 | 26.92 | 175 | 0.7570 | 0.7391 |
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| 0.2756 | 28.0 | 182 | 0.7873 | 0.6957 |
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| 0.2756 | 28.92 | 188 | 0.7895 | 0.7609 |
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| 0.2254 | 30.0 | 195 | 0.7443 | 0.8043 |
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| 0.2576 | 30.92 | 201 | 0.9623 | 0.6739 |
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| 0.2576 | 32.0 | 208 | 0.7349 | 0.7826 |
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| 0.2113 | 32.92 | 214 | 0.7887 | 0.7609 |
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| 0.1978 | 34.0 | 221 | 0.8921 | 0.7391 |
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| 0.1978 | 34.92 | 227 | 0.8102 | 0.7391 |
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| 0.2455 | 36.0 | 234 | 0.8947 | 0.7391 |
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| 0.1809 | 36.92 | 240 | 0.8144 | 0.7826 |
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| 0.1809 | 38.0 | 247 | 0.8290 | 0.7174 |
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| 0.1967 | 38.92 | 253 | 0.8135 | 0.7391 |
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| 0.1608 | 40.0 | 260 | 0.8065 | 0.7609 |
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| 0.1608 | 40.92 | 266 | 0.7399 | 0.7609 |
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| 0.1704 | 42.0 | 273 | 0.7099 | 0.8043 |
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| 0.1704 | 42.92 | 279 | 0.7569 | 0.7826 |
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| 0.1682 | 44.0 | 286 | 0.8459 | 0.7826 |
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| 0.1607 | 44.92 | 292 | 0.7311 | 0.7609 |
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| 0.1607 | 46.0 | 299 | 0.7833 | 0.7174 |
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| 0.1589 | 46.92 | 305 | 0.8073 | 0.6957 |
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| 0.1524 | 48.0 | 312 | 0.7473 | 0.7609 |
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| 0.1524 | 48.92 | 318 | 0.6780 | 0.8043 |
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| 0.1586 | 50.0 | 325 | 0.7573 | 0.7174 |
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| 0.128 | 50.92 | 331 | 0.7614 | 0.7391 |
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| 0.128 | 52.0 | 338 | 0.7338 | 0.7609 |
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| 0.1254 | 52.92 | 344 | 0.7666 | 0.7391 |
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| 0.1206 | 54.0 | 351 | 0.8433 | 0.7174 |
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| 0.1206 | 54.92 | 357 | 0.8747 | 0.6957 |
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| 0.1398 | 56.0 | 364 | 0.8940 | 0.7174 |
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| 0.1536 | 56.92 | 370 | 0.7781 | 0.7826 |
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| 0.1536 | 58.0 | 377 | 0.7351 | 0.7391 |
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| 0.1281 | 58.92 | 383 | 0.7601 | 0.7174 |
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| 0.1156 | 60.0 | 390 | 0.7991 | 0.7174 |
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| 0.1156 | 60.92 | 396 | 0.7776 | 0.7609 |
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| 0.0852 | 62.0 | 403 | 0.7838 | 0.7391 |
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| 0.0852 | 62.92 | 409 | 0.7752 | 0.7609 |
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| 0.1106 | 64.0 | 416 | 0.7541 | 0.7609 |
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| 0.0817 | 64.92 | 422 | 0.7536 | 0.7391 |
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| 0.0817 | 66.0 | 429 | 0.8129 | 0.7609 |
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| 0.1211 | 66.92 | 435 | 0.7884 | 0.7609 |
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| 0.0944 | 68.0 | 442 | 0.8011 | 0.7609 |
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| 0.0944 | 68.92 | 448 | 0.8068 | 0.7391 |
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| 0.1187 | 70.0 | 455 | 0.7796 | 0.7391 |
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| 0.0935 | 70.92 | 461 | 0.7934 | 0.7391 |
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| 0.0935 | 72.0 | 468 | 0.7367 | 0.7391 |
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| 0.109 | 72.92 | 474 | 0.7515 | 0.7391 |
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| 0.1006 | 73.85 | 480 | 0.7888 | 0.7174 |
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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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