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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-80c
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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: 0.8043478260869565
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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-80c
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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: 0.7032
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- Accuracy: 0.8043
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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: 0.15
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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 | 1.3860 | 0.2391 |
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| 1.3859 | 2.0 | 13 | 1.3844 | 0.3043 |
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| 1.3859 | 2.92 | 19 | 1.3820 | 0.1957 |
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| 1.381 | 4.0 | 26 | 1.3746 | 0.1739 |
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| 1.3573 | 4.92 | 32 | 1.3643 | 0.1957 |
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| 1.3573 | 6.0 | 39 | 1.3561 | 0.1522 |
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| 1.2692 | 6.92 | 45 | 1.3583 | 0.1522 |
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| 1.1682 | 8.0 | 52 | 1.3623 | 0.1739 |
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| 1.1682 | 8.92 | 58 | 1.3296 | 0.2609 |
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| 1.1005 | 10.0 | 65 | 1.2663 | 0.3913 |
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| 0.9884 | 10.92 | 71 | 1.3160 | 0.3696 |
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| 0.9884 | 12.0 | 78 | 1.1806 | 0.4783 |
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| 0.9111 | 12.92 | 84 | 1.1560 | 0.6087 |
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| 0.8464 | 14.0 | 91 | 1.1350 | 0.5870 |
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| 0.8464 | 14.92 | 97 | 1.0768 | 0.6304 |
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| 0.7768 | 16.0 | 104 | 0.9707 | 0.6087 |
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| 0.6754 | 16.92 | 110 | 0.9544 | 0.6522 |
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| 0.6754 | 18.0 | 117 | 0.9885 | 0.6739 |
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| 0.657 | 18.92 | 123 | 0.8578 | 0.6957 |
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| 0.5408 | 20.0 | 130 | 0.7794 | 0.7391 |
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| 0.5408 | 20.92 | 136 | 0.8072 | 0.7391 |
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| 0.5094 | 22.0 | 143 | 0.7917 | 0.6739 |
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| 0.5094 | 22.92 | 149 | 0.7975 | 0.6739 |
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| 0.4546 | 24.0 | 156 | 0.7583 | 0.7609 |
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| 0.3722 | 24.92 | 162 | 0.7074 | 0.7826 |
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| 0.3722 | 26.0 | 169 | 0.6909 | 0.7391 |
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| 0.3494 | 26.92 | 175 | 0.7032 | 0.8043 |
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| 0.3092 | 28.0 | 182 | 0.8149 | 0.7826 |
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| 0.3092 | 28.92 | 188 | 0.7898 | 0.7826 |
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| 0.2643 | 30.0 | 195 | 0.7312 | 0.8043 |
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| 0.2659 | 30.92 | 201 | 0.7598 | 0.7174 |
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| 0.2659 | 32.0 | 208 | 0.7531 | 0.7609 |
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| 0.2298 | 32.92 | 214 | 0.6877 | 0.8043 |
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| 0.2147 | 34.0 | 221 | 0.6864 | 0.8043 |
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| 0.2147 | 34.92 | 227 | 0.7656 | 0.7391 |
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| 0.2457 | 36.0 | 234 | 0.8494 | 0.7391 |
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| 0.1905 | 36.92 | 240 | 0.7319 | 0.7609 |
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| 0.1905 | 38.0 | 247 | 0.8290 | 0.6957 |
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| 0.2073 | 38.92 | 253 | 0.7963 | 0.7609 |
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| 0.1603 | 40.0 | 260 | 0.8693 | 0.6957 |
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| 0.1603 | 40.92 | 266 | 0.7138 | 0.8043 |
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| 0.1852 | 42.0 | 273 | 0.7274 | 0.7609 |
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| 0.1852 | 42.92 | 279 | 0.8353 | 0.6739 |
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| 0.1641 | 44.0 | 286 | 0.9382 | 0.6957 |
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| 0.1568 | 44.92 | 292 | 0.8655 | 0.7174 |
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| 0.1568 | 46.0 | 299 | 0.7621 | 0.7391 |
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| 0.1498 | 46.92 | 305 | 0.7944 | 0.7174 |
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| 0.1563 | 48.0 | 312 | 0.8433 | 0.6957 |
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| 0.1563 | 48.92 | 318 | 0.8633 | 0.7609 |
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| 0.1554 | 50.0 | 325 | 0.8543 | 0.7391 |
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| 0.1316 | 50.92 | 331 | 0.9127 | 0.7174 |
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| 0.1316 | 52.0 | 338 | 0.9248 | 0.6957 |
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| 0.1264 | 52.92 | 344 | 0.9349 | 0.6957 |
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| 0.1082 | 54.0 | 351 | 0.9785 | 0.6739 |
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| 0.1082 | 54.92 | 357 | 1.0165 | 0.6739 |
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| 0.1366 | 56.0 | 364 | 0.8369 | 0.6957 |
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| 0.1546 | 56.92 | 370 | 0.8372 | 0.7174 |
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| 0.1546 | 58.0 | 377 | 0.8596 | 0.6957 |
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| 0.1218 | 58.92 | 383 | 0.8054 | 0.7174 |
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| 0.1162 | 60.0 | 390 | 0.7963 | 0.7391 |
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| 0.1162 | 60.92 | 396 | 0.7953 | 0.7391 |
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| 0.0876 | 62.0 | 403 | 0.8229 | 0.7391 |
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| 0.0876 | 62.92 | 409 | 0.8365 | 0.7391 |
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| 0.1032 | 64.0 | 416 | 0.8162 | 0.7609 |
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| 0.0825 | 64.92 | 422 | 0.8646 | 0.7391 |
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| 0.0825 | 66.0 | 429 | 0.9135 | 0.7391 |
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| 0.1119 | 66.92 | 435 | 0.9164 | 0.7391 |
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| 0.0949 | 68.0 | 442 | 0.9232 | 0.7391 |
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| 0.0949 | 68.92 | 448 | 0.9381 | 0.7391 |
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| 0.1227 | 70.0 | 455 | 0.8998 | 0.7391 |
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| 0.0872 | 70.92 | 461 | 0.9632 | 0.7174 |
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| 0.0872 | 72.0 | 468 | 0.8566 | 0.7174 |
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| 0.1033 | 72.92 | 474 | 0.8909 | 0.7174 |
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| 0.0876 | 73.85 | 480 | 0.8869 | 0.7609 |
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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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