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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: 0.8695652173913043
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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: 0.6163
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- Accuracy: 0.8696
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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 | 1.4461 | 0.1087 |
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| 1.3993 | 2.0 | 13 | 1.4435 | 0.1087 |
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| 1.3993 | 2.92 | 19 | 1.4389 | 0.1087 |
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| 1.3849 | 4.0 | 26 | 1.4284 | 0.1087 |
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| 1.3287 | 4.92 | 32 | 1.4223 | 0.1304 |
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| 1.3287 | 6.0 | 39 | 1.4647 | 0.1087 |
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| 1.2128 | 6.92 | 45 | 1.4184 | 0.1739 |
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| 1.122 | 8.0 | 52 | 1.3262 | 0.1957 |
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| 1.122 | 8.92 | 58 | 1.3298 | 0.1957 |
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| 1.0062 | 10.0 | 65 | 1.2035 | 0.3696 |
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| 0.872 | 10.92 | 71 | 1.3667 | 0.3261 |
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| 0.872 | 12.0 | 78 | 1.2013 | 0.4348 |
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| 0.814 | 12.92 | 84 | 0.9996 | 0.6957 |
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| 0.7228 | 14.0 | 91 | 0.9706 | 0.7609 |
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| 0.7228 | 14.92 | 97 | 0.9295 | 0.7391 |
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| 0.6473 | 16.0 | 104 | 0.8988 | 0.7174 |
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| 0.5696 | 16.92 | 110 | 0.9612 | 0.6739 |
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| 0.5696 | 18.0 | 117 | 0.8713 | 0.7609 |
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| 0.5546 | 18.92 | 123 | 0.8050 | 0.7609 |
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| 0.4747 | 20.0 | 130 | 0.7725 | 0.7609 |
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| 0.4747 | 20.92 | 136 | 0.7933 | 0.6957 |
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| 0.4393 | 22.0 | 143 | 0.7665 | 0.6957 |
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| 0.4393 | 22.92 | 149 | 0.7886 | 0.7174 |
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| 0.4077 | 24.0 | 156 | 0.7824 | 0.7391 |
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| 0.3326 | 24.92 | 162 | 0.7021 | 0.7391 |
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| 0.3326 | 26.0 | 169 | 0.6346 | 0.8261 |
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| 0.315 | 26.92 | 175 | 0.6163 | 0.8696 |
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| 0.2729 | 28.0 | 182 | 0.6938 | 0.8043 |
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| 0.2729 | 28.92 | 188 | 0.7417 | 0.8043 |
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| 0.2218 | 30.0 | 195 | 0.6669 | 0.7826 |
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| 0.2499 | 30.92 | 201 | 0.7111 | 0.7174 |
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| 0.2499 | 32.0 | 208 | 0.6730 | 0.7826 |
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| 0.2218 | 32.92 | 214 | 0.6512 | 0.8043 |
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| 0.2037 | 34.0 | 221 | 0.7165 | 0.7391 |
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| 0.2037 | 34.92 | 227 | 0.6300 | 0.8261 |
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| 0.2367 | 36.0 | 234 | 0.7421 | 0.7826 |
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| 0.1835 | 36.92 | 240 | 0.6644 | 0.8043 |
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| 0.1835 | 38.0 | 247 | 0.6251 | 0.8261 |
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| 0.2073 | 38.92 | 253 | 0.6431 | 0.7826 |
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| 0.1643 | 40.0 | 260 | 0.6348 | 0.8043 |
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| 0.1643 | 40.92 | 266 | 0.6192 | 0.8043 |
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| 0.1685 | 42.0 | 273 | 0.6753 | 0.8043 |
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| 0.1685 | 42.92 | 279 | 0.7440 | 0.7826 |
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| 0.1539 | 44.0 | 286 | 0.7505 | 0.8043 |
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| 0.1658 | 44.92 | 292 | 0.6331 | 0.8261 |
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| 0.1658 | 46.0 | 299 | 0.6550 | 0.8043 |
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| 0.1596 | 46.92 | 305 | 0.6824 | 0.8043 |
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| 0.1534 | 48.0 | 312 | 0.6971 | 0.8043 |
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| 0.1534 | 48.92 | 318 | 0.6347 | 0.8261 |
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| 0.1677 | 50.0 | 325 | 0.6392 | 0.8261 |
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| 0.1453 | 50.92 | 331 | 0.6369 | 0.8043 |
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| 0.1453 | 52.0 | 338 | 0.6230 | 0.7826 |
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| 0.1385 | 52.92 | 344 | 0.6432 | 0.7609 |
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| 0.1221 | 54.0 | 351 | 0.6757 | 0.7391 |
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| 0.1221 | 54.92 | 357 | 0.7383 | 0.7609 |
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| 0.1433 | 56.0 | 364 | 0.7100 | 0.7609 |
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| 0.1567 | 56.92 | 370 | 0.6862 | 0.7609 |
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| 0.1567 | 58.0 | 377 | 0.6654 | 0.7609 |
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| 0.1361 | 58.92 | 383 | 0.6665 | 0.7826 |
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| 0.1157 | 60.0 | 390 | 0.6439 | 0.7826 |
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| 0.1157 | 60.92 | 396 | 0.6306 | 0.8261 |
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| 0.0934 | 62.0 | 403 | 0.6546 | 0.8043 |
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| 0.0934 | 62.92 | 409 | 0.6651 | 0.8043 |
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| 0.1123 | 64.0 | 416 | 0.6568 | 0.7609 |
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| 0.0855 | 64.92 | 422 | 0.6507 | 0.7609 |
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| 0.0855 | 66.0 | 429 | 0.6667 | 0.8043 |
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| 0.1135 | 66.92 | 435 | 0.6516 | 0.7826 |
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| 0.0932 | 68.0 | 442 | 0.6596 | 0.8043 |
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| 0.0932 | 68.92 | 448 | 0.6772 | 0.8043 |
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| 0.1228 | 70.0 | 455 | 0.6526 | 0.7609 |
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| 0.0878 | 70.92 | 461 | 0.6731 | 0.8261 |
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| 0.0878 | 72.0 | 468 | 0.6351 | 0.7826 |
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| 0.1073 | 72.92 | 474 | 0.6269 | 0.7826 |
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| 0.1028 | 73.85 | 480 | 0.6743 | 0.7826 |
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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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