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swiftformer-xs-ve-U13-b-80d

Image Classification
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swiftformer
Generated from Trainer
Eval Results
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  2. model.safetensors +1 -1
  3. runs/Jun12_16-54-21_DESKTOP-SKBE9FB/events.out.tfevents.1718232862.DESKTOP-SKBE9FB.13132.0 +2 -2
README.md ADDED
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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-80d
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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: 0.6739130434782609
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+ ---
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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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+
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+ # swiftformer-xs-ve-U13-b-80d
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+
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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: 1.0773
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+ - Accuracy: 0.6739
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 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: 0.05
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+ - num_epochs: 70
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.92 | 6 | 1.3848 | 0.2174 |
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+ | 1.3838 | 2.0 | 13 | 1.3723 | 0.1957 |
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+ | 1.3838 | 2.92 | 19 | 1.3540 | 0.1739 |
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+ | 1.3023 | 4.0 | 26 | 1.3327 | 0.2391 |
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+ | 1.1398 | 4.92 | 32 | 1.2555 | 0.2391 |
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+ | 1.1398 | 6.0 | 39 | 1.3010 | 0.3913 |
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+ | 1.0076 | 6.92 | 45 | 1.1957 | 0.5 |
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+ | 0.8823 | 8.0 | 52 | 1.0565 | 0.5870 |
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+ | 0.8823 | 8.92 | 58 | 0.9410 | 0.7391 |
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+ | 0.7637 | 10.0 | 65 | 0.9274 | 0.7391 |
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+ | 0.6688 | 10.92 | 71 | 0.8492 | 0.7826 |
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+ | 0.6688 | 12.0 | 78 | 0.8906 | 0.6739 |
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+ | 0.5855 | 12.92 | 84 | 0.8929 | 0.6522 |
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+ | 0.4921 | 14.0 | 91 | 0.8338 | 0.7391 |
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+ | 0.4921 | 14.92 | 97 | 0.7686 | 0.7826 |
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+ | 0.4318 | 16.0 | 104 | 0.8430 | 0.7609 |
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+ | 0.386 | 16.92 | 110 | 0.8315 | 0.7826 |
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+ | 0.386 | 18.0 | 117 | 0.7669 | 0.8261 |
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+ | 0.3483 | 18.92 | 123 | 0.8347 | 0.7174 |
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+ | 0.3023 | 20.0 | 130 | 1.1037 | 0.6304 |
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+ | 0.3023 | 20.92 | 136 | 0.9024 | 0.7174 |
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+ | 0.2973 | 22.0 | 143 | 0.7760 | 0.7826 |
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+ | 0.2973 | 22.92 | 149 | 0.7400 | 0.7826 |
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+ | 0.2529 | 24.0 | 156 | 1.0058 | 0.7174 |
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+ | 0.2086 | 24.92 | 162 | 0.9260 | 0.7609 |
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+ | 0.2086 | 26.0 | 169 | 0.8370 | 0.7174 |
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+ | 0.2265 | 26.92 | 175 | 0.8060 | 0.7391 |
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+ | 0.1942 | 28.0 | 182 | 0.9812 | 0.6957 |
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+ | 0.1942 | 28.92 | 188 | 0.8996 | 0.7391 |
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+ | 0.1708 | 30.0 | 195 | 0.9630 | 0.6957 |
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+ | 0.1747 | 30.92 | 201 | 0.9691 | 0.7174 |
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+ | 0.1747 | 32.0 | 208 | 1.0017 | 0.7391 |
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+ | 0.1461 | 32.92 | 214 | 0.9965 | 0.6957 |
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+ | 0.1457 | 34.0 | 221 | 0.9506 | 0.7391 |
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+ | 0.1457 | 34.92 | 227 | 0.9834 | 0.7391 |
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+ | 0.1814 | 36.0 | 234 | 1.0191 | 0.7609 |
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+ | 0.1383 | 36.92 | 240 | 0.8807 | 0.7609 |
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+ | 0.1383 | 38.0 | 247 | 0.8724 | 0.7609 |
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+ | 0.1718 | 38.92 | 253 | 0.8090 | 0.7391 |
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+ | 0.1289 | 40.0 | 260 | 0.8709 | 0.7609 |
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+ | 0.1289 | 40.92 | 266 | 0.9704 | 0.7391 |
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+ | 0.1193 | 42.0 | 273 | 1.0518 | 0.7391 |
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+ | 0.1193 | 42.92 | 279 | 1.0157 | 0.7174 |
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+ | 0.1224 | 44.0 | 286 | 1.0794 | 0.7391 |
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+ | 0.1104 | 44.92 | 292 | 1.0402 | 0.7391 |
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+ | 0.1104 | 46.0 | 299 | 0.9837 | 0.7609 |
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+ | 0.1055 | 46.92 | 305 | 1.0323 | 0.7174 |
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+ | 0.1242 | 48.0 | 312 | 0.9907 | 0.7391 |
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+ | 0.1242 | 48.92 | 318 | 1.0436 | 0.7609 |
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+ | 0.1283 | 50.0 | 325 | 0.9829 | 0.7391 |
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+ | 0.1035 | 50.92 | 331 | 1.0400 | 0.7174 |
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+ | 0.1035 | 52.0 | 338 | 1.0414 | 0.7174 |
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+ | 0.1066 | 52.92 | 344 | 1.0958 | 0.6957 |
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+ | 0.0863 | 54.0 | 351 | 1.0914 | 0.7174 |
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+ | 0.0863 | 54.92 | 357 | 1.0816 | 0.7174 |
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+ | 0.1062 | 56.0 | 364 | 1.0087 | 0.7174 |
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+ | 0.1214 | 56.92 | 370 | 1.0454 | 0.7391 |
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+ | 0.1214 | 58.0 | 377 | 1.0324 | 0.7391 |
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+ | 0.0984 | 58.92 | 383 | 1.0591 | 0.6739 |
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+ | 0.0966 | 60.0 | 390 | 1.0037 | 0.6957 |
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+ | 0.0966 | 60.92 | 396 | 0.9887 | 0.6957 |
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+ | 0.0626 | 62.0 | 403 | 1.0294 | 0.6739 |
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+ | 0.0626 | 62.92 | 409 | 0.9939 | 0.7174 |
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+ | 0.085 | 64.0 | 416 | 0.9886 | 0.6957 |
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+ | 0.068 | 64.62 | 420 | 1.0773 | 0.6739 |
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+
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+
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+ ### Framework versions
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+
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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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