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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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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: swiftformer-xs-dmae-va-U5-42
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+ results: []
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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-dmae-va-U5-42
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0447
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+ - Accuracy: 0.55
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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: 5e-05
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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: 42
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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 | 0.9 | 7 | 1.3144 | 0.4833 |
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+ | 1.3947 | 1.94 | 15 | 1.3154 | 0.4 |
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+ | 1.3947 | 2.97 | 23 | 1.2849 | 0.4167 |
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+ | 1.3608 | 4.0 | 31 | 1.2512 | 0.4667 |
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+ | 1.3048 | 4.9 | 38 | 1.2340 | 0.55 |
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+ | 1.3048 | 5.94 | 46 | 1.2118 | 0.5833 |
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+ | 1.2456 | 6.97 | 54 | 1.2077 | 0.55 |
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+ | 1.186 | 8.0 | 62 | 1.1672 | 0.5333 |
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+ | 1.186 | 8.9 | 69 | 1.1565 | 0.6167 |
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+ | 1.1218 | 9.94 | 77 | 1.1532 | 0.5833 |
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+ | 1.0731 | 10.97 | 85 | 1.1304 | 0.5833 |
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+ | 1.0731 | 12.0 | 93 | 1.1664 | 0.5167 |
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+ | 1.0135 | 12.9 | 100 | 1.1222 | 0.55 |
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+ | 0.9783 | 13.94 | 108 | 1.1404 | 0.5333 |
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+ | 0.9783 | 14.97 | 116 | 1.1022 | 0.5833 |
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+ | 0.9195 | 16.0 | 124 | 1.0996 | 0.55 |
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+ | 0.9195 | 16.9 | 131 | 1.0715 | 0.6 |
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+ | 0.9023 | 17.94 | 139 | 1.0779 | 0.5833 |
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+ | 0.8575 | 18.97 | 147 | 1.0797 | 0.5667 |
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+ | 0.8575 | 20.0 | 155 | 1.0508 | 0.5833 |
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+ | 0.8519 | 20.9 | 162 | 1.0500 | 0.5833 |
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+ | 0.8098 | 21.94 | 170 | 1.0212 | 0.5667 |
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+ | 0.8098 | 22.97 | 178 | 1.0041 | 0.5833 |
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+ | 0.8018 | 24.0 | 186 | 1.0197 | 0.5667 |
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+ | 0.7709 | 24.9 | 193 | 1.0283 | 0.5333 |
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+ | 0.7709 | 25.94 | 201 | 1.0303 | 0.55 |
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+ | 0.7642 | 26.97 | 209 | 1.0100 | 0.5833 |
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+ | 0.7322 | 28.0 | 217 | 1.0475 | 0.5333 |
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+ | 0.7322 | 28.9 | 224 | 1.0667 | 0.55 |
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+ | 0.7245 | 29.94 | 232 | 1.0743 | 0.55 |
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+ | 0.7254 | 30.97 | 240 | 1.0416 | 0.5333 |
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+ | 0.7254 | 32.0 | 248 | 1.0664 | 0.5667 |
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+ | 0.7201 | 32.9 | 255 | 1.0393 | 0.55 |
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+ | 0.7201 | 33.94 | 263 | 1.0284 | 0.55 |
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+ | 0.6968 | 34.97 | 271 | 1.0420 | 0.55 |
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+ | 0.7073 | 36.0 | 279 | 1.0396 | 0.5333 |
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+ | 0.7073 | 36.9 | 286 | 1.0640 | 0.55 |
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+ | 0.6891 | 37.94 | 294 | 1.0447 | 0.55 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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