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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-U-SF |
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results: [] |
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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-dmae-va-U-SF |
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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: 0.6964 |
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- Accuracy: 0.7615 |
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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: 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: 40 |
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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 | 0.9 | 7 | 1.3887 | 0.3119 | |
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| 1.4383 | 1.94 | 15 | 1.3440 | 0.4128 | |
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| 1.3956 | 2.97 | 23 | 1.3159 | 0.3761 | |
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| 1.36 | 4.0 | 31 | 1.2907 | 0.3853 | |
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| 1.36 | 4.9 | 38 | 1.2488 | 0.4404 | |
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| 1.2912 | 5.94 | 46 | 1.2129 | 0.4037 | |
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| 1.2387 | 6.97 | 54 | 1.1734 | 0.4679 | |
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| 1.1607 | 8.0 | 62 | 1.1436 | 0.5138 | |
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| 1.1607 | 8.9 | 69 | 1.0991 | 0.4954 | |
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| 1.1224 | 9.94 | 77 | 1.0479 | 0.5505 | |
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| 1.0547 | 10.97 | 85 | 0.9993 | 0.5963 | |
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| 1.0137 | 12.0 | 93 | 0.9860 | 0.6147 | |
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| 0.9652 | 12.9 | 100 | 0.9698 | 0.6147 | |
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| 0.9652 | 13.94 | 108 | 0.9519 | 0.6055 | |
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| 0.9217 | 14.97 | 116 | 0.9242 | 0.6055 | |
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| 0.9122 | 16.0 | 124 | 0.9062 | 0.6147 | |
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| 0.8763 | 16.9 | 131 | 0.8873 | 0.6422 | |
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| 0.8763 | 17.94 | 139 | 0.8477 | 0.6514 | |
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| 0.8471 | 18.97 | 147 | 0.8427 | 0.6514 | |
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| 0.8331 | 20.0 | 155 | 0.8257 | 0.6881 | |
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| 0.8167 | 20.9 | 162 | 0.8025 | 0.6881 | |
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| 0.8022 | 21.94 | 170 | 0.8011 | 0.6972 | |
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| 0.8022 | 22.97 | 178 | 0.8078 | 0.6972 | |
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| 0.7996 | 24.0 | 186 | 0.7920 | 0.7064 | |
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| 0.7962 | 24.9 | 193 | 0.7604 | 0.7248 | |
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| 0.7268 | 25.94 | 201 | 0.7597 | 0.6972 | |
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| 0.7268 | 26.97 | 209 | 0.7462 | 0.6972 | |
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| 0.7477 | 28.0 | 217 | 0.7316 | 0.7064 | |
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| 0.7411 | 28.9 | 224 | 0.7275 | 0.7523 | |
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| 0.7415 | 29.94 | 232 | 0.7210 | 0.7248 | |
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| 0.7159 | 30.97 | 240 | 0.7271 | 0.7248 | |
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| 0.7159 | 32.0 | 248 | 0.7005 | 0.7431 | |
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| 0.7322 | 32.9 | 255 | 0.7012 | 0.7431 | |
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| 0.7124 | 33.94 | 263 | 0.7052 | 0.7523 | |
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| 0.7194 | 34.97 | 271 | 0.6964 | 0.7615 | |
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| 0.7194 | 36.0 | 279 | 0.7007 | 0.7523 | |
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| 0.6903 | 36.13 | 280 | 0.6987 | 0.7431 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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