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swiftformer-xs-dmae-va-U-40

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  1. README.md +98 -0
  2. model.safetensors +1 -1
  3. runs/Feb01_15-59-58_56aa26a8524f/events.out.tfevents.1706803208.56aa26a8524f.1432.0 +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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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: swiftformer-xs-dmae-va-U-40
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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-U-40
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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: 0.6736
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+ - Accuracy: 0.7523
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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: 40
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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 | 1.3578 | 0.2936 |
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+ | 1.3702 | 1.94 | 15 | 1.3703 | 0.2936 |
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+ | 1.3497 | 2.97 | 23 | 1.3361 | 0.3394 |
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+ | 1.3004 | 4.0 | 31 | 1.2852 | 0.3670 |
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+ | 1.3004 | 4.9 | 38 | 1.2317 | 0.4312 |
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+ | 1.2248 | 5.94 | 46 | 1.1786 | 0.4587 |
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+ | 1.1485 | 6.97 | 54 | 1.1240 | 0.5046 |
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+ | 1.0759 | 8.0 | 62 | 1.0727 | 0.5505 |
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+ | 1.0759 | 8.9 | 69 | 1.0404 | 0.5596 |
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+ | 1.0244 | 9.94 | 77 | 0.9742 | 0.6239 |
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+ | 0.9782 | 10.97 | 85 | 0.9374 | 0.6422 |
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+ | 0.9359 | 12.0 | 93 | 0.9197 | 0.6789 |
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+ | 0.9051 | 12.9 | 100 | 0.8753 | 0.6881 |
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+ | 0.9051 | 13.94 | 108 | 0.8679 | 0.6972 |
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+ | 0.8652 | 14.97 | 116 | 0.8316 | 0.7156 |
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+ | 0.8336 | 16.0 | 124 | 0.8222 | 0.6972 |
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+ | 0.8177 | 16.9 | 131 | 0.8178 | 0.6972 |
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+ | 0.8177 | 17.94 | 139 | 0.7818 | 0.7339 |
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+ | 0.8077 | 18.97 | 147 | 0.7627 | 0.7339 |
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+ | 0.7796 | 20.0 | 155 | 0.7478 | 0.7339 |
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+ | 0.7673 | 20.9 | 162 | 0.7415 | 0.7431 |
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+ | 0.7445 | 21.94 | 170 | 0.7414 | 0.7156 |
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+ | 0.7445 | 22.97 | 178 | 0.7375 | 0.7156 |
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+ | 0.7413 | 24.0 | 186 | 0.7354 | 0.7156 |
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+ | 0.739 | 24.9 | 193 | 0.7110 | 0.7431 |
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+ | 0.6992 | 25.94 | 201 | 0.7121 | 0.7339 |
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+ | 0.6992 | 26.97 | 209 | 0.7044 | 0.7431 |
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+ | 0.7111 | 28.0 | 217 | 0.6947 | 0.7339 |
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+ | 0.7013 | 28.9 | 224 | 0.7007 | 0.7523 |
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+ | 0.712 | 29.94 | 232 | 0.6793 | 0.7431 |
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+ | 0.671 | 30.97 | 240 | 0.6808 | 0.7431 |
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+ | 0.671 | 32.0 | 248 | 0.6821 | 0.7339 |
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+ | 0.6862 | 32.9 | 255 | 0.6705 | 0.7339 |
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+ | 0.6606 | 33.94 | 263 | 0.6784 | 0.7431 |
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+ | 0.6667 | 34.97 | 271 | 0.6764 | 0.7523 |
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+ | 0.6667 | 36.0 | 279 | 0.6717 | 0.7523 |
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+ | 0.6687 | 36.13 | 280 | 0.6736 | 0.7523 |
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+
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+
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+ ### Framework versions
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+
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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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