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swin-tiny-patch4-window7-224-dmae-va-U5-42

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  2. model.safetensors +1 -1
  3. runs/Apr01_20-08-19_DESKTOP-SKBE9FB/events.out.tfevents.1712023701.DESKTOP-SKBE9FB.12956.0 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: microsoft/swin-tiny-patch4-window7-224
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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: swin-tiny-patch4-window7-224-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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+ # swin-tiny-patch4-window7-224-dmae-va-U5-42
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+
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+ This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8840
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+ - Accuracy: 0.7333
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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 | 1.3831 | 0.45 |
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+ | 1.3852 | 1.94 | 15 | 1.3624 | 0.45 |
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+ | 1.3728 | 2.97 | 23 | 1.2927 | 0.4667 |
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+ | 1.2791 | 4.0 | 31 | 1.1182 | 0.4833 |
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+ | 1.2791 | 4.9 | 38 | 1.0065 | 0.4667 |
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+ | 1.094 | 5.94 | 46 | 0.8931 | 0.6 |
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+ | 0.9601 | 6.97 | 54 | 0.9210 | 0.4833 |
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+ | 0.8598 | 8.0 | 62 | 0.9478 | 0.5167 |
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+ | 0.8598 | 8.9 | 69 | 0.8558 | 0.5833 |
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+ | 0.7558 | 9.94 | 77 | 0.9259 | 0.65 |
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+ | 0.6696 | 10.97 | 85 | 0.7953 | 0.6167 |
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+ | 0.6079 | 12.0 | 93 | 0.7281 | 0.7 |
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+ | 0.516 | 12.9 | 100 | 0.8552 | 0.6667 |
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+ | 0.516 | 13.94 | 108 | 0.6653 | 0.75 |
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+ | 0.4475 | 14.97 | 116 | 0.7548 | 0.6833 |
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+ | 0.4152 | 16.0 | 124 | 0.7556 | 0.7167 |
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+ | 0.3759 | 16.9 | 131 | 0.7038 | 0.7333 |
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+ | 0.3759 | 17.94 | 139 | 0.7356 | 0.7167 |
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+ | 0.3366 | 18.97 | 147 | 0.6650 | 0.75 |
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+ | 0.3212 | 20.0 | 155 | 0.7668 | 0.7167 |
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+ | 0.2903 | 20.9 | 162 | 0.7997 | 0.6833 |
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+ | 0.312 | 21.94 | 170 | 0.7473 | 0.7167 |
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+ | 0.312 | 22.97 | 178 | 0.8479 | 0.7 |
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+ | 0.2488 | 24.0 | 186 | 0.8070 | 0.7 |
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+ | 0.283 | 24.9 | 193 | 0.8080 | 0.6833 |
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+ | 0.2109 | 25.94 | 201 | 0.8220 | 0.7 |
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+ | 0.2109 | 26.97 | 209 | 0.8354 | 0.7167 |
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+ | 0.2215 | 28.0 | 217 | 0.8668 | 0.7 |
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+ | 0.2067 | 28.9 | 224 | 0.8479 | 0.75 |
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+ | 0.1967 | 29.94 | 232 | 0.8868 | 0.7167 |
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+ | 0.1948 | 30.97 | 240 | 0.8883 | 0.7 |
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+ | 0.1948 | 32.0 | 248 | 0.8612 | 0.7333 |
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+ | 0.186 | 32.9 | 255 | 0.8860 | 0.7333 |
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+ | 0.1662 | 33.94 | 263 | 0.9057 | 0.75 |
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+ | 0.1773 | 34.97 | 271 | 0.9140 | 0.7167 |
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+ | 0.1773 | 36.0 | 279 | 0.9013 | 0.7333 |
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+ | 0.1519 | 36.9 | 286 | 0.8869 | 0.75 |
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+ | 0.1775 | 37.94 | 294 | 0.8840 | 0.7333 |
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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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