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+ ---
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - image_folder
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+ metrics:
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+ - f1
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+ model-index:
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+ - name: deit_flyswot
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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: image_folder
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+ type: image_folder
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+ args: default
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+ metrics:
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+ - name: F1
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+ type: f1
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+ value: 0.990761405263678
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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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+ # deit_flyswot
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+
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+ This model was trained from scratch on the image_folder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0755
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+ - F1: 0.9908
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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: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 666
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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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+ - num_epochs: 30
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | No log | 1.0 | 52 | 0.5710 | 0.8095 |
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+ | No log | 2.0 | 104 | 0.2814 | 0.9380 |
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+ | No log | 3.0 | 156 | 0.1719 | 0.9555 |
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+ | No log | 4.0 | 208 | 0.1410 | 0.9692 |
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+ | No log | 5.0 | 260 | 0.1457 | 0.9680 |
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+ | No log | 6.0 | 312 | 0.1084 | 0.9747 |
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+ | No log | 7.0 | 364 | 0.0892 | 0.9736 |
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+ | No log | 8.0 | 416 | 0.0962 | 0.9831 |
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+ | No log | 9.0 | 468 | 0.0819 | 0.9796 |
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+ | 0.2034 | 10.0 | 520 | 0.0916 | 0.9778 |
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+ | 0.2034 | 11.0 | 572 | 0.0793 | 0.9827 |
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+ | 0.2034 | 12.0 | 624 | 0.0818 | 0.9894 |
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+ | 0.2034 | 13.0 | 676 | 0.0852 | 0.9807 |
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+ | 0.2034 | 14.0 | 728 | 0.0938 | 0.9778 |
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+ | 0.2034 | 15.0 | 780 | 0.0814 | 0.9876 |
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+ | 0.2034 | 16.0 | 832 | 0.0702 | 0.9892 |
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+ | 0.2034 | 17.0 | 884 | 0.0801 | 0.9892 |
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+ | 0.2034 | 18.0 | 936 | 0.0806 | 0.9892 |
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+ | 0.2034 | 19.0 | 988 | 0.0769 | 0.9926 |
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+ | 0.0115 | 20.0 | 1040 | 0.0800 | 0.9926 |
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+ | 0.0115 | 21.0 | 1092 | 0.0794 | 0.9926 |
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+ | 0.0115 | 22.0 | 1144 | 0.0762 | 0.9846 |
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+ | 0.0115 | 23.0 | 1196 | 0.0789 | 0.9830 |
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+ | 0.0115 | 24.0 | 1248 | 0.0794 | 0.9829 |
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+ | 0.0115 | 25.0 | 1300 | 0.0770 | 0.9908 |
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+ | 0.0115 | 26.0 | 1352 | 0.0791 | 0.9829 |
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+ | 0.0115 | 27.0 | 1404 | 0.0813 | 0.9892 |
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+ | 0.0115 | 28.0 | 1456 | 0.0816 | 0.9908 |
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+ | 0.0058 | 29.0 | 1508 | 0.0774 | 0.9908 |
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+ | 0.0058 | 30.0 | 1560 | 0.0755 | 0.9908 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.17.0
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+ - Pytorch 1.10.0+cu111
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+ - Datasets 2.0.0
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+ - Tokenizers 0.11.6