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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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<!-- 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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# deit_flyswot |
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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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## 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: 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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### Training results |
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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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### Framework versions |
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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 |
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