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--- |
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license: apache-2.0 |
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base_model: microsoft/beit-base-patch16-224 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: smids_1x_beit_base_adamax_001_fold3 |
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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: imagefolder |
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type: imagefolder |
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config: default |
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split: test |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8066666666666666 |
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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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# smids_1x_beit_base_adamax_001_fold3 |
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This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6207 |
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- Accuracy: 0.8067 |
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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: 0.001 |
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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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- 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: 50 |
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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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| 0.961 | 1.0 | 75 | 0.9579 | 0.5083 | |
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| 0.8519 | 2.0 | 150 | 0.8223 | 0.555 | |
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| 0.8429 | 3.0 | 225 | 0.8258 | 0.5417 | |
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| 0.8689 | 4.0 | 300 | 1.1933 | 0.5183 | |
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| 0.7212 | 5.0 | 375 | 0.6887 | 0.7133 | |
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| 0.649 | 6.0 | 450 | 0.7128 | 0.6567 | |
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| 0.6409 | 7.0 | 525 | 0.6763 | 0.71 | |
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| 0.5869 | 8.0 | 600 | 0.5948 | 0.7383 | |
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| 0.5565 | 9.0 | 675 | 0.6418 | 0.695 | |
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| 0.5839 | 10.0 | 750 | 0.6087 | 0.7267 | |
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| 0.5293 | 11.0 | 825 | 0.5977 | 0.7267 | |
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| 0.4762 | 12.0 | 900 | 0.5491 | 0.7783 | |
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| 0.4499 | 13.0 | 975 | 0.5838 | 0.7517 | |
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| 0.4302 | 14.0 | 1050 | 0.5473 | 0.77 | |
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| 0.4099 | 15.0 | 1125 | 0.5508 | 0.755 | |
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| 0.3178 | 16.0 | 1200 | 0.5699 | 0.78 | |
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| 0.341 | 17.0 | 1275 | 0.6033 | 0.7933 | |
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| 0.2555 | 18.0 | 1350 | 0.6573 | 0.7767 | |
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| 0.3366 | 19.0 | 1425 | 0.5611 | 0.7933 | |
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| 0.1724 | 20.0 | 1500 | 0.7339 | 0.7933 | |
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| 0.2297 | 21.0 | 1575 | 0.8132 | 0.78 | |
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| 0.2293 | 22.0 | 1650 | 0.7112 | 0.7833 | |
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| 0.1656 | 23.0 | 1725 | 0.8681 | 0.7767 | |
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| 0.1488 | 24.0 | 1800 | 0.9454 | 0.79 | |
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| 0.1667 | 25.0 | 1875 | 0.9934 | 0.7767 | |
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| 0.0534 | 26.0 | 1950 | 0.9484 | 0.7767 | |
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| 0.1635 | 27.0 | 2025 | 1.0833 | 0.77 | |
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| 0.0554 | 28.0 | 2100 | 1.1552 | 0.8017 | |
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| 0.0938 | 29.0 | 2175 | 1.0865 | 0.7917 | |
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| 0.1141 | 30.0 | 2250 | 1.3605 | 0.7883 | |
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| 0.0561 | 31.0 | 2325 | 1.2003 | 0.8033 | |
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| 0.064 | 32.0 | 2400 | 1.3257 | 0.7933 | |
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| 0.0695 | 33.0 | 2475 | 1.6036 | 0.7883 | |
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| 0.0143 | 34.0 | 2550 | 1.5166 | 0.7717 | |
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| 0.0099 | 35.0 | 2625 | 1.5177 | 0.7833 | |
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| 0.046 | 36.0 | 2700 | 1.6809 | 0.7983 | |
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| 0.0535 | 37.0 | 2775 | 1.6548 | 0.7783 | |
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| 0.0142 | 38.0 | 2850 | 1.9052 | 0.7867 | |
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| 0.0043 | 39.0 | 2925 | 1.8855 | 0.785 | |
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| 0.0169 | 40.0 | 3000 | 1.8422 | 0.7983 | |
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| 0.0085 | 41.0 | 3075 | 1.6803 | 0.8033 | |
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| 0.0125 | 42.0 | 3150 | 1.4852 | 0.8033 | |
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| 0.0037 | 43.0 | 3225 | 1.5490 | 0.7883 | |
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| 0.0153 | 44.0 | 3300 | 1.3985 | 0.81 | |
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| 0.0066 | 45.0 | 3375 | 1.5369 | 0.8083 | |
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| 0.0076 | 46.0 | 3450 | 1.5177 | 0.7983 | |
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| 0.0089 | 47.0 | 3525 | 1.6039 | 0.7883 | |
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| 0.0027 | 48.0 | 3600 | 1.6013 | 0.8067 | |
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| 0.0003 | 49.0 | 3675 | 1.6182 | 0.8067 | |
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| 0.0026 | 50.0 | 3750 | 1.6207 | 0.8067 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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