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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_5x_beit_base_rms_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: 0.7883333333333333 |
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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_5x_beit_base_rms_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: 1.2450 |
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- Accuracy: 0.7883 |
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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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| 0.8383 | 1.0 | 375 | 0.9251 | 0.4967 | |
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| 0.7811 | 2.0 | 750 | 0.8274 | 0.55 | |
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| 0.7757 | 3.0 | 1125 | 0.8322 | 0.55 | |
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| 0.774 | 4.0 | 1500 | 0.7903 | 0.5667 | |
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| 0.7988 | 5.0 | 1875 | 0.7818 | 0.59 | |
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| 0.7926 | 6.0 | 2250 | 0.7711 | 0.595 | |
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| 0.7549 | 7.0 | 2625 | 0.7682 | 0.6267 | |
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| 0.7997 | 8.0 | 3000 | 0.7569 | 0.61 | |
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| 0.6926 | 9.0 | 3375 | 0.7561 | 0.6417 | |
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| 0.7413 | 10.0 | 3750 | 0.7251 | 0.6567 | |
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| 0.6722 | 11.0 | 4125 | 0.7285 | 0.6533 | |
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| 0.7582 | 12.0 | 4500 | 0.7029 | 0.66 | |
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| 0.6728 | 13.0 | 4875 | 0.7283 | 0.6433 | |
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| 0.6373 | 14.0 | 5250 | 0.7252 | 0.6333 | |
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| 0.648 | 15.0 | 5625 | 0.7000 | 0.67 | |
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| 0.6675 | 16.0 | 6000 | 0.7072 | 0.6683 | |
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| 0.7316 | 17.0 | 6375 | 0.7063 | 0.6717 | |
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| 0.7151 | 18.0 | 6750 | 0.6856 | 0.6683 | |
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| 0.6082 | 19.0 | 7125 | 0.6800 | 0.6817 | |
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| 0.6879 | 20.0 | 7500 | 0.6816 | 0.6733 | |
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| 0.5586 | 21.0 | 7875 | 0.6735 | 0.695 | |
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| 0.6065 | 22.0 | 8250 | 0.6507 | 0.71 | |
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| 0.5783 | 23.0 | 8625 | 0.6597 | 0.69 | |
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| 0.6456 | 24.0 | 9000 | 0.6102 | 0.74 | |
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| 0.5238 | 25.0 | 9375 | 0.6683 | 0.7117 | |
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| 0.5326 | 26.0 | 9750 | 0.6240 | 0.7183 | |
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| 0.5499 | 27.0 | 10125 | 0.6403 | 0.7083 | |
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| 0.5607 | 28.0 | 10500 | 0.5945 | 0.7417 | |
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| 0.4887 | 29.0 | 10875 | 0.6536 | 0.71 | |
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| 0.5354 | 30.0 | 11250 | 0.5785 | 0.725 | |
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| 0.5136 | 31.0 | 11625 | 0.6072 | 0.7517 | |
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| 0.5448 | 32.0 | 12000 | 0.6265 | 0.7383 | |
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| 0.4542 | 33.0 | 12375 | 0.6265 | 0.7417 | |
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| 0.4208 | 34.0 | 12750 | 0.6113 | 0.745 | |
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| 0.3509 | 35.0 | 13125 | 0.6279 | 0.7467 | |
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| 0.4112 | 36.0 | 13500 | 0.6145 | 0.74 | |
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| 0.3719 | 37.0 | 13875 | 0.6674 | 0.745 | |
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| 0.3029 | 38.0 | 14250 | 0.6977 | 0.7583 | |
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| 0.3416 | 39.0 | 14625 | 0.6751 | 0.7717 | |
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| 0.3246 | 40.0 | 15000 | 0.6878 | 0.7633 | |
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| 0.2432 | 41.0 | 15375 | 0.6417 | 0.79 | |
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| 0.2014 | 42.0 | 15750 | 0.7882 | 0.78 | |
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| 0.2354 | 43.0 | 16125 | 0.8175 | 0.7817 | |
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| 0.1797 | 44.0 | 16500 | 0.8553 | 0.79 | |
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| 0.1419 | 45.0 | 16875 | 0.9481 | 0.765 | |
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| 0.1815 | 46.0 | 17250 | 1.0306 | 0.765 | |
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| 0.1604 | 47.0 | 17625 | 1.0263 | 0.765 | |
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| 0.103 | 48.0 | 18000 | 1.1281 | 0.7833 | |
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| 0.0441 | 49.0 | 18375 | 1.2055 | 0.79 | |
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| 0.0741 | 50.0 | 18750 | 1.2450 | 0.7883 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.2 |
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