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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_rms_00001_fold2 |
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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: 0.8885191347753744 |
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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_rms_00001_fold2 |
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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: 0.7810 |
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- Accuracy: 0.8885 |
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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: 1e-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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- 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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| 0.3067 | 1.0 | 75 | 0.2670 | 0.9018 | |
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| 0.1737 | 2.0 | 150 | 0.2937 | 0.8918 | |
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| 0.1236 | 3.0 | 225 | 0.2592 | 0.8968 | |
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| 0.093 | 4.0 | 300 | 0.2806 | 0.9085 | |
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| 0.0342 | 5.0 | 375 | 0.3377 | 0.9035 | |
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| 0.0514 | 6.0 | 450 | 0.4662 | 0.8769 | |
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| 0.0285 | 7.0 | 525 | 0.4751 | 0.8902 | |
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| 0.0245 | 8.0 | 600 | 0.4931 | 0.8968 | |
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| 0.0336 | 9.0 | 675 | 0.4686 | 0.9035 | |
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| 0.0057 | 10.0 | 750 | 0.6619 | 0.8852 | |
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| 0.0005 | 11.0 | 825 | 0.5601 | 0.9018 | |
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| 0.045 | 12.0 | 900 | 0.6300 | 0.8869 | |
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| 0.0006 | 13.0 | 975 | 0.6005 | 0.8968 | |
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| 0.0104 | 14.0 | 1050 | 0.6903 | 0.8769 | |
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| 0.0013 | 15.0 | 1125 | 0.6574 | 0.8968 | |
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| 0.0022 | 16.0 | 1200 | 0.6330 | 0.8952 | |
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| 0.0138 | 17.0 | 1275 | 0.6340 | 0.9018 | |
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| 0.0109 | 18.0 | 1350 | 0.7199 | 0.8902 | |
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| 0.007 | 19.0 | 1425 | 0.7166 | 0.8968 | |
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| 0.009 | 20.0 | 1500 | 0.8141 | 0.8802 | |
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| 0.0077 | 21.0 | 1575 | 0.8216 | 0.8935 | |
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| 0.0199 | 22.0 | 1650 | 0.8347 | 0.8802 | |
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| 0.0056 | 23.0 | 1725 | 0.7454 | 0.8869 | |
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| 0.0076 | 24.0 | 1800 | 0.6539 | 0.8968 | |
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| 0.0001 | 25.0 | 1875 | 0.7625 | 0.8819 | |
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| 0.0105 | 26.0 | 1950 | 0.7771 | 0.8918 | |
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| 0.0191 | 27.0 | 2025 | 0.7871 | 0.8902 | |
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| 0.0146 | 28.0 | 2100 | 0.7395 | 0.8968 | |
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| 0.0063 | 29.0 | 2175 | 0.7297 | 0.8968 | |
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| 0.0064 | 30.0 | 2250 | 0.6880 | 0.8952 | |
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| 0.0044 | 31.0 | 2325 | 0.7924 | 0.8918 | |
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| 0.0115 | 32.0 | 2400 | 0.7709 | 0.8918 | |
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| 0.0213 | 33.0 | 2475 | 0.6964 | 0.8918 | |
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| 0.0034 | 34.0 | 2550 | 0.7612 | 0.8918 | |
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| 0.0052 | 35.0 | 2625 | 0.7685 | 0.8968 | |
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| 0.0043 | 36.0 | 2700 | 0.8478 | 0.8869 | |
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| 0.0001 | 37.0 | 2775 | 0.7661 | 0.8902 | |
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| 0.0031 | 38.0 | 2850 | 0.7393 | 0.8968 | |
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| 0.0464 | 39.0 | 2925 | 0.7536 | 0.8918 | |
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| 0.0026 | 40.0 | 3000 | 0.7768 | 0.8852 | |
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| 0.0001 | 41.0 | 3075 | 0.8423 | 0.8835 | |
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| 0.0041 | 42.0 | 3150 | 0.7762 | 0.8918 | |
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| 0.0072 | 43.0 | 3225 | 0.7847 | 0.8902 | |
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| 0.0 | 44.0 | 3300 | 0.7699 | 0.8835 | |
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| 0.0049 | 45.0 | 3375 | 0.7675 | 0.8852 | |
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| 0.0001 | 46.0 | 3450 | 0.7767 | 0.8885 | |
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| 0.0029 | 47.0 | 3525 | 0.7697 | 0.8885 | |
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| 0.0 | 48.0 | 3600 | 0.7734 | 0.8885 | |
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| 0.0 | 49.0 | 3675 | 0.7813 | 0.8885 | |
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| 0.0231 | 50.0 | 3750 | 0.7810 | 0.8885 | |
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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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