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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_00001_fold5 |
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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: 0.89 |
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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_00001_fold5 |
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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: 0.6882 |
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- Accuracy: 0.89 |
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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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| 0.3992 | 1.0 | 75 | 0.3544 | 0.845 | |
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| 0.2938 | 2.0 | 150 | 0.2944 | 0.88 | |
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| 0.2043 | 3.0 | 225 | 0.2889 | 0.8733 | |
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| 0.1457 | 4.0 | 300 | 0.2668 | 0.8917 | |
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| 0.1371 | 5.0 | 375 | 0.2691 | 0.8833 | |
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| 0.1186 | 6.0 | 450 | 0.2876 | 0.8733 | |
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| 0.0675 | 7.0 | 525 | 0.2905 | 0.895 | |
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| 0.0675 | 8.0 | 600 | 0.3070 | 0.8983 | |
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| 0.0951 | 9.0 | 675 | 0.3449 | 0.8917 | |
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| 0.0427 | 10.0 | 750 | 0.3642 | 0.885 | |
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| 0.0217 | 11.0 | 825 | 0.3880 | 0.8817 | |
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| 0.0513 | 12.0 | 900 | 0.3991 | 0.9 | |
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| 0.0247 | 13.0 | 975 | 0.4163 | 0.8983 | |
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| 0.018 | 14.0 | 1050 | 0.4538 | 0.8883 | |
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| 0.0291 | 15.0 | 1125 | 0.4599 | 0.8917 | |
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| 0.0096 | 16.0 | 1200 | 0.5126 | 0.89 | |
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| 0.0106 | 17.0 | 1275 | 0.5125 | 0.8867 | |
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| 0.0447 | 18.0 | 1350 | 0.5410 | 0.8883 | |
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| 0.016 | 19.0 | 1425 | 0.5359 | 0.8883 | |
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| 0.0033 | 20.0 | 1500 | 0.5522 | 0.8867 | |
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| 0.0086 | 21.0 | 1575 | 0.5579 | 0.8883 | |
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| 0.0299 | 22.0 | 1650 | 0.5864 | 0.8833 | |
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| 0.0058 | 23.0 | 1725 | 0.5904 | 0.8867 | |
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| 0.0156 | 24.0 | 1800 | 0.6102 | 0.89 | |
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| 0.0161 | 25.0 | 1875 | 0.6210 | 0.8883 | |
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| 0.0066 | 26.0 | 1950 | 0.6149 | 0.8883 | |
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| 0.0424 | 27.0 | 2025 | 0.6199 | 0.8867 | |
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| 0.011 | 28.0 | 2100 | 0.6388 | 0.8867 | |
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| 0.0021 | 29.0 | 2175 | 0.6358 | 0.8917 | |
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| 0.0014 | 30.0 | 2250 | 0.6319 | 0.8883 | |
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| 0.0203 | 31.0 | 2325 | 0.6459 | 0.89 | |
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| 0.0221 | 32.0 | 2400 | 0.6739 | 0.8883 | |
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| 0.0066 | 33.0 | 2475 | 0.6562 | 0.89 | |
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| 0.0119 | 34.0 | 2550 | 0.6704 | 0.885 | |
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| 0.0088 | 35.0 | 2625 | 0.6526 | 0.89 | |
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| 0.0115 | 36.0 | 2700 | 0.6534 | 0.8867 | |
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| 0.0355 | 37.0 | 2775 | 0.6663 | 0.8883 | |
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| 0.0376 | 38.0 | 2850 | 0.6538 | 0.89 | |
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| 0.0299 | 39.0 | 2925 | 0.6757 | 0.8867 | |
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| 0.0019 | 40.0 | 3000 | 0.6764 | 0.8883 | |
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| 0.0235 | 41.0 | 3075 | 0.6776 | 0.89 | |
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| 0.0081 | 42.0 | 3150 | 0.6798 | 0.8883 | |
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| 0.0053 | 43.0 | 3225 | 0.6758 | 0.8883 | |
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| 0.0234 | 44.0 | 3300 | 0.6788 | 0.8933 | |
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| 0.0053 | 45.0 | 3375 | 0.6853 | 0.8883 | |
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| 0.0121 | 46.0 | 3450 | 0.6875 | 0.8867 | |
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| 0.001 | 47.0 | 3525 | 0.6878 | 0.8883 | |
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| 0.0104 | 48.0 | 3600 | 0.6872 | 0.89 | |
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| 0.0042 | 49.0 | 3675 | 0.6870 | 0.8883 | |
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| 0.0115 | 50.0 | 3750 | 0.6882 | 0.89 | |
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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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