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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_sgd_001_fold1 |
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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: 0.8914858096828047 |
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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_sgd_001_fold1 |
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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: 0.2771 |
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- Accuracy: 0.8915 |
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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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| 0.7737 | 1.0 | 376 | 1.0623 | 0.3957 | |
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| 0.6499 | 2.0 | 752 | 0.5904 | 0.7679 | |
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| 0.5039 | 3.0 | 1128 | 0.4948 | 0.8114 | |
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| 0.4425 | 4.0 | 1504 | 0.4355 | 0.8314 | |
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| 0.4117 | 5.0 | 1880 | 0.4034 | 0.8381 | |
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| 0.3506 | 6.0 | 2256 | 0.3735 | 0.8497 | |
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| 0.3184 | 7.0 | 2632 | 0.3579 | 0.8614 | |
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| 0.3583 | 8.0 | 3008 | 0.3422 | 0.8664 | |
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| 0.3344 | 9.0 | 3384 | 0.3340 | 0.8765 | |
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| 0.3048 | 10.0 | 3760 | 0.3243 | 0.8731 | |
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| 0.3275 | 11.0 | 4136 | 0.3128 | 0.8815 | |
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| 0.2663 | 12.0 | 4512 | 0.3111 | 0.8765 | |
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| 0.2691 | 13.0 | 4888 | 0.3046 | 0.8815 | |
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| 0.2761 | 14.0 | 5264 | 0.3135 | 0.8715 | |
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| 0.3203 | 15.0 | 5640 | 0.2998 | 0.8831 | |
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| 0.2245 | 16.0 | 6016 | 0.2963 | 0.8881 | |
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| 0.2282 | 17.0 | 6392 | 0.2992 | 0.8881 | |
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| 0.3086 | 18.0 | 6768 | 0.2841 | 0.8881 | |
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| 0.2882 | 19.0 | 7144 | 0.2985 | 0.8831 | |
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| 0.2358 | 20.0 | 7520 | 0.2906 | 0.8898 | |
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| 0.25 | 21.0 | 7896 | 0.2925 | 0.8848 | |
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| 0.2381 | 22.0 | 8272 | 0.2832 | 0.8915 | |
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| 0.2558 | 23.0 | 8648 | 0.2829 | 0.8898 | |
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| 0.2316 | 24.0 | 9024 | 0.2855 | 0.8865 | |
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| 0.2594 | 25.0 | 9400 | 0.2808 | 0.8915 | |
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| 0.2312 | 26.0 | 9776 | 0.2815 | 0.8915 | |
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| 0.1664 | 27.0 | 10152 | 0.2829 | 0.8865 | |
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| 0.2051 | 28.0 | 10528 | 0.2875 | 0.8815 | |
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| 0.229 | 29.0 | 10904 | 0.2816 | 0.8881 | |
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| 0.1761 | 30.0 | 11280 | 0.2816 | 0.8915 | |
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| 0.2039 | 31.0 | 11656 | 0.2802 | 0.8965 | |
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| 0.2453 | 32.0 | 12032 | 0.2762 | 0.8965 | |
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| 0.186 | 33.0 | 12408 | 0.2762 | 0.8965 | |
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| 0.1739 | 34.0 | 12784 | 0.2763 | 0.8948 | |
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| 0.1942 | 35.0 | 13160 | 0.2781 | 0.8898 | |
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| 0.2172 | 36.0 | 13536 | 0.2768 | 0.8898 | |
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| 0.1982 | 37.0 | 13912 | 0.2760 | 0.8965 | |
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| 0.2031 | 38.0 | 14288 | 0.2780 | 0.8881 | |
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| 0.2045 | 39.0 | 14664 | 0.2746 | 0.8948 | |
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| 0.1936 | 40.0 | 15040 | 0.2754 | 0.8998 | |
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| 0.2051 | 41.0 | 15416 | 0.2792 | 0.8948 | |
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| 0.2059 | 42.0 | 15792 | 0.2787 | 0.8932 | |
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| 0.2037 | 43.0 | 16168 | 0.2780 | 0.8932 | |
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| 0.2183 | 44.0 | 16544 | 0.2796 | 0.8898 | |
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| 0.1934 | 45.0 | 16920 | 0.2779 | 0.8965 | |
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| 0.2385 | 46.0 | 17296 | 0.2770 | 0.8915 | |
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| 0.1872 | 47.0 | 17672 | 0.2768 | 0.8948 | |
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| 0.1967 | 48.0 | 18048 | 0.2773 | 0.8898 | |
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| 0.1829 | 49.0 | 18424 | 0.2770 | 0.8932 | |
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| 0.1506 | 50.0 | 18800 | 0.2771 | 0.8915 | |
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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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