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--- |
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license: apache-2.0 |
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base_model: facebook/deit-small-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_deit_tiny_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_deit_tiny_sgd_001_fold1 |
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This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2974 |
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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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| 0.7214 | 1.0 | 376 | 0.7354 | 0.7112 | |
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| 0.5305 | 2.0 | 752 | 0.5484 | 0.7780 | |
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| 0.423 | 3.0 | 1128 | 0.4775 | 0.8063 | |
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| 0.4098 | 4.0 | 1504 | 0.4302 | 0.8364 | |
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| 0.4286 | 5.0 | 1880 | 0.4059 | 0.8497 | |
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| 0.3605 | 6.0 | 2256 | 0.3872 | 0.8548 | |
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| 0.3093 | 7.0 | 2632 | 0.3738 | 0.8648 | |
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| 0.3348 | 8.0 | 3008 | 0.3632 | 0.8664 | |
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| 0.3284 | 9.0 | 3384 | 0.3510 | 0.8765 | |
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| 0.3008 | 10.0 | 3760 | 0.3447 | 0.8748 | |
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| 0.289 | 11.0 | 4136 | 0.3398 | 0.8798 | |
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| 0.2542 | 12.0 | 4512 | 0.3320 | 0.8848 | |
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| 0.245 | 13.0 | 4888 | 0.3263 | 0.8865 | |
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| 0.2258 | 14.0 | 5264 | 0.3225 | 0.8865 | |
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| 0.3082 | 15.0 | 5640 | 0.3188 | 0.8848 | |
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| 0.2685 | 16.0 | 6016 | 0.3171 | 0.8848 | |
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| 0.2379 | 17.0 | 6392 | 0.3137 | 0.8865 | |
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| 0.2778 | 18.0 | 6768 | 0.3111 | 0.8848 | |
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| 0.2374 | 19.0 | 7144 | 0.3083 | 0.8848 | |
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| 0.1845 | 20.0 | 7520 | 0.3061 | 0.8848 | |
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| 0.2126 | 21.0 | 7896 | 0.3049 | 0.8865 | |
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| 0.2068 | 22.0 | 8272 | 0.3078 | 0.8831 | |
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| 0.2364 | 23.0 | 8648 | 0.3060 | 0.8798 | |
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| 0.1851 | 24.0 | 9024 | 0.3035 | 0.8881 | |
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| 0.2035 | 25.0 | 9400 | 0.3013 | 0.8848 | |
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| 0.2146 | 26.0 | 9776 | 0.3016 | 0.8881 | |
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| 0.1495 | 27.0 | 10152 | 0.2986 | 0.8915 | |
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| 0.1962 | 28.0 | 10528 | 0.2989 | 0.8898 | |
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| 0.2019 | 29.0 | 10904 | 0.2993 | 0.8881 | |
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| 0.1531 | 30.0 | 11280 | 0.2975 | 0.8932 | |
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| 0.1643 | 31.0 | 11656 | 0.2990 | 0.8898 | |
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| 0.2082 | 32.0 | 12032 | 0.2991 | 0.8881 | |
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| 0.1845 | 33.0 | 12408 | 0.2980 | 0.8915 | |
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| 0.1333 | 34.0 | 12784 | 0.2976 | 0.8932 | |
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| 0.1524 | 35.0 | 13160 | 0.3000 | 0.8865 | |
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| 0.1908 | 36.0 | 13536 | 0.2977 | 0.8915 | |
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| 0.1391 | 37.0 | 13912 | 0.2964 | 0.8948 | |
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| 0.1756 | 38.0 | 14288 | 0.2975 | 0.8915 | |
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| 0.2131 | 39.0 | 14664 | 0.2969 | 0.8932 | |
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| 0.1588 | 40.0 | 15040 | 0.2977 | 0.8898 | |
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| 0.1631 | 41.0 | 15416 | 0.2962 | 0.8932 | |
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| 0.1431 | 42.0 | 15792 | 0.2974 | 0.8915 | |
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| 0.1556 | 43.0 | 16168 | 0.2976 | 0.8898 | |
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| 0.1705 | 44.0 | 16544 | 0.2978 | 0.8915 | |
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| 0.1792 | 45.0 | 16920 | 0.2986 | 0.8898 | |
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| 0.1949 | 46.0 | 17296 | 0.2975 | 0.8915 | |
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| 0.1472 | 47.0 | 17672 | 0.2972 | 0.8915 | |
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| 0.139 | 48.0 | 18048 | 0.2974 | 0.8915 | |
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| 0.1452 | 49.0 | 18424 | 0.2974 | 0.8915 | |
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| 0.1388 | 50.0 | 18800 | 0.2974 | 0.8915 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.2 |
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