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smids_5x_deit_tiny_sgd_001_fold5

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/deit-tiny-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_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: 0.8966666666666666
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+ ---
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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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+
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+ # smids_5x_deit_tiny_sgd_001_fold5
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+
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+ This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2922
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+ - Accuracy: 0.8967
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.732 | 1.0 | 375 | 0.7708 | 0.6633 |
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+ | 0.5592 | 2.0 | 750 | 0.5202 | 0.805 |
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+ | 0.438 | 3.0 | 1125 | 0.4358 | 0.8283 |
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+ | 0.4192 | 4.0 | 1500 | 0.3942 | 0.8367 |
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+ | 0.3481 | 5.0 | 1875 | 0.3697 | 0.855 |
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+ | 0.3125 | 6.0 | 2250 | 0.3536 | 0.855 |
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+ | 0.2839 | 7.0 | 2625 | 0.3373 | 0.8583 |
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+ | 0.307 | 8.0 | 3000 | 0.3279 | 0.865 |
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+ | 0.3167 | 9.0 | 3375 | 0.3230 | 0.8633 |
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+ | 0.2868 | 10.0 | 3750 | 0.3137 | 0.8717 |
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+ | 0.2359 | 11.0 | 4125 | 0.3108 | 0.8717 |
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+ | 0.1975 | 12.0 | 4500 | 0.3038 | 0.8717 |
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+ | 0.2176 | 13.0 | 4875 | 0.3032 | 0.8733 |
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+ | 0.2542 | 14.0 | 5250 | 0.3007 | 0.875 |
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+ | 0.2703 | 15.0 | 5625 | 0.2972 | 0.8683 |
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+ | 0.1798 | 16.0 | 6000 | 0.2915 | 0.885 |
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+ | 0.2588 | 17.0 | 6375 | 0.2956 | 0.89 |
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+ | 0.2412 | 18.0 | 6750 | 0.2946 | 0.8917 |
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+ | 0.2128 | 19.0 | 7125 | 0.2865 | 0.89 |
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+ | 0.1689 | 20.0 | 7500 | 0.2885 | 0.8917 |
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+ | 0.1828 | 21.0 | 7875 | 0.2918 | 0.885 |
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+ | 0.1759 | 22.0 | 8250 | 0.2944 | 0.895 |
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+ | 0.2982 | 23.0 | 8625 | 0.2937 | 0.895 |
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+ | 0.1829 | 24.0 | 9000 | 0.2869 | 0.8917 |
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+ | 0.2242 | 25.0 | 9375 | 0.2897 | 0.8967 |
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+ | 0.1828 | 26.0 | 9750 | 0.2915 | 0.8967 |
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+ | 0.2241 | 27.0 | 10125 | 0.2878 | 0.8933 |
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+ | 0.1723 | 28.0 | 10500 | 0.2984 | 0.8967 |
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+ | 0.1963 | 29.0 | 10875 | 0.2878 | 0.8867 |
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+ | 0.1493 | 30.0 | 11250 | 0.2886 | 0.89 |
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+ | 0.2083 | 31.0 | 11625 | 0.2897 | 0.8983 |
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+ | 0.1814 | 32.0 | 12000 | 0.2856 | 0.8917 |
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+ | 0.1849 | 33.0 | 12375 | 0.2930 | 0.895 |
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+ | 0.2425 | 34.0 | 12750 | 0.2930 | 0.8967 |
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+ | 0.156 | 35.0 | 13125 | 0.2856 | 0.89 |
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+ | 0.1222 | 36.0 | 13500 | 0.2860 | 0.8933 |
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+ | 0.1645 | 37.0 | 13875 | 0.2870 | 0.89 |
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+ | 0.1564 | 38.0 | 14250 | 0.2951 | 0.8967 |
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+ | 0.1413 | 39.0 | 14625 | 0.2881 | 0.8967 |
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+ | 0.1794 | 40.0 | 15000 | 0.2908 | 0.8917 |
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+ | 0.1449 | 41.0 | 15375 | 0.2944 | 0.8983 |
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+ | 0.1425 | 42.0 | 15750 | 0.2915 | 0.8933 |
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+ | 0.1565 | 43.0 | 16125 | 0.2889 | 0.895 |
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+ | 0.1698 | 44.0 | 16500 | 0.2893 | 0.8933 |
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+ | 0.1716 | 45.0 | 16875 | 0.2917 | 0.8983 |
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+ | 0.1879 | 46.0 | 17250 | 0.2923 | 0.895 |
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+ | 0.1864 | 47.0 | 17625 | 0.2918 | 0.8967 |
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+ | 0.1231 | 48.0 | 18000 | 0.2914 | 0.8967 |
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+ | 0.1631 | 49.0 | 18375 | 0.2921 | 0.8967 |
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+ | 0.1701 | 50.0 | 18750 | 0.2922 | 0.8967 |
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+
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+
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+ ### Framework versions
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+
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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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