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smids_5x_deit_base_sgd_001_fold1

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
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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-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_deit_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: 0.8931552587646077
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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_base_sgd_001_fold1
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+
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+ This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-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: 0.2661
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+ - Accuracy: 0.8932
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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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+ | 0.7985 | 1.0 | 376 | 0.8182 | 0.6978 |
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+ | 0.594 | 2.0 | 752 | 0.5849 | 0.7746 |
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+ | 0.4653 | 3.0 | 1128 | 0.4811 | 0.8197 |
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+ | 0.4509 | 4.0 | 1504 | 0.4265 | 0.8264 |
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+ | 0.406 | 5.0 | 1880 | 0.3929 | 0.8447 |
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+ | 0.3758 | 6.0 | 2256 | 0.3696 | 0.8581 |
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+ | 0.3147 | 7.0 | 2632 | 0.3531 | 0.8698 |
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+ | 0.3421 | 8.0 | 3008 | 0.3417 | 0.8664 |
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+ | 0.3606 | 9.0 | 3384 | 0.3307 | 0.8798 |
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+ | 0.2866 | 10.0 | 3760 | 0.3222 | 0.8865 |
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+ | 0.2912 | 11.0 | 4136 | 0.3153 | 0.8798 |
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+ | 0.2629 | 12.0 | 4512 | 0.3094 | 0.8865 |
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+ | 0.2464 | 13.0 | 4888 | 0.3048 | 0.8848 |
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+ | 0.2413 | 14.0 | 5264 | 0.3005 | 0.8881 |
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+ | 0.3125 | 15.0 | 5640 | 0.2955 | 0.8932 |
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+ | 0.226 | 16.0 | 6016 | 0.2931 | 0.8865 |
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+ | 0.2346 | 17.0 | 6392 | 0.2899 | 0.8915 |
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+ | 0.2997 | 18.0 | 6768 | 0.2867 | 0.8881 |
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+ | 0.2564 | 19.0 | 7144 | 0.2849 | 0.8898 |
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+ | 0.1951 | 20.0 | 7520 | 0.2838 | 0.8898 |
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+ | 0.2828 | 21.0 | 7896 | 0.2817 | 0.8898 |
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+ | 0.2327 | 22.0 | 8272 | 0.2806 | 0.8898 |
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+ | 0.2604 | 23.0 | 8648 | 0.2786 | 0.8865 |
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+ | 0.2065 | 24.0 | 9024 | 0.2780 | 0.8881 |
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+ | 0.2338 | 25.0 | 9400 | 0.2766 | 0.8881 |
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+ | 0.2197 | 26.0 | 9776 | 0.2745 | 0.8898 |
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+ | 0.1797 | 27.0 | 10152 | 0.2743 | 0.8898 |
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+ | 0.199 | 28.0 | 10528 | 0.2732 | 0.8915 |
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+ | 0.2002 | 29.0 | 10904 | 0.2724 | 0.8898 |
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+ | 0.1586 | 30.0 | 11280 | 0.2714 | 0.8932 |
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+ | 0.1861 | 31.0 | 11656 | 0.2710 | 0.8932 |
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+ | 0.2539 | 32.0 | 12032 | 0.2706 | 0.8948 |
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+ | 0.1906 | 33.0 | 12408 | 0.2700 | 0.8948 |
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+ | 0.1642 | 34.0 | 12784 | 0.2697 | 0.8915 |
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+ | 0.1856 | 35.0 | 13160 | 0.2694 | 0.8915 |
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+ | 0.2084 | 36.0 | 13536 | 0.2691 | 0.8932 |
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+ | 0.1812 | 37.0 | 13912 | 0.2681 | 0.8948 |
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+ | 0.2073 | 38.0 | 14288 | 0.2680 | 0.8948 |
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+ | 0.1854 | 39.0 | 14664 | 0.2677 | 0.8915 |
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+ | 0.1953 | 40.0 | 15040 | 0.2671 | 0.8932 |
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+ | 0.1912 | 41.0 | 15416 | 0.2672 | 0.8948 |
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+ | 0.1646 | 42.0 | 15792 | 0.2669 | 0.8932 |
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+ | 0.1689 | 43.0 | 16168 | 0.2666 | 0.8932 |
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+ | 0.1894 | 44.0 | 16544 | 0.2664 | 0.8932 |
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+ | 0.173 | 45.0 | 16920 | 0.2663 | 0.8932 |
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+ | 0.2186 | 46.0 | 17296 | 0.2661 | 0.8932 |
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+ | 0.1671 | 47.0 | 17672 | 0.2661 | 0.8932 |
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+ | 0.1916 | 48.0 | 18048 | 0.2661 | 0.8932 |
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+ | 0.1583 | 49.0 | 18424 | 0.2661 | 0.8932 |
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+ | 0.137 | 50.0 | 18800 | 0.2661 | 0.8932 |
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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 2.1.0+cu121
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.2
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