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smids_10x_deit_base_sgd_001_fold3

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-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_10x_deit_base_sgd_001_fold3
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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: 0.9083333333333333
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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_10x_deit_base_sgd_001_fold3
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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: 0.2607
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+ - Accuracy: 0.9083
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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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+ | 0.5671 | 1.0 | 750 | 0.5928 | 0.7967 |
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+ | 0.408 | 2.0 | 1500 | 0.4283 | 0.8517 |
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+ | 0.3447 | 3.0 | 2250 | 0.3742 | 0.8633 |
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+ | 0.3088 | 4.0 | 3000 | 0.3475 | 0.8683 |
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+ | 0.2979 | 5.0 | 3750 | 0.3269 | 0.8733 |
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+ | 0.2962 | 6.0 | 4500 | 0.3183 | 0.8767 |
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+ | 0.2557 | 7.0 | 5250 | 0.3059 | 0.8817 |
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+ | 0.2555 | 8.0 | 6000 | 0.2957 | 0.8817 |
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+ | 0.2367 | 9.0 | 6750 | 0.2914 | 0.885 |
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+ | 0.1949 | 10.0 | 7500 | 0.2859 | 0.8917 |
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+ | 0.2488 | 11.0 | 8250 | 0.2846 | 0.8917 |
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+ | 0.2475 | 12.0 | 9000 | 0.2777 | 0.895 |
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+ | 0.1828 | 13.0 | 9750 | 0.2753 | 0.8983 |
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+ | 0.2439 | 14.0 | 10500 | 0.2718 | 0.9017 |
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+ | 0.2473 | 15.0 | 11250 | 0.2704 | 0.895 |
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+ | 0.1928 | 16.0 | 12000 | 0.2696 | 0.895 |
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+ | 0.1843 | 17.0 | 12750 | 0.2710 | 0.8983 |
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+ | 0.2029 | 18.0 | 13500 | 0.2625 | 0.9033 |
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+ | 0.2035 | 19.0 | 14250 | 0.2665 | 0.9 |
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+ | 0.1744 | 20.0 | 15000 | 0.2677 | 0.905 |
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+ | 0.152 | 21.0 | 15750 | 0.2612 | 0.9033 |
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+ | 0.1898 | 22.0 | 16500 | 0.2631 | 0.9 |
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+ | 0.1983 | 23.0 | 17250 | 0.2648 | 0.9067 |
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+ | 0.1746 | 24.0 | 18000 | 0.2651 | 0.9067 |
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+ | 0.2045 | 25.0 | 18750 | 0.2633 | 0.9067 |
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+ | 0.1969 | 26.0 | 19500 | 0.2578 | 0.9067 |
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+ | 0.1227 | 27.0 | 20250 | 0.2593 | 0.91 |
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+ | 0.1518 | 28.0 | 21000 | 0.2610 | 0.9083 |
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+ | 0.1661 | 29.0 | 21750 | 0.2607 | 0.9067 |
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+ | 0.1698 | 30.0 | 22500 | 0.2600 | 0.9083 |
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+ | 0.1513 | 31.0 | 23250 | 0.2624 | 0.9067 |
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+ | 0.1181 | 32.0 | 24000 | 0.2595 | 0.9083 |
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+ | 0.1772 | 33.0 | 24750 | 0.2601 | 0.9083 |
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+ | 0.1745 | 34.0 | 25500 | 0.2608 | 0.9083 |
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+ | 0.1241 | 35.0 | 26250 | 0.2599 | 0.9083 |
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+ | 0.1459 | 36.0 | 27000 | 0.2607 | 0.9083 |
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+ | 0.1333 | 37.0 | 27750 | 0.2607 | 0.9083 |
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+ | 0.1934 | 38.0 | 28500 | 0.2605 | 0.905 |
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+ | 0.1357 | 39.0 | 29250 | 0.2594 | 0.91 |
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+ | 0.1781 | 40.0 | 30000 | 0.2597 | 0.91 |
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+ | 0.1473 | 41.0 | 30750 | 0.2601 | 0.91 |
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+ | 0.1773 | 42.0 | 31500 | 0.2596 | 0.9083 |
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+ | 0.1488 | 43.0 | 32250 | 0.2600 | 0.9083 |
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+ | 0.1451 | 44.0 | 33000 | 0.2615 | 0.9083 |
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+ | 0.1365 | 45.0 | 33750 | 0.2606 | 0.9083 |
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+ | 0.1144 | 46.0 | 34500 | 0.2619 | 0.9067 |
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+ | 0.1714 | 47.0 | 35250 | 0.2607 | 0.9083 |
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+ | 0.1189 | 48.0 | 36000 | 0.2607 | 0.9083 |
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+ | 0.1679 | 49.0 | 36750 | 0.2607 | 0.9083 |
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+ | 0.1606 | 50.0 | 37500 | 0.2607 | 0.9083 |
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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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