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hkivancoral
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smids_3x_deit_tiny_rms_00001_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-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_3x_deit_tiny_rms_00001_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: 0.9033333333333333
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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_3x_deit_tiny_rms_00001_fold3
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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: 0.9705
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+ - Accuracy: 0.9033
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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: 1e-05
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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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+ | 0.3413 | 1.0 | 225 | 0.2808 | 0.8933 |
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+ | 0.2287 | 2.0 | 450 | 0.2742 | 0.9 |
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+ | 0.1591 | 3.0 | 675 | 0.3006 | 0.89 |
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+ | 0.0862 | 4.0 | 900 | 0.3381 | 0.8883 |
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+ | 0.087 | 5.0 | 1125 | 0.4066 | 0.8783 |
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+ | 0.0686 | 6.0 | 1350 | 0.4702 | 0.885 |
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+ | 0.0747 | 7.0 | 1575 | 0.5496 | 0.8933 |
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+ | 0.0256 | 8.0 | 1800 | 0.6539 | 0.885 |
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+ | 0.0458 | 9.0 | 2025 | 0.6793 | 0.8883 |
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+ | 0.0397 | 10.0 | 2250 | 0.7901 | 0.88 |
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+ | 0.0252 | 11.0 | 2475 | 0.7599 | 0.8967 |
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+ | 0.0212 | 12.0 | 2700 | 0.8640 | 0.89 |
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+ | 0.033 | 13.0 | 2925 | 0.8965 | 0.88 |
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+ | 0.0005 | 14.0 | 3150 | 0.8332 | 0.895 |
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+ | 0.0068 | 15.0 | 3375 | 0.9483 | 0.8717 |
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+ | 0.0008 | 16.0 | 3600 | 1.0157 | 0.8783 |
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+ | 0.0016 | 17.0 | 3825 | 0.8948 | 0.8867 |
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+ | 0.0002 | 18.0 | 4050 | 0.8418 | 0.895 |
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+ | 0.0 | 19.0 | 4275 | 0.8994 | 0.8983 |
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+ | 0.0044 | 20.0 | 4500 | 0.8798 | 0.9083 |
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+ | 0.0 | 21.0 | 4725 | 1.0795 | 0.8717 |
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+ | 0.0009 | 22.0 | 4950 | 1.0744 | 0.885 |
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+ | 0.0066 | 23.0 | 5175 | 0.9462 | 0.8883 |
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+ | 0.0 | 24.0 | 5400 | 0.8715 | 0.9017 |
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+ | 0.0088 | 25.0 | 5625 | 0.9553 | 0.8983 |
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+ | 0.0 | 26.0 | 5850 | 0.9300 | 0.9 |
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+ | 0.0271 | 27.0 | 6075 | 0.9362 | 0.8967 |
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+ | 0.0 | 28.0 | 6300 | 0.9453 | 0.8967 |
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+ | 0.0056 | 29.0 | 6525 | 1.0241 | 0.8917 |
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+ | 0.0134 | 30.0 | 6750 | 0.9852 | 0.9017 |
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+ | 0.0062 | 31.0 | 6975 | 0.9946 | 0.9017 |
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+ | 0.0 | 32.0 | 7200 | 1.0433 | 0.89 |
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+ | 0.0 | 33.0 | 7425 | 0.9693 | 0.8983 |
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+ | 0.0 | 34.0 | 7650 | 0.9977 | 0.8983 |
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+ | 0.0 | 35.0 | 7875 | 0.9577 | 0.9033 |
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+ | 0.0 | 36.0 | 8100 | 0.9692 | 0.8967 |
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+ | 0.0 | 37.0 | 8325 | 0.9675 | 0.8967 |
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+ | 0.0 | 38.0 | 8550 | 0.9775 | 0.9 |
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+ | 0.0 | 39.0 | 8775 | 0.9600 | 0.9 |
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+ | 0.0 | 40.0 | 9000 | 0.9503 | 0.8983 |
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+ | 0.0 | 41.0 | 9225 | 0.9634 | 0.895 |
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+ | 0.0 | 42.0 | 9450 | 0.9624 | 0.9 |
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+ | 0.0 | 43.0 | 9675 | 0.9737 | 0.9 |
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+ | 0.0 | 44.0 | 9900 | 0.9743 | 0.9017 |
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+ | 0.0 | 45.0 | 10125 | 0.9706 | 0.9 |
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+ | 0.0 | 46.0 | 10350 | 0.9706 | 0.9 |
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+ | 0.0019 | 47.0 | 10575 | 0.9708 | 0.9017 |
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+ | 0.0 | 48.0 | 10800 | 0.9707 | 0.9017 |
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+ | 0.0 | 49.0 | 11025 | 0.9710 | 0.9017 |
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+ | 0.0 | 50.0 | 11250 | 0.9705 | 0.9033 |
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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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