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smids_5x_deit_tiny_adamax_00001_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_adamax_00001_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: 0.8933333333333333
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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_adamax_00001_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: 0.8918
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+ - Accuracy: 0.8933
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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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+ | 0.3356 | 1.0 | 375 | 0.3637 | 0.8583 |
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+ | 0.2941 | 2.0 | 750 | 0.2859 | 0.8917 |
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+ | 0.2173 | 3.0 | 1125 | 0.2723 | 0.8933 |
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+ | 0.2107 | 4.0 | 1500 | 0.2619 | 0.9017 |
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+ | 0.1256 | 5.0 | 1875 | 0.3096 | 0.8767 |
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+ | 0.0844 | 6.0 | 2250 | 0.2740 | 0.8983 |
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+ | 0.0863 | 7.0 | 2625 | 0.3155 | 0.895 |
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+ | 0.0472 | 8.0 | 3000 | 0.3497 | 0.895 |
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+ | 0.0763 | 9.0 | 3375 | 0.3686 | 0.895 |
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+ | 0.0335 | 10.0 | 3750 | 0.4149 | 0.8967 |
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+ | 0.0338 | 11.0 | 4125 | 0.4756 | 0.8933 |
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+ | 0.0184 | 12.0 | 4500 | 0.5125 | 0.89 |
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+ | 0.0027 | 13.0 | 4875 | 0.6023 | 0.8767 |
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+ | 0.0397 | 14.0 | 5250 | 0.6231 | 0.885 |
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+ | 0.0014 | 15.0 | 5625 | 0.7069 | 0.8733 |
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+ | 0.0003 | 16.0 | 6000 | 0.6770 | 0.8983 |
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+ | 0.0258 | 17.0 | 6375 | 0.7038 | 0.895 |
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+ | 0.0256 | 18.0 | 6750 | 0.7293 | 0.89 |
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+ | 0.0002 | 19.0 | 7125 | 0.7746 | 0.8833 |
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+ | 0.0001 | 20.0 | 7500 | 0.7738 | 0.8917 |
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+ | 0.0001 | 21.0 | 7875 | 0.8059 | 0.8833 |
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+ | 0.026 | 22.0 | 8250 | 0.8287 | 0.8933 |
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+ | 0.0138 | 23.0 | 8625 | 0.8293 | 0.8867 |
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+ | 0.0 | 24.0 | 9000 | 0.8289 | 0.88 |
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+ | 0.0 | 25.0 | 9375 | 0.8428 | 0.8933 |
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+ | 0.0001 | 26.0 | 9750 | 0.8343 | 0.8917 |
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+ | 0.0016 | 27.0 | 10125 | 0.8455 | 0.89 |
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+ | 0.0 | 28.0 | 10500 | 0.8478 | 0.89 |
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+ | 0.0001 | 29.0 | 10875 | 0.8508 | 0.8917 |
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+ | 0.0173 | 30.0 | 11250 | 0.8741 | 0.8917 |
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+ | 0.0 | 31.0 | 11625 | 0.8677 | 0.8933 |
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+ | 0.0 | 32.0 | 12000 | 0.8682 | 0.8933 |
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+ | 0.0 | 33.0 | 12375 | 0.8819 | 0.8917 |
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+ | 0.0 | 34.0 | 12750 | 0.8684 | 0.8917 |
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+ | 0.0 | 35.0 | 13125 | 0.8910 | 0.8933 |
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+ | 0.0 | 36.0 | 13500 | 0.8845 | 0.8933 |
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+ | 0.0 | 37.0 | 13875 | 0.8700 | 0.8917 |
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+ | 0.0072 | 38.0 | 14250 | 0.8781 | 0.8917 |
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+ | 0.0 | 39.0 | 14625 | 0.8840 | 0.8933 |
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+ | 0.0 | 40.0 | 15000 | 0.8993 | 0.895 |
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+ | 0.0 | 41.0 | 15375 | 0.8767 | 0.8883 |
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+ | 0.0 | 42.0 | 15750 | 0.8820 | 0.8967 |
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+ | 0.0 | 43.0 | 16125 | 0.8803 | 0.8983 |
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+ | 0.0 | 44.0 | 16500 | 0.8853 | 0.895 |
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+ | 0.0 | 45.0 | 16875 | 0.8969 | 0.8917 |
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+ | 0.0 | 46.0 | 17250 | 0.8999 | 0.8917 |
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+ | 0.0073 | 47.0 | 17625 | 0.8921 | 0.895 |
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+ | 0.0 | 48.0 | 18000 | 0.8943 | 0.8917 |
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+ | 0.0 | 49.0 | 18375 | 0.8940 | 0.8933 |
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+ | 0.0065 | 50.0 | 18750 | 0.8918 | 0.8933 |
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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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