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hushem_1x_deit_tiny_rms_lr00001_fold5

Image Classification
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  2. model.safetensors +1 -1
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: hushem_1x_deit_tiny_rms_lr00001_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: 0.7073170731707317
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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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+ # hushem_1x_deit_tiny_rms_lr00001_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: 0.8230
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+ - Accuracy: 0.7073
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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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+ | No log | 1.0 | 6 | 1.1737 | 0.4634 |
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+ | 1.1816 | 2.0 | 12 | 0.8675 | 0.5366 |
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+ | 1.1816 | 3.0 | 18 | 0.8079 | 0.6341 |
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+ | 0.5246 | 4.0 | 24 | 0.8632 | 0.5854 |
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+ | 0.2225 | 5.0 | 30 | 0.7815 | 0.5610 |
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+ | 0.2225 | 6.0 | 36 | 0.6787 | 0.6585 |
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+ | 0.0792 | 7.0 | 42 | 0.7052 | 0.6585 |
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+ | 0.0792 | 8.0 | 48 | 0.7120 | 0.6341 |
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+ | 0.029 | 9.0 | 54 | 0.8373 | 0.6585 |
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+ | 0.0096 | 10.0 | 60 | 0.6713 | 0.7317 |
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+ | 0.0096 | 11.0 | 66 | 0.7185 | 0.7073 |
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+ | 0.0045 | 12.0 | 72 | 0.7237 | 0.6829 |
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+ | 0.0045 | 13.0 | 78 | 0.7062 | 0.6829 |
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+ | 0.0033 | 14.0 | 84 | 0.7203 | 0.7073 |
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+ | 0.0025 | 15.0 | 90 | 0.7207 | 0.7073 |
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+ | 0.0025 | 16.0 | 96 | 0.7400 | 0.7073 |
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+ | 0.002 | 17.0 | 102 | 0.7337 | 0.6829 |
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+ | 0.002 | 18.0 | 108 | 0.7527 | 0.6829 |
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+ | 0.0017 | 19.0 | 114 | 0.7553 | 0.6829 |
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+ | 0.0015 | 20.0 | 120 | 0.7631 | 0.6829 |
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+ | 0.0015 | 21.0 | 126 | 0.7684 | 0.6829 |
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+ | 0.0014 | 22.0 | 132 | 0.7730 | 0.6829 |
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+ | 0.0014 | 23.0 | 138 | 0.7803 | 0.6829 |
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+ | 0.0012 | 24.0 | 144 | 0.7869 | 0.6829 |
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+ | 0.0011 | 25.0 | 150 | 0.7854 | 0.6829 |
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+ | 0.0011 | 26.0 | 156 | 0.7958 | 0.6829 |
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+ | 0.001 | 27.0 | 162 | 0.7899 | 0.6829 |
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+ | 0.001 | 28.0 | 168 | 0.7956 | 0.6829 |
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+ | 0.001 | 29.0 | 174 | 0.8038 | 0.6829 |
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+ | 0.0009 | 30.0 | 180 | 0.8059 | 0.6829 |
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+ | 0.0009 | 31.0 | 186 | 0.8121 | 0.6829 |
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+ | 0.0008 | 32.0 | 192 | 0.8137 | 0.6829 |
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+ | 0.0008 | 33.0 | 198 | 0.8161 | 0.6829 |
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+ | 0.0008 | 34.0 | 204 | 0.8136 | 0.6829 |
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+ | 0.0008 | 35.0 | 210 | 0.8158 | 0.6829 |
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+ | 0.0008 | 36.0 | 216 | 0.8175 | 0.7073 |
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+ | 0.0007 | 37.0 | 222 | 0.8190 | 0.7073 |
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+ | 0.0007 | 38.0 | 228 | 0.8213 | 0.7073 |
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+ | 0.0007 | 39.0 | 234 | 0.8222 | 0.7073 |
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+ | 0.0007 | 40.0 | 240 | 0.8227 | 0.7073 |
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+ | 0.0007 | 41.0 | 246 | 0.8228 | 0.7073 |
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+ | 0.0007 | 42.0 | 252 | 0.8230 | 0.7073 |
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+ | 0.0007 | 43.0 | 258 | 0.8230 | 0.7073 |
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+ | 0.0007 | 44.0 | 264 | 0.8230 | 0.7073 |
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+ | 0.0007 | 45.0 | 270 | 0.8230 | 0.7073 |
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+ | 0.0007 | 46.0 | 276 | 0.8230 | 0.7073 |
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+ | 0.0007 | 47.0 | 282 | 0.8230 | 0.7073 |
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+ | 0.0007 | 48.0 | 288 | 0.8230 | 0.7073 |
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+ | 0.0007 | 49.0 | 294 | 0.8230 | 0.7073 |
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+ | 0.0007 | 50.0 | 300 | 0.8230 | 0.7073 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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