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hushem_5x_deit_tiny_rms_0001_fold3

Image Classification
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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: hushem_5x_deit_tiny_rms_0001_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: 0.6976744186046512
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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_5x_deit_tiny_rms_0001_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: 2.7509
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+ - Accuracy: 0.6977
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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: 0.0001
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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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+ | 1.5103 | 1.0 | 28 | 2.0778 | 0.2558 |
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+ | 1.4169 | 2.0 | 56 | 1.4920 | 0.2558 |
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+ | 1.1717 | 3.0 | 84 | 1.4368 | 0.3488 |
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+ | 0.9912 | 4.0 | 112 | 0.9988 | 0.4651 |
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+ | 0.8022 | 5.0 | 140 | 1.6709 | 0.3953 |
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+ | 0.7789 | 6.0 | 168 | 0.6692 | 0.7907 |
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+ | 0.7753 | 7.0 | 196 | 0.7299 | 0.7209 |
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+ | 0.7094 | 8.0 | 224 | 0.9947 | 0.7209 |
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+ | 0.5393 | 9.0 | 252 | 1.1069 | 0.6279 |
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+ | 0.4827 | 10.0 | 280 | 1.3153 | 0.5581 |
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+ | 0.4471 | 11.0 | 308 | 0.7571 | 0.7209 |
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+ | 0.2911 | 12.0 | 336 | 1.0945 | 0.6977 |
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+ | 0.2341 | 13.0 | 364 | 1.4428 | 0.7209 |
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+ | 0.1731 | 14.0 | 392 | 1.1663 | 0.7442 |
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+ | 0.1668 | 15.0 | 420 | 2.1058 | 0.5581 |
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+ | 0.0808 | 16.0 | 448 | 1.5095 | 0.6977 |
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+ | 0.0267 | 17.0 | 476 | 2.3464 | 0.5349 |
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+ | 0.0601 | 18.0 | 504 | 1.3157 | 0.7442 |
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+ | 0.0193 | 19.0 | 532 | 1.9786 | 0.6279 |
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+ | 0.0007 | 20.0 | 560 | 1.8771 | 0.7209 |
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+ | 0.0002 | 21.0 | 588 | 1.8199 | 0.6744 |
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+ | 0.0002 | 22.0 | 616 | 2.2093 | 0.6279 |
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+ | 0.0001 | 23.0 | 644 | 2.3026 | 0.6512 |
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+ | 0.0 | 24.0 | 672 | 2.3149 | 0.6744 |
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+ | 0.0 | 25.0 | 700 | 2.3349 | 0.6744 |
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+ | 0.0 | 26.0 | 728 | 2.3579 | 0.6744 |
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+ | 0.0 | 27.0 | 756 | 2.3790 | 0.6744 |
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+ | 0.0 | 28.0 | 784 | 2.4090 | 0.6744 |
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+ | 0.0 | 29.0 | 812 | 2.4324 | 0.6744 |
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+ | 0.0 | 30.0 | 840 | 2.4483 | 0.6977 |
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+ | 0.0 | 31.0 | 868 | 2.4871 | 0.6977 |
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+ | 0.0 | 32.0 | 896 | 2.5064 | 0.6977 |
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+ | 0.0 | 33.0 | 924 | 2.5268 | 0.6977 |
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+ | 0.0 | 34.0 | 952 | 2.5458 | 0.6977 |
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+ | 0.0 | 35.0 | 980 | 2.5702 | 0.6977 |
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+ | 0.0 | 36.0 | 1008 | 2.5945 | 0.6977 |
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+ | 0.0 | 37.0 | 1036 | 2.6129 | 0.6977 |
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+ | 0.0 | 38.0 | 1064 | 2.6351 | 0.6977 |
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+ | 0.0 | 39.0 | 1092 | 2.6496 | 0.6977 |
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+ | 0.0 | 40.0 | 1120 | 2.6665 | 0.6977 |
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+ | 0.0 | 41.0 | 1148 | 2.6790 | 0.6977 |
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+ | 0.0 | 42.0 | 1176 | 2.6948 | 0.6977 |
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+ | 0.0 | 43.0 | 1204 | 2.7095 | 0.6977 |
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+ | 0.0 | 44.0 | 1232 | 2.7229 | 0.6977 |
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+ | 0.0 | 45.0 | 1260 | 2.7315 | 0.6977 |
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+ | 0.0 | 46.0 | 1288 | 2.7407 | 0.6977 |
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+ | 0.0 | 47.0 | 1316 | 2.7476 | 0.6977 |
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+ | 0.0 | 48.0 | 1344 | 2.7508 | 0.6977 |
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+ | 0.0 | 49.0 | 1372 | 2.7509 | 0.6977 |
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+ | 0.0 | 50.0 | 1400 | 2.7509 | 0.6977 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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