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hushem_1x_deit_base_rms_00001_fold5

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  2. model.safetensors +1 -1
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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: hushem_1x_deit_base_rms_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: 0.8048780487804879
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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_base_rms_00001_fold5
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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: 0.6686
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+ - Accuracy: 0.8049
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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 | 1.1610 | 0.4878 |
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+ | 1.1582 | 2.0 | 12 | 0.8046 | 0.6585 |
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+ | 1.1582 | 3.0 | 18 | 0.6473 | 0.7805 |
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+ | 0.4382 | 4.0 | 24 | 0.6375 | 0.7073 |
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+ | 0.1279 | 5.0 | 30 | 0.5568 | 0.7317 |
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+ | 0.1279 | 6.0 | 36 | 0.6762 | 0.7805 |
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+ | 0.0256 | 7.0 | 42 | 0.5322 | 0.8049 |
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+ | 0.0256 | 8.0 | 48 | 0.6244 | 0.8049 |
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+ | 0.0081 | 9.0 | 54 | 0.5937 | 0.7805 |
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+ | 0.0049 | 10.0 | 60 | 0.5932 | 0.8049 |
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+ | 0.0049 | 11.0 | 66 | 0.6107 | 0.8049 |
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+ | 0.0035 | 12.0 | 72 | 0.6136 | 0.8049 |
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+ | 0.0035 | 13.0 | 78 | 0.6118 | 0.8049 |
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+ | 0.0028 | 14.0 | 84 | 0.6111 | 0.8049 |
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+ | 0.0023 | 15.0 | 90 | 0.6113 | 0.8049 |
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+ | 0.0023 | 16.0 | 96 | 0.6216 | 0.8049 |
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+ | 0.0019 | 17.0 | 102 | 0.6208 | 0.8049 |
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+ | 0.0019 | 18.0 | 108 | 0.6301 | 0.8049 |
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+ | 0.0017 | 19.0 | 114 | 0.6331 | 0.8049 |
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+ | 0.0015 | 20.0 | 120 | 0.6358 | 0.8049 |
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+ | 0.0015 | 21.0 | 126 | 0.6382 | 0.8049 |
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+ | 0.0014 | 22.0 | 132 | 0.6393 | 0.8049 |
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+ | 0.0014 | 23.0 | 138 | 0.6427 | 0.8049 |
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+ | 0.0012 | 24.0 | 144 | 0.6480 | 0.8049 |
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+ | 0.0012 | 25.0 | 150 | 0.6496 | 0.8049 |
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+ | 0.0012 | 26.0 | 156 | 0.6549 | 0.8049 |
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+ | 0.0011 | 27.0 | 162 | 0.6526 | 0.8049 |
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+ | 0.0011 | 28.0 | 168 | 0.6563 | 0.8049 |
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+ | 0.001 | 29.0 | 174 | 0.6589 | 0.8049 |
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+ | 0.0009 | 30.0 | 180 | 0.6593 | 0.8049 |
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+ | 0.0009 | 31.0 | 186 | 0.6617 | 0.8049 |
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+ | 0.0009 | 32.0 | 192 | 0.6634 | 0.8049 |
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+ | 0.0009 | 33.0 | 198 | 0.6645 | 0.8049 |
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+ | 0.0009 | 34.0 | 204 | 0.6634 | 0.8049 |
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+ | 0.0008 | 35.0 | 210 | 0.6653 | 0.8049 |
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+ | 0.0008 | 36.0 | 216 | 0.6660 | 0.8049 |
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+ | 0.0008 | 37.0 | 222 | 0.6671 | 0.8049 |
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+ | 0.0008 | 38.0 | 228 | 0.6676 | 0.8049 |
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+ | 0.0008 | 39.0 | 234 | 0.6682 | 0.8049 |
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+ | 0.0008 | 40.0 | 240 | 0.6685 | 0.8049 |
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+ | 0.0008 | 41.0 | 246 | 0.6685 | 0.8049 |
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+ | 0.0008 | 42.0 | 252 | 0.6686 | 0.8049 |
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+ | 0.0008 | 43.0 | 258 | 0.6686 | 0.8049 |
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+ | 0.0007 | 44.0 | 264 | 0.6686 | 0.8049 |
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+ | 0.0008 | 45.0 | 270 | 0.6686 | 0.8049 |
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+ | 0.0008 | 46.0 | 276 | 0.6686 | 0.8049 |
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+ | 0.0008 | 47.0 | 282 | 0.6686 | 0.8049 |
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+ | 0.0008 | 48.0 | 288 | 0.6686 | 0.8049 |
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+ | 0.0008 | 49.0 | 294 | 0.6686 | 0.8049 |
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+ | 0.0008 | 50.0 | 300 | 0.6686 | 0.8049 |
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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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