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hushem_5x_deit_base_rms_001_fold3

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  2. model.safetensors +1 -1
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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_5x_deit_base_rms_001_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: 0.5348837209302325
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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_base_rms_001_fold3
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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: 4.1290
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+ - Accuracy: 0.5349
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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: 0.001
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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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+ | 2.2595 | 1.0 | 28 | 2.7858 | 0.2558 |
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+ | 1.4501 | 2.0 | 56 | 1.7856 | 0.2558 |
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+ | 1.3782 | 3.0 | 84 | 1.3873 | 0.3721 |
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+ | 1.2094 | 4.0 | 112 | 1.1943 | 0.3953 |
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+ | 1.0231 | 5.0 | 140 | 1.6338 | 0.3023 |
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+ | 1.0191 | 6.0 | 168 | 1.7056 | 0.2558 |
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+ | 1.0547 | 7.0 | 196 | 1.1755 | 0.4884 |
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+ | 1.0296 | 8.0 | 224 | 1.0491 | 0.5349 |
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+ | 1.0202 | 9.0 | 252 | 2.3436 | 0.2791 |
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+ | 1.0203 | 10.0 | 280 | 1.0971 | 0.4419 |
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+ | 0.9795 | 11.0 | 308 | 1.0790 | 0.5581 |
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+ | 0.955 | 12.0 | 336 | 1.4547 | 0.6047 |
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+ | 0.9606 | 13.0 | 364 | 0.9445 | 0.6512 |
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+ | 0.9236 | 14.0 | 392 | 1.2878 | 0.3721 |
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+ | 0.9401 | 15.0 | 420 | 0.9664 | 0.4651 |
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+ | 0.8825 | 16.0 | 448 | 0.9455 | 0.6512 |
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+ | 0.8605 | 17.0 | 476 | 0.9844 | 0.6977 |
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+ | 0.8738 | 18.0 | 504 | 1.1677 | 0.4651 |
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+ | 0.8294 | 19.0 | 532 | 1.0462 | 0.6744 |
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+ | 0.689 | 20.0 | 560 | 1.1927 | 0.6047 |
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+ | 0.7976 | 21.0 | 588 | 1.0142 | 0.7209 |
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+ | 0.741 | 22.0 | 616 | 0.7957 | 0.7907 |
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+ | 0.7475 | 23.0 | 644 | 0.7104 | 0.7209 |
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+ | 0.6791 | 24.0 | 672 | 1.7534 | 0.5349 |
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+ | 0.6457 | 25.0 | 700 | 0.9601 | 0.6512 |
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+ | 0.7254 | 26.0 | 728 | 1.1256 | 0.6279 |
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+ | 0.6589 | 27.0 | 756 | 1.4604 | 0.5349 |
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+ | 0.6888 | 28.0 | 784 | 0.8802 | 0.7209 |
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+ | 0.6341 | 29.0 | 812 | 0.9513 | 0.7442 |
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+ | 0.5815 | 30.0 | 840 | 1.2459 | 0.6047 |
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+ | 0.5918 | 31.0 | 868 | 1.5991 | 0.5116 |
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+ | 0.5623 | 32.0 | 896 | 1.5099 | 0.6279 |
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+ | 0.5389 | 33.0 | 924 | 1.3552 | 0.6744 |
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+ | 0.5523 | 34.0 | 952 | 1.5820 | 0.6279 |
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+ | 0.5205 | 35.0 | 980 | 2.2601 | 0.4651 |
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+ | 0.4888 | 36.0 | 1008 | 1.7684 | 0.5349 |
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+ | 0.4363 | 37.0 | 1036 | 2.2769 | 0.5581 |
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+ | 0.3724 | 38.0 | 1064 | 2.5879 | 0.5581 |
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+ | 0.3349 | 39.0 | 1092 | 2.2241 | 0.5581 |
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+ | 0.5052 | 40.0 | 1120 | 2.8178 | 0.4651 |
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+ | 0.3018 | 41.0 | 1148 | 2.5305 | 0.5814 |
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+ | 0.2857 | 42.0 | 1176 | 2.9348 | 0.5581 |
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+ | 0.1485 | 43.0 | 1204 | 3.1875 | 0.5581 |
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+ | 0.1386 | 44.0 | 1232 | 3.2594 | 0.6279 |
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+ | 0.1242 | 45.0 | 1260 | 3.4524 | 0.5814 |
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+ | 0.0734 | 46.0 | 1288 | 3.6284 | 0.5814 |
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+ | 0.0218 | 47.0 | 1316 | 4.0538 | 0.5349 |
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+ | 0.0226 | 48.0 | 1344 | 4.1281 | 0.5349 |
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+ | 0.01 | 49.0 | 1372 | 4.1290 | 0.5349 |
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+ | 0.0091 | 50.0 | 1400 | 4.1290 | 0.5349 |
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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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