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End of training

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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: smids_10x_deit_base_sgd_00001_fold1
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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: 0.5776293823038398
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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_10x_deit_base_sgd_00001_fold1
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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: 0.9942
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+ - Accuracy: 0.5776
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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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+ | 1.1101 | 1.0 | 751 | 1.0912 | 0.3940 |
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+ | 1.1137 | 2.0 | 1502 | 1.0874 | 0.3990 |
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+ | 1.0977 | 3.0 | 2253 | 1.0838 | 0.4057 |
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+ | 1.0963 | 4.0 | 3004 | 1.0803 | 0.4157 |
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+ | 1.0734 | 5.0 | 3755 | 1.0769 | 0.4307 |
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+ | 1.0814 | 6.0 | 4506 | 1.0737 | 0.4424 |
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+ | 1.0905 | 7.0 | 5257 | 1.0705 | 0.4558 |
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+ | 1.0682 | 8.0 | 6008 | 1.0673 | 0.4508 |
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+ | 1.0698 | 9.0 | 6759 | 1.0643 | 0.4524 |
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+ | 1.066 | 10.0 | 7510 | 1.0613 | 0.4608 |
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+ | 1.0809 | 11.0 | 8261 | 1.0584 | 0.4691 |
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+ | 1.0569 | 12.0 | 9012 | 1.0556 | 0.4708 |
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+ | 1.0524 | 13.0 | 9763 | 1.0527 | 0.4908 |
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+ | 1.051 | 14.0 | 10514 | 1.0500 | 0.5042 |
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+ | 1.0693 | 15.0 | 11265 | 1.0473 | 0.5092 |
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+ | 1.0517 | 16.0 | 12016 | 1.0446 | 0.5175 |
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+ | 1.0588 | 17.0 | 12767 | 1.0419 | 0.5159 |
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+ | 1.0399 | 18.0 | 13518 | 1.0394 | 0.5192 |
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+ | 1.0367 | 19.0 | 14269 | 1.0368 | 0.5225 |
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+ | 1.0366 | 20.0 | 15020 | 1.0343 | 0.5259 |
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+ | 1.0281 | 21.0 | 15771 | 1.0318 | 0.5326 |
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+ | 1.036 | 22.0 | 16522 | 1.0294 | 0.5342 |
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+ | 1.0334 | 23.0 | 17273 | 1.0270 | 0.5359 |
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+ | 1.0262 | 24.0 | 18024 | 1.0247 | 0.5376 |
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+ | 1.0153 | 25.0 | 18775 | 1.0224 | 0.5392 |
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+ | 1.0269 | 26.0 | 19526 | 1.0202 | 0.5409 |
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+ | 1.0163 | 27.0 | 20277 | 1.0180 | 0.5459 |
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+ | 1.0112 | 28.0 | 21028 | 1.0159 | 0.5459 |
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+ | 1.0292 | 29.0 | 21779 | 1.0139 | 0.5509 |
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+ | 1.0159 | 30.0 | 22530 | 1.0120 | 0.5526 |
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+ | 1.0063 | 31.0 | 23281 | 1.0102 | 0.5526 |
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+ | 1.0238 | 32.0 | 24032 | 1.0085 | 0.5543 |
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+ | 0.9962 | 33.0 | 24783 | 1.0069 | 0.5543 |
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+ | 1.0016 | 34.0 | 25534 | 1.0053 | 0.5593 |
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+ | 1.0116 | 35.0 | 26285 | 1.0039 | 0.5593 |
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+ | 1.0035 | 36.0 | 27036 | 1.0026 | 0.5626 |
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+ | 1.0094 | 37.0 | 27787 | 1.0013 | 0.5659 |
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+ | 0.9975 | 38.0 | 28538 | 1.0002 | 0.5676 |
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+ | 1.0065 | 39.0 | 29289 | 0.9992 | 0.5743 |
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+ | 0.9968 | 40.0 | 30040 | 0.9982 | 0.5760 |
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+ | 0.9969 | 41.0 | 30791 | 0.9974 | 0.5760 |
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+ | 0.9821 | 42.0 | 31542 | 0.9967 | 0.5776 |
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+ | 0.9849 | 43.0 | 32293 | 0.9961 | 0.5776 |
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+ | 1.002 | 44.0 | 33044 | 0.9955 | 0.5776 |
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+ | 1.0006 | 45.0 | 33795 | 0.9951 | 0.5776 |
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+ | 1.0018 | 46.0 | 34546 | 0.9948 | 0.5776 |
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+ | 0.9926 | 47.0 | 35297 | 0.9945 | 0.5776 |
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+ | 1.0075 | 48.0 | 36048 | 0.9943 | 0.5776 |
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+ | 0.9883 | 49.0 | 36799 | 0.9942 | 0.5776 |
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+ | 0.9793 | 50.0 | 37550 | 0.9942 | 0.5776 |
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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 2.1.0+cu121
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.2
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