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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-small-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_small_rms_00001_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: 0.9116666666666666
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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_small_rms_00001_fold3
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+
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+ This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0298
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+ - Accuracy: 0.9117
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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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+ | 0.17 | 1.0 | 750 | 0.2376 | 0.9167 |
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+ | 0.1586 | 2.0 | 1500 | 0.3127 | 0.9117 |
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+ | 0.0361 | 3.0 | 2250 | 0.4163 | 0.9033 |
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+ | 0.0337 | 4.0 | 3000 | 0.5484 | 0.89 |
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+ | 0.0423 | 5.0 | 3750 | 0.5723 | 0.91 |
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+ | 0.0287 | 6.0 | 4500 | 0.6189 | 0.905 |
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+ | 0.0936 | 7.0 | 5250 | 0.8112 | 0.895 |
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+ | 0.0008 | 8.0 | 6000 | 0.7783 | 0.8967 |
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+ | 0.0117 | 9.0 | 6750 | 0.8326 | 0.8983 |
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+ | 0.0553 | 10.0 | 7500 | 0.8619 | 0.8967 |
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+ | 0.0 | 11.0 | 8250 | 0.7664 | 0.895 |
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+ | 0.0 | 12.0 | 9000 | 0.9064 | 0.8917 |
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+ | 0.022 | 13.0 | 9750 | 0.8767 | 0.905 |
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+ | 0.0003 | 14.0 | 10500 | 0.8256 | 0.8967 |
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+ | 0.0 | 15.0 | 11250 | 0.8920 | 0.8983 |
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+ | 0.0 | 16.0 | 12000 | 0.8919 | 0.8883 |
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+ | 0.0005 | 17.0 | 12750 | 0.7873 | 0.91 |
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+ | 0.0002 | 18.0 | 13500 | 1.0358 | 0.8833 |
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+ | 0.0 | 19.0 | 14250 | 0.9585 | 0.8933 |
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+ | 0.0 | 20.0 | 15000 | 0.9183 | 0.8933 |
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+ | 0.02 | 21.0 | 15750 | 1.0608 | 0.8867 |
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+ | 0.0 | 22.0 | 16500 | 0.9497 | 0.8983 |
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+ | 0.0 | 23.0 | 17250 | 0.9676 | 0.895 |
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+ | 0.0 | 24.0 | 18000 | 0.9490 | 0.8983 |
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+ | 0.001 | 25.0 | 18750 | 1.0068 | 0.8983 |
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+ | 0.0001 | 26.0 | 19500 | 0.9409 | 0.9017 |
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+ | 0.0 | 27.0 | 20250 | 0.9205 | 0.8933 |
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+ | 0.0006 | 28.0 | 21000 | 0.9294 | 0.9033 |
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+ | 0.0 | 29.0 | 21750 | 0.9650 | 0.8917 |
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+ | 0.0 | 30.0 | 22500 | 1.0551 | 0.8933 |
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+ | 0.0 | 31.0 | 23250 | 0.9687 | 0.895 |
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+ | 0.0 | 32.0 | 24000 | 0.9869 | 0.8933 |
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+ | 0.0 | 33.0 | 24750 | 0.9708 | 0.905 |
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+ | 0.0 | 34.0 | 25500 | 0.9496 | 0.9067 |
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+ | 0.0 | 35.0 | 26250 | 0.9626 | 0.91 |
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+ | 0.0 | 36.0 | 27000 | 1.0150 | 0.9033 |
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+ | 0.0 | 37.0 | 27750 | 0.9930 | 0.9017 |
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+ | 0.0 | 38.0 | 28500 | 0.9861 | 0.905 |
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+ | 0.0 | 39.0 | 29250 | 1.0163 | 0.9033 |
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+ | 0.0 | 40.0 | 30000 | 1.0159 | 0.9017 |
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+ | 0.0 | 41.0 | 30750 | 1.0242 | 0.9033 |
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+ | 0.0 | 42.0 | 31500 | 1.0278 | 0.905 |
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+ | 0.0 | 43.0 | 32250 | 1.0282 | 0.9033 |
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+ | 0.0 | 44.0 | 33000 | 1.0251 | 0.9083 |
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+ | 0.0 | 45.0 | 33750 | 1.0218 | 0.91 |
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+ | 0.0 | 46.0 | 34500 | 1.0275 | 0.91 |
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+ | 0.0 | 47.0 | 35250 | 1.0270 | 0.9083 |
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+ | 0.0 | 48.0 | 36000 | 1.0297 | 0.91 |
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+ | 0.0 | 49.0 | 36750 | 1.0292 | 0.91 |
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+ | 0.0 | 50.0 | 37500 | 1.0298 | 0.9117 |
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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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