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smids_3x_beit_base_sgd_0001_fold1

Image Classification
Transformers
PyTorch
beit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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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: microsoft/beit-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_3x_beit_base_sgd_0001_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: 0.7512520868113522
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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_3x_beit_base_sgd_0001_fold1
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+
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+ This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-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: 0.6006
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+ - Accuracy: 0.7513
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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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+ | 1.2428 | 1.0 | 226 | 1.2900 | 0.3139 |
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+ | 1.1165 | 2.0 | 452 | 1.2280 | 0.3389 |
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+ | 1.085 | 3.0 | 678 | 1.1717 | 0.3606 |
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+ | 1.0873 | 4.0 | 904 | 1.1174 | 0.3973 |
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+ | 1.0209 | 5.0 | 1130 | 1.0648 | 0.4207 |
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+ | 0.9387 | 6.0 | 1356 | 1.0163 | 0.4741 |
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+ | 0.9347 | 7.0 | 1582 | 0.9719 | 0.5175 |
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+ | 0.8727 | 8.0 | 1808 | 0.9312 | 0.5626 |
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+ | 0.8169 | 9.0 | 2034 | 0.8951 | 0.5993 |
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+ | 0.861 | 10.0 | 2260 | 0.8623 | 0.6160 |
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+ | 0.8138 | 11.0 | 2486 | 0.8344 | 0.6327 |
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+ | 0.7635 | 12.0 | 2712 | 0.8096 | 0.6444 |
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+ | 0.7469 | 13.0 | 2938 | 0.7879 | 0.6477 |
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+ | 0.7457 | 14.0 | 3164 | 0.7697 | 0.6561 |
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+ | 0.6958 | 15.0 | 3390 | 0.7527 | 0.6728 |
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+ | 0.6961 | 16.0 | 3616 | 0.7374 | 0.6795 |
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+ | 0.6436 | 17.0 | 3842 | 0.7245 | 0.6878 |
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+ | 0.6513 | 18.0 | 4068 | 0.7127 | 0.6912 |
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+ | 0.6672 | 19.0 | 4294 | 0.7016 | 0.6962 |
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+ | 0.6558 | 20.0 | 4520 | 0.6918 | 0.7012 |
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+ | 0.6466 | 21.0 | 4746 | 0.6834 | 0.7028 |
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+ | 0.6561 | 22.0 | 4972 | 0.6751 | 0.7045 |
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+ | 0.6208 | 23.0 | 5198 | 0.6670 | 0.7145 |
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+ | 0.6499 | 24.0 | 5424 | 0.6602 | 0.7162 |
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+ | 0.6316 | 25.0 | 5650 | 0.6537 | 0.7179 |
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+ | 0.6488 | 26.0 | 5876 | 0.6486 | 0.7245 |
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+ | 0.6013 | 27.0 | 6102 | 0.6431 | 0.7229 |
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+ | 0.6349 | 28.0 | 6328 | 0.6385 | 0.7295 |
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+ | 0.5571 | 29.0 | 6554 | 0.6343 | 0.7312 |
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+ | 0.6883 | 30.0 | 6780 | 0.6303 | 0.7329 |
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+ | 0.5874 | 31.0 | 7006 | 0.6269 | 0.7362 |
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+ | 0.5957 | 32.0 | 7232 | 0.6236 | 0.7412 |
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+ | 0.5454 | 33.0 | 7458 | 0.6209 | 0.7446 |
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+ | 0.5392 | 34.0 | 7684 | 0.6182 | 0.7446 |
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+ | 0.6014 | 35.0 | 7910 | 0.6160 | 0.7462 |
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+ | 0.5394 | 36.0 | 8136 | 0.6140 | 0.7462 |
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+ | 0.5557 | 37.0 | 8362 | 0.6119 | 0.7479 |
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+ | 0.5868 | 38.0 | 8588 | 0.6101 | 0.7479 |
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+ | 0.5673 | 39.0 | 8814 | 0.6084 | 0.7479 |
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+ | 0.5576 | 40.0 | 9040 | 0.6071 | 0.7479 |
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+ | 0.5598 | 41.0 | 9266 | 0.6057 | 0.7479 |
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+ | 0.5493 | 42.0 | 9492 | 0.6045 | 0.7496 |
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+ | 0.573 | 43.0 | 9718 | 0.6035 | 0.7513 |
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+ | 0.5428 | 44.0 | 9944 | 0.6027 | 0.7513 |
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+ | 0.6174 | 45.0 | 10170 | 0.6020 | 0.7513 |
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+ | 0.5654 | 46.0 | 10396 | 0.6015 | 0.7513 |
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+ | 0.5911 | 47.0 | 10622 | 0.6010 | 0.7513 |
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+ | 0.5644 | 48.0 | 10848 | 0.6008 | 0.7513 |
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+ | 0.5284 | 49.0 | 11074 | 0.6007 | 0.7513 |
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+ | 0.5888 | 50.0 | 11300 | 0.6006 | 0.7513 |
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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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