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hushem_5x_beit_base_rms_00001_fold2

Image Classification
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  1. README.md +125 -0
  2. model.safetensors +1 -1
  3. runs/Nov29_09-24-55_ac8792add2e0/events.out.tfevents.1701249896.ac8792add2e0.2336.24 +2 -2
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: hushem_5x_beit_base_rms_00001_fold2
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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: 0.8666666666666667
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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_beit_base_rms_00001_fold2
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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: 0.8184
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+ - Accuracy: 0.8667
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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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+ | 0.6865 | 1.0 | 27 | 0.7969 | 0.7556 |
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+ | 0.1615 | 2.0 | 54 | 0.9353 | 0.7778 |
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+ | 0.041 | 3.0 | 81 | 1.0745 | 0.6444 |
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+ | 0.0119 | 4.0 | 108 | 1.0481 | 0.7333 |
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+ | 0.0095 | 5.0 | 135 | 0.6063 | 0.8667 |
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+ | 0.0013 | 6.0 | 162 | 0.6520 | 0.8444 |
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+ | 0.0015 | 7.0 | 189 | 0.7604 | 0.8667 |
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+ | 0.0013 | 8.0 | 216 | 0.7595 | 0.8444 |
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+ | 0.0008 | 9.0 | 243 | 0.8299 | 0.8444 |
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+ | 0.0008 | 10.0 | 270 | 0.6509 | 0.8444 |
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+ | 0.0009 | 11.0 | 297 | 0.7989 | 0.8444 |
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+ | 0.0002 | 12.0 | 324 | 0.8458 | 0.8444 |
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+ | 0.0005 | 13.0 | 351 | 0.6321 | 0.8667 |
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+ | 0.0002 | 14.0 | 378 | 0.6972 | 0.8444 |
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+ | 0.0002 | 15.0 | 405 | 0.7426 | 0.8667 |
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+ | 0.0005 | 16.0 | 432 | 0.9776 | 0.8 |
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+ | 0.0023 | 17.0 | 459 | 1.0180 | 0.8 |
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+ | 0.0003 | 18.0 | 486 | 1.1105 | 0.7778 |
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+ | 0.0006 | 19.0 | 513 | 0.9919 | 0.7556 |
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+ | 0.0002 | 20.0 | 540 | 1.0177 | 0.8 |
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+ | 0.0012 | 21.0 | 567 | 0.9992 | 0.8444 |
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+ | 0.0003 | 22.0 | 594 | 0.9760 | 0.8444 |
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+ | 0.0047 | 23.0 | 621 | 0.9891 | 0.8 |
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+ | 0.0061 | 24.0 | 648 | 0.9730 | 0.8222 |
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+ | 0.0002 | 25.0 | 675 | 0.8247 | 0.8222 |
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+ | 0.0001 | 26.0 | 702 | 0.8270 | 0.8667 |
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+ | 0.0001 | 27.0 | 729 | 0.7978 | 0.8222 |
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+ | 0.0 | 28.0 | 756 | 0.8136 | 0.8444 |
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+ | 0.0001 | 29.0 | 783 | 0.8553 | 0.8444 |
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+ | 0.0001 | 30.0 | 810 | 0.9423 | 0.8444 |
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+ | 0.0001 | 31.0 | 837 | 0.9286 | 0.8222 |
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+ | 0.0001 | 32.0 | 864 | 0.9464 | 0.8222 |
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+ | 0.0002 | 33.0 | 891 | 0.8713 | 0.8444 |
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+ | 0.0001 | 34.0 | 918 | 0.8762 | 0.8444 |
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+ | 0.0001 | 35.0 | 945 | 0.9092 | 0.8667 |
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+ | 0.0 | 36.0 | 972 | 0.9547 | 0.8444 |
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+ | 0.0 | 37.0 | 999 | 0.9283 | 0.8444 |
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+ | 0.0 | 38.0 | 1026 | 0.8639 | 0.8444 |
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+ | 0.0001 | 39.0 | 1053 | 0.8477 | 0.8667 |
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+ | 0.0 | 40.0 | 1080 | 0.8432 | 0.8667 |
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+ | 0.0 | 41.0 | 1107 | 0.8325 | 0.8667 |
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+ | 0.0 | 42.0 | 1134 | 0.7851 | 0.8667 |
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+ | 0.0003 | 43.0 | 1161 | 0.7875 | 0.8667 |
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+ | 0.0 | 44.0 | 1188 | 0.7888 | 0.8667 |
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+ | 0.0001 | 45.0 | 1215 | 0.8006 | 0.8889 |
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+ | 0.0001 | 46.0 | 1242 | 0.8075 | 0.8889 |
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+ | 0.0001 | 47.0 | 1269 | 0.8158 | 0.8889 |
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+ | 0.0 | 48.0 | 1296 | 0.8184 | 0.8667 |
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+ | 0.0002 | 49.0 | 1323 | 0.8184 | 0.8667 |
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+ | 0.0001 | 50.0 | 1350 | 0.8184 | 0.8667 |
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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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