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hushem_40x_beit_large_adamax_0001_fold4

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-large-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_40x_beit_large_adamax_0001_fold4
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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: 0.9761904761904762
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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_40x_beit_large_adamax_0001_fold4
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+
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+ This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1076
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+ - Accuracy: 0.9762
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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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+ | 0.0165 | 1.0 | 219 | 0.5362 | 0.8810 |
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+ | 0.0002 | 2.0 | 438 | 0.2899 | 0.9048 |
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+ | 0.002 | 3.0 | 657 | 0.2264 | 0.9286 |
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+ | 0.0 | 4.0 | 876 | 0.0134 | 1.0 |
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+ | 0.0 | 5.0 | 1095 | 0.0221 | 0.9762 |
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+ | 0.0 | 6.0 | 1314 | 0.0312 | 0.9762 |
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+ | 0.0 | 7.0 | 1533 | 0.0455 | 0.9762 |
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+ | 0.0 | 8.0 | 1752 | 0.1418 | 0.9524 |
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+ | 0.0 | 9.0 | 1971 | 0.1481 | 0.9762 |
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+ | 0.0 | 10.0 | 2190 | 0.0104 | 1.0 |
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+ | 0.0 | 11.0 | 2409 | 0.0643 | 0.9762 |
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+ | 0.0 | 12.0 | 2628 | 0.0455 | 0.9762 |
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+ | 0.0 | 13.0 | 2847 | 0.0444 | 0.9762 |
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+ | 0.0 | 14.0 | 3066 | 0.0410 | 0.9762 |
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+ | 0.0 | 15.0 | 3285 | 0.0550 | 0.9762 |
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+ | 0.0 | 16.0 | 3504 | 0.0281 | 0.9762 |
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+ | 0.0 | 17.0 | 3723 | 0.0303 | 0.9762 |
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+ | 0.0 | 18.0 | 3942 | 0.0305 | 0.9762 |
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+ | 0.0 | 19.0 | 4161 | 0.0952 | 0.9762 |
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+ | 0.0 | 20.0 | 4380 | 0.0860 | 0.9762 |
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+ | 0.0 | 21.0 | 4599 | 0.0315 | 0.9762 |
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+ | 0.0 | 22.0 | 4818 | 0.0334 | 0.9762 |
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+ | 0.0 | 23.0 | 5037 | 0.0409 | 0.9762 |
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+ | 0.0004 | 24.0 | 5256 | 0.3332 | 0.9524 |
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+ | 0.0 | 25.0 | 5475 | 0.1274 | 0.9762 |
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+ | 0.0071 | 26.0 | 5694 | 0.1341 | 0.9762 |
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+ | 0.0 | 27.0 | 5913 | 0.1590 | 0.9762 |
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+ | 0.0 | 28.0 | 6132 | 0.1155 | 0.9762 |
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+ | 0.0 | 29.0 | 6351 | 0.1162 | 0.9762 |
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+ | 0.0 | 30.0 | 6570 | 0.1374 | 0.9762 |
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+ | 0.0 | 31.0 | 6789 | 0.1350 | 0.9762 |
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+ | 0.0 | 32.0 | 7008 | 0.1260 | 0.9762 |
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+ | 0.0 | 33.0 | 7227 | 0.1236 | 0.9762 |
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+ | 0.0 | 34.0 | 7446 | 0.1361 | 0.9762 |
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+ | 0.0 | 35.0 | 7665 | 0.1318 | 0.9762 |
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+ | 0.0 | 36.0 | 7884 | 0.1308 | 0.9762 |
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+ | 0.0 | 37.0 | 8103 | 0.1168 | 0.9762 |
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+ | 0.0 | 38.0 | 8322 | 0.1190 | 0.9762 |
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+ | 0.0 | 39.0 | 8541 | 0.0898 | 0.9762 |
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+ | 0.0 | 40.0 | 8760 | 0.0926 | 0.9762 |
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+ | 0.0 | 41.0 | 8979 | 0.0919 | 0.9762 |
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+ | 0.0 | 42.0 | 9198 | 0.0987 | 0.9762 |
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+ | 0.0 | 43.0 | 9417 | 0.0991 | 0.9762 |
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+ | 0.0 | 44.0 | 9636 | 0.1047 | 0.9762 |
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+ | 0.0 | 45.0 | 9855 | 0.1049 | 0.9762 |
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+ | 0.0 | 46.0 | 10074 | 0.1056 | 0.9762 |
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+ | 0.0 | 47.0 | 10293 | 0.1068 | 0.9762 |
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+ | 0.0 | 48.0 | 10512 | 0.1039 | 0.9762 |
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+ | 0.0 | 49.0 | 10731 | 0.1062 | 0.9762 |
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+ | 0.0 | 50.0 | 10950 | 0.1076 | 0.9762 |
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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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