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hushem_40x_beit_large_adamax_00001_fold3

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_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: 0.8837209302325582
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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_00001_fold3
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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: 1.0094
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+ - Accuracy: 0.8837
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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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+ | 0.0088 | 1.0 | 217 | 0.5009 | 0.8605 |
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+ | 0.0048 | 2.0 | 434 | 0.5720 | 0.8837 |
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+ | 0.0002 | 3.0 | 651 | 0.6684 | 0.8605 |
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+ | 0.0005 | 4.0 | 868 | 0.6185 | 0.8605 |
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+ | 0.0001 | 5.0 | 1085 | 0.7115 | 0.8837 |
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+ | 0.0002 | 6.0 | 1302 | 0.7630 | 0.8837 |
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+ | 0.0001 | 7.0 | 1519 | 0.6588 | 0.8837 |
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+ | 0.0 | 8.0 | 1736 | 0.6227 | 0.8837 |
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+ | 0.0001 | 9.0 | 1953 | 0.5468 | 0.9070 |
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+ | 0.0 | 10.0 | 2170 | 0.7021 | 0.8837 |
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+ | 0.0 | 11.0 | 2387 | 0.7605 | 0.8605 |
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+ | 0.0002 | 12.0 | 2604 | 0.7994 | 0.8837 |
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+ | 0.0 | 13.0 | 2821 | 1.0881 | 0.8372 |
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+ | 0.0002 | 14.0 | 3038 | 0.8413 | 0.8605 |
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+ | 0.0002 | 15.0 | 3255 | 0.9237 | 0.8837 |
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+ | 0.0 | 16.0 | 3472 | 0.9623 | 0.8605 |
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+ | 0.0 | 17.0 | 3689 | 0.9912 | 0.8605 |
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+ | 0.0001 | 18.0 | 3906 | 0.7287 | 0.9070 |
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+ | 0.0 | 19.0 | 4123 | 0.9687 | 0.8372 |
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+ | 0.0 | 20.0 | 4340 | 0.6790 | 0.9070 |
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+ | 0.0 | 21.0 | 4557 | 0.8424 | 0.9070 |
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+ | 0.0 | 22.0 | 4774 | 0.7674 | 0.9070 |
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+ | 0.0 | 23.0 | 4991 | 0.8450 | 0.9070 |
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+ | 0.0 | 24.0 | 5208 | 0.8947 | 0.8837 |
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+ | 0.0 | 25.0 | 5425 | 0.8485 | 0.8837 |
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+ | 0.0 | 26.0 | 5642 | 0.9138 | 0.8837 |
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+ | 0.0 | 27.0 | 5859 | 0.9516 | 0.8837 |
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+ | 0.0 | 28.0 | 6076 | 0.8628 | 0.9070 |
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+ | 0.0 | 29.0 | 6293 | 0.9458 | 0.8837 |
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+ | 0.0 | 30.0 | 6510 | 0.9582 | 0.8837 |
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+ | 0.0 | 31.0 | 6727 | 1.1730 | 0.8837 |
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+ | 0.0 | 32.0 | 6944 | 1.0331 | 0.8837 |
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+ | 0.0 | 33.0 | 7161 | 1.1055 | 0.8605 |
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+ | 0.0 | 34.0 | 7378 | 0.9893 | 0.8837 |
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+ | 0.0 | 35.0 | 7595 | 1.0353 | 0.8837 |
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+ | 0.0 | 36.0 | 7812 | 1.0373 | 0.8837 |
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+ | 0.0 | 37.0 | 8029 | 1.0358 | 0.8837 |
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+ | 0.0 | 38.0 | 8246 | 1.0426 | 0.8837 |
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+ | 0.0 | 39.0 | 8463 | 1.1391 | 0.8837 |
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+ | 0.0 | 40.0 | 8680 | 1.0647 | 0.8837 |
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+ | 0.0 | 41.0 | 8897 | 1.0082 | 0.8837 |
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+ | 0.0 | 42.0 | 9114 | 1.0681 | 0.8837 |
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+ | 0.0 | 43.0 | 9331 | 1.0189 | 0.8837 |
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+ | 0.0 | 44.0 | 9548 | 1.0129 | 0.8837 |
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+ | 0.0 | 45.0 | 9765 | 1.0237 | 0.8837 |
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+ | 0.0 | 46.0 | 9982 | 1.0239 | 0.8837 |
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+ | 0.0 | 47.0 | 10199 | 1.0008 | 0.8837 |
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+ | 0.0 | 48.0 | 10416 | 1.0075 | 0.8837 |
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+ | 0.0001 | 49.0 | 10633 | 1.0115 | 0.8837 |
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+ | 0.0 | 50.0 | 10850 | 1.0094 | 0.8837 |
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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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