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smids_3x_beit_base_adamax_001_fold1

Image Classification
Transformers
PyTorch
beit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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  1. README.md +125 -0
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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_adamax_001_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: 0.8848080133555927
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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_adamax_001_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: 0.9792
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+ - Accuracy: 0.8848
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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: 0.001
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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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+ | 0.5347 | 1.0 | 226 | 0.5865 | 0.7796 |
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+ | 0.481 | 2.0 | 452 | 0.4735 | 0.8047 |
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+ | 0.392 | 3.0 | 678 | 0.3827 | 0.8397 |
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+ | 0.3513 | 4.0 | 904 | 0.4550 | 0.8080 |
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+ | 0.3191 | 5.0 | 1130 | 0.5279 | 0.8364 |
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+ | 0.2659 | 6.0 | 1356 | 0.3980 | 0.8564 |
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+ | 0.2461 | 7.0 | 1582 | 0.3991 | 0.8798 |
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+ | 0.2656 | 8.0 | 1808 | 0.4588 | 0.8664 |
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+ | 0.1595 | 9.0 | 2034 | 0.4089 | 0.8715 |
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+ | 0.1456 | 10.0 | 2260 | 0.4772 | 0.8631 |
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+ | 0.0575 | 11.0 | 2486 | 0.5294 | 0.8614 |
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+ | 0.0953 | 12.0 | 2712 | 0.4940 | 0.8748 |
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+ | 0.0784 | 13.0 | 2938 | 0.5992 | 0.8548 |
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+ | 0.0313 | 14.0 | 3164 | 0.5155 | 0.8731 |
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+ | 0.1006 | 15.0 | 3390 | 0.5131 | 0.8898 |
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+ | 0.0394 | 16.0 | 3616 | 0.6916 | 0.8815 |
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+ | 0.0372 | 17.0 | 3842 | 0.6693 | 0.8748 |
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+ | 0.0368 | 18.0 | 4068 | 0.7021 | 0.8765 |
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+ | 0.0584 | 19.0 | 4294 | 0.7487 | 0.8715 |
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+ | 0.0031 | 20.0 | 4520 | 0.6697 | 0.8865 |
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+ | 0.0088 | 21.0 | 4746 | 0.7746 | 0.8865 |
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+ | 0.0319 | 22.0 | 4972 | 0.7417 | 0.8614 |
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+ | 0.0133 | 23.0 | 5198 | 0.9026 | 0.8581 |
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+ | 0.001 | 24.0 | 5424 | 0.7822 | 0.8865 |
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+ | 0.0186 | 25.0 | 5650 | 0.8476 | 0.8698 |
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+ | 0.0405 | 26.0 | 5876 | 0.7548 | 0.8915 |
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+ | 0.0061 | 27.0 | 6102 | 0.7539 | 0.8798 |
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+ | 0.0213 | 28.0 | 6328 | 0.8310 | 0.8848 |
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+ | 0.0063 | 29.0 | 6554 | 0.7841 | 0.8781 |
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+ | 0.0003 | 30.0 | 6780 | 0.8782 | 0.8798 |
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+ | 0.0005 | 31.0 | 7006 | 0.8431 | 0.8865 |
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+ | 0.0002 | 32.0 | 7232 | 0.8900 | 0.8915 |
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+ | 0.0077 | 33.0 | 7458 | 0.9508 | 0.8898 |
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+ | 0.0001 | 34.0 | 7684 | 0.8836 | 0.8848 |
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+ | 0.0001 | 35.0 | 7910 | 0.8853 | 0.8898 |
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+ | 0.0002 | 36.0 | 8136 | 0.8931 | 0.8865 |
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+ | 0.0 | 37.0 | 8362 | 0.9183 | 0.8831 |
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+ | 0.0 | 38.0 | 8588 | 0.9668 | 0.8865 |
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+ | 0.0 | 39.0 | 8814 | 0.9612 | 0.8881 |
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+ | 0.0002 | 40.0 | 9040 | 0.9819 | 0.8848 |
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+ | 0.0033 | 41.0 | 9266 | 0.9561 | 0.8915 |
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+ | 0.0038 | 42.0 | 9492 | 0.9632 | 0.8915 |
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+ | 0.0001 | 43.0 | 9718 | 0.9739 | 0.8865 |
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+ | 0.0 | 44.0 | 9944 | 0.9696 | 0.8848 |
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+ | 0.0 | 45.0 | 10170 | 0.9928 | 0.8815 |
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+ | 0.0 | 46.0 | 10396 | 0.9848 | 0.8798 |
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+ | 0.0 | 47.0 | 10622 | 0.9849 | 0.8815 |
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+ | 0.0 | 48.0 | 10848 | 0.9754 | 0.8831 |
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+ | 0.0 | 49.0 | 11074 | 0.9791 | 0.8848 |
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+ | 0.0 | 50.0 | 11300 | 0.9792 | 0.8848 |
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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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