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smids_3x_beit_base_adamax_0001_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-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_0001_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: 0.91
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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_0001_fold3
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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: 0.8017
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+ - Accuracy: 0.91
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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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+ | 0.3218 | 1.0 | 225 | 0.3049 | 0.8783 |
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+ | 0.1886 | 2.0 | 450 | 0.2841 | 0.8967 |
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+ | 0.0936 | 3.0 | 675 | 0.2901 | 0.905 |
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+ | 0.0347 | 4.0 | 900 | 0.3730 | 0.9067 |
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+ | 0.0374 | 5.0 | 1125 | 0.5485 | 0.885 |
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+ | 0.0265 | 6.0 | 1350 | 0.5296 | 0.8933 |
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+ | 0.0077 | 7.0 | 1575 | 0.5235 | 0.9083 |
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+ | 0.0372 | 8.0 | 1800 | 0.5900 | 0.915 |
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+ | 0.0065 | 9.0 | 2025 | 0.6549 | 0.905 |
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+ | 0.0316 | 10.0 | 2250 | 0.8684 | 0.88 |
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+ | 0.0273 | 11.0 | 2475 | 0.6609 | 0.9133 |
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+ | 0.0029 | 12.0 | 2700 | 0.7388 | 0.8983 |
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+ | 0.001 | 13.0 | 2925 | 0.7878 | 0.8933 |
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+ | 0.0056 | 14.0 | 3150 | 0.7685 | 0.9 |
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+ | 0.0005 | 15.0 | 3375 | 0.7882 | 0.8933 |
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+ | 0.0052 | 16.0 | 3600 | 0.7154 | 0.9017 |
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+ | 0.0026 | 17.0 | 3825 | 0.6645 | 0.8967 |
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+ | 0.0001 | 18.0 | 4050 | 0.7811 | 0.8917 |
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+ | 0.0005 | 19.0 | 4275 | 0.8281 | 0.8883 |
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+ | 0.001 | 20.0 | 4500 | 0.6603 | 0.9083 |
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+ | 0.0022 | 21.0 | 4725 | 0.7385 | 0.905 |
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+ | 0.0001 | 22.0 | 4950 | 0.7367 | 0.9033 |
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+ | 0.0002 | 23.0 | 5175 | 0.8135 | 0.885 |
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+ | 0.0001 | 24.0 | 5400 | 0.8005 | 0.8983 |
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+ | 0.0193 | 25.0 | 5625 | 0.8350 | 0.8883 |
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+ | 0.0 | 26.0 | 5850 | 0.7434 | 0.905 |
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+ | 0.0 | 27.0 | 6075 | 0.7179 | 0.905 |
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+ | 0.0001 | 28.0 | 6300 | 0.8254 | 0.9 |
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+ | 0.0047 | 29.0 | 6525 | 0.8746 | 0.8933 |
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+ | 0.006 | 30.0 | 6750 | 0.8594 | 0.8983 |
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+ | 0.0021 | 31.0 | 6975 | 0.8754 | 0.8917 |
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+ | 0.0 | 32.0 | 7200 | 0.8773 | 0.8983 |
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+ | 0.0 | 33.0 | 7425 | 0.8925 | 0.8867 |
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+ | 0.0 | 34.0 | 7650 | 0.9018 | 0.89 |
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+ | 0.0 | 35.0 | 7875 | 0.8530 | 0.8983 |
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+ | 0.0 | 36.0 | 8100 | 0.7923 | 0.905 |
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+ | 0.0 | 37.0 | 8325 | 0.7837 | 0.905 |
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+ | 0.0 | 38.0 | 8550 | 0.8324 | 0.9017 |
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+ | 0.0 | 39.0 | 8775 | 0.8536 | 0.895 |
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+ | 0.0 | 40.0 | 9000 | 0.8379 | 0.8917 |
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+ | 0.0009 | 41.0 | 9225 | 0.8179 | 0.8983 |
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+ | 0.0 | 42.0 | 9450 | 0.8003 | 0.9067 |
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+ | 0.0 | 43.0 | 9675 | 0.8131 | 0.9033 |
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+ | 0.0 | 44.0 | 9900 | 0.7802 | 0.9117 |
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+ | 0.0 | 45.0 | 10125 | 0.8111 | 0.9 |
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+ | 0.0 | 46.0 | 10350 | 0.8012 | 0.9033 |
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+ | 0.0026 | 47.0 | 10575 | 0.7937 | 0.9117 |
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+ | 0.0 | 48.0 | 10800 | 0.8052 | 0.9117 |
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+ | 0.0 | 49.0 | 11025 | 0.8066 | 0.9083 |
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+ | 0.0 | 50.0 | 11250 | 0.8017 | 0.91 |
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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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