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smids_5x_beit_base_adamax_00001_fold2

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_5x_beit_base_adamax_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: 0.8935108153078203
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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_5x_beit_base_adamax_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: 0.8334
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+ - Accuracy: 0.8935
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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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+ | 0.3036 | 1.0 | 375 | 0.2703 | 0.8918 |
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+ | 0.2118 | 2.0 | 750 | 0.2674 | 0.8968 |
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+ | 0.1557 | 3.0 | 1125 | 0.2889 | 0.8918 |
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+ | 0.074 | 4.0 | 1500 | 0.2842 | 0.9002 |
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+ | 0.0616 | 5.0 | 1875 | 0.3403 | 0.8935 |
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+ | 0.036 | 6.0 | 2250 | 0.3534 | 0.9101 |
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+ | 0.0382 | 7.0 | 2625 | 0.4309 | 0.8985 |
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+ | 0.0686 | 8.0 | 3000 | 0.4835 | 0.8985 |
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+ | 0.022 | 9.0 | 3375 | 0.5298 | 0.8935 |
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+ | 0.0158 | 10.0 | 3750 | 0.5869 | 0.9002 |
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+ | 0.0173 | 11.0 | 4125 | 0.5623 | 0.8952 |
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+ | 0.0241 | 12.0 | 4500 | 0.7014 | 0.8869 |
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+ | 0.013 | 13.0 | 4875 | 0.6238 | 0.8952 |
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+ | 0.004 | 14.0 | 5250 | 0.6124 | 0.9002 |
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+ | 0.0249 | 15.0 | 5625 | 0.6495 | 0.8935 |
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+ | 0.0004 | 16.0 | 6000 | 0.6999 | 0.8952 |
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+ | 0.0493 | 17.0 | 6375 | 0.6887 | 0.8952 |
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+ | 0.0087 | 18.0 | 6750 | 0.6681 | 0.9018 |
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+ | 0.0007 | 19.0 | 7125 | 0.6956 | 0.8985 |
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+ | 0.0126 | 20.0 | 7500 | 0.7749 | 0.8968 |
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+ | 0.024 | 21.0 | 7875 | 0.7255 | 0.9002 |
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+ | 0.0023 | 22.0 | 8250 | 0.7116 | 0.9052 |
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+ | 0.0003 | 23.0 | 8625 | 0.7428 | 0.8985 |
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+ | 0.0002 | 24.0 | 9000 | 0.7479 | 0.9002 |
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+ | 0.0001 | 25.0 | 9375 | 0.7803 | 0.8952 |
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+ | 0.0002 | 26.0 | 9750 | 0.7628 | 0.9002 |
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+ | 0.0069 | 27.0 | 10125 | 0.7997 | 0.8985 |
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+ | 0.0015 | 28.0 | 10500 | 0.7552 | 0.8985 |
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+ | 0.0269 | 29.0 | 10875 | 0.7735 | 0.9002 |
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+ | 0.0044 | 30.0 | 11250 | 0.7914 | 0.8985 |
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+ | 0.0192 | 31.0 | 11625 | 0.8157 | 0.8918 |
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+ | 0.0066 | 32.0 | 12000 | 0.8365 | 0.8952 |
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+ | 0.0069 | 33.0 | 12375 | 0.7991 | 0.8952 |
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+ | 0.0008 | 34.0 | 12750 | 0.8440 | 0.8968 |
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+ | 0.0002 | 35.0 | 13125 | 0.8522 | 0.8985 |
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+ | 0.0024 | 36.0 | 13500 | 0.8528 | 0.8968 |
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+ | 0.0031 | 37.0 | 13875 | 0.8295 | 0.8968 |
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+ | 0.0002 | 38.0 | 14250 | 0.8478 | 0.8952 |
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+ | 0.0052 | 39.0 | 14625 | 0.8298 | 0.8918 |
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+ | 0.0186 | 40.0 | 15000 | 0.8272 | 0.8935 |
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+ | 0.0182 | 41.0 | 15375 | 0.8469 | 0.8935 |
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+ | 0.0085 | 42.0 | 15750 | 0.8174 | 0.8968 |
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+ | 0.0293 | 43.0 | 16125 | 0.8181 | 0.8935 |
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+ | 0.001 | 44.0 | 16500 | 0.8046 | 0.9035 |
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+ | 0.0229 | 45.0 | 16875 | 0.8447 | 0.8935 |
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+ | 0.0261 | 46.0 | 17250 | 0.8340 | 0.8935 |
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+ | 0.0189 | 47.0 | 17625 | 0.8319 | 0.8952 |
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+ | 0.0195 | 48.0 | 18000 | 0.8342 | 0.8952 |
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+ | 0.0133 | 49.0 | 18375 | 0.8317 | 0.8935 |
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+ | 0.0026 | 50.0 | 18750 | 0.8334 | 0.8935 |
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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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