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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: hushem_5x_beit_base_adamax_0001_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: 0.8666666666666667 |
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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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# hushem_5x_beit_base_adamax_0001_fold2 |
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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: 1.1073 |
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- Accuracy: 0.8667 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.56 | 1.0 | 27 | 0.5803 | 0.8444 | |
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| 0.1296 | 2.0 | 54 | 0.5439 | 0.8444 | |
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| 0.0323 | 3.0 | 81 | 1.1689 | 0.7556 | |
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| 0.051 | 4.0 | 108 | 0.6969 | 0.8444 | |
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| 0.0058 | 5.0 | 135 | 0.7561 | 0.8444 | |
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| 0.0281 | 6.0 | 162 | 0.6767 | 0.8444 | |
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| 0.0031 | 7.0 | 189 | 0.9959 | 0.8 | |
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| 0.006 | 8.0 | 216 | 1.0852 | 0.8222 | |
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| 0.0042 | 9.0 | 243 | 0.9557 | 0.8667 | |
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| 0.0002 | 10.0 | 270 | 0.9792 | 0.8444 | |
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| 0.0001 | 11.0 | 297 | 1.0071 | 0.8667 | |
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| 0.0001 | 12.0 | 324 | 1.1614 | 0.8 | |
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| 0.0001 | 13.0 | 351 | 1.0429 | 0.8667 | |
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| 0.0001 | 14.0 | 378 | 1.0442 | 0.8667 | |
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| 0.0001 | 15.0 | 405 | 1.1430 | 0.8222 | |
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| 0.0001 | 16.0 | 432 | 1.1457 | 0.8222 | |
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| 0.0027 | 17.0 | 459 | 1.3728 | 0.8222 | |
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| 0.0001 | 18.0 | 486 | 1.0448 | 0.8667 | |
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| 0.0001 | 19.0 | 513 | 1.0357 | 0.8667 | |
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| 0.0 | 20.0 | 540 | 1.2604 | 0.8 | |
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| 0.0026 | 21.0 | 567 | 1.0654 | 0.8667 | |
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| 0.0004 | 22.0 | 594 | 1.1414 | 0.8444 | |
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| 0.0001 | 23.0 | 621 | 1.1523 | 0.8444 | |
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| 0.0001 | 24.0 | 648 | 1.1307 | 0.8444 | |
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| 0.0002 | 25.0 | 675 | 1.1816 | 0.8444 | |
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| 0.0 | 26.0 | 702 | 1.1278 | 0.8444 | |
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| 0.0 | 27.0 | 729 | 1.0224 | 0.8667 | |
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| 0.0001 | 28.0 | 756 | 1.4430 | 0.7333 | |
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| 0.0001 | 29.0 | 783 | 1.3228 | 0.7556 | |
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| 0.0 | 30.0 | 810 | 1.2875 | 0.8 | |
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| 0.0001 | 31.0 | 837 | 1.2284 | 0.8222 | |
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| 0.0003 | 32.0 | 864 | 1.3104 | 0.8444 | |
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| 0.0001 | 33.0 | 891 | 1.1798 | 0.8667 | |
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| 0.0001 | 34.0 | 918 | 1.1586 | 0.8667 | |
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| 0.0001 | 35.0 | 945 | 1.1617 | 0.8667 | |
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| 0.0 | 36.0 | 972 | 1.1634 | 0.8667 | |
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| 0.0 | 37.0 | 999 | 1.1712 | 0.8667 | |
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| 0.0 | 38.0 | 1026 | 1.1767 | 0.8667 | |
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| 0.0 | 39.0 | 1053 | 1.1666 | 0.8667 | |
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| 0.0 | 40.0 | 1080 | 1.1693 | 0.8667 | |
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| 0.0 | 41.0 | 1107 | 1.1706 | 0.8667 | |
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| 0.0 | 42.0 | 1134 | 1.0988 | 0.8667 | |
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| 0.001 | 43.0 | 1161 | 1.0945 | 0.8667 | |
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| 0.0 | 44.0 | 1188 | 1.0895 | 0.8667 | |
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| 0.0 | 45.0 | 1215 | 1.0977 | 0.8667 | |
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| 0.0004 | 46.0 | 1242 | 1.0978 | 0.8667 | |
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| 0.0 | 47.0 | 1269 | 1.1013 | 0.8667 | |
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| 0.0001 | 48.0 | 1296 | 1.1072 | 0.8667 | |
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| 0.0001 | 49.0 | 1323 | 1.1073 | 0.8667 | |
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| 0.0 | 50.0 | 1350 | 1.1073 | 0.8667 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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