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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_rms_00001_fold5 |
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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: 0.8048780487804879 |
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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_rms_00001_fold5 |
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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: 1.1845 |
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- Accuracy: 0.8049 |
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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: 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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.9367 | 1.0 | 28 | 0.6533 | 0.7073 | |
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| 0.1926 | 2.0 | 56 | 0.5512 | 0.7805 | |
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| 0.047 | 3.0 | 84 | 0.6007 | 0.8049 | |
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| 0.0193 | 4.0 | 112 | 0.2590 | 0.9024 | |
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| 0.0089 | 5.0 | 140 | 0.4654 | 0.8293 | |
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| 0.0038 | 6.0 | 168 | 0.5932 | 0.8293 | |
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| 0.0017 | 7.0 | 196 | 0.6877 | 0.8293 | |
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| 0.0014 | 8.0 | 224 | 0.7982 | 0.8049 | |
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| 0.0007 | 9.0 | 252 | 0.6044 | 0.8293 | |
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| 0.0007 | 10.0 | 280 | 0.6788 | 0.8537 | |
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| 0.0003 | 11.0 | 308 | 0.6662 | 0.8537 | |
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| 0.0003 | 12.0 | 336 | 0.6588 | 0.8537 | |
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| 0.0002 | 13.0 | 364 | 0.6343 | 0.8293 | |
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| 0.0046 | 14.0 | 392 | 1.0649 | 0.7805 | |
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| 0.0012 | 15.0 | 420 | 0.7359 | 0.8293 | |
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| 0.0005 | 16.0 | 448 | 0.7345 | 0.8293 | |
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| 0.0066 | 17.0 | 476 | 0.7816 | 0.8537 | |
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| 0.0014 | 18.0 | 504 | 0.6553 | 0.8780 | |
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| 0.0003 | 19.0 | 532 | 0.5879 | 0.8780 | |
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| 0.0001 | 20.0 | 560 | 0.6539 | 0.8537 | |
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| 0.0001 | 21.0 | 588 | 0.5762 | 0.8293 | |
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| 0.0006 | 22.0 | 616 | 0.3307 | 0.8293 | |
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| 0.0001 | 23.0 | 644 | 0.6447 | 0.8293 | |
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| 0.0002 | 24.0 | 672 | 0.7471 | 0.8537 | |
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| 0.0002 | 25.0 | 700 | 0.6200 | 0.8537 | |
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| 0.0001 | 26.0 | 728 | 0.9057 | 0.8537 | |
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| 0.0001 | 27.0 | 756 | 0.8578 | 0.8537 | |
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| 0.0004 | 28.0 | 784 | 0.7354 | 0.8537 | |
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| 0.0001 | 29.0 | 812 | 0.8285 | 0.8537 | |
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| 0.0004 | 30.0 | 840 | 0.7442 | 0.8780 | |
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| 0.0001 | 31.0 | 868 | 0.9315 | 0.8049 | |
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| 0.0002 | 32.0 | 896 | 1.0255 | 0.8049 | |
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| 0.0 | 33.0 | 924 | 1.0401 | 0.7805 | |
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| 0.0001 | 34.0 | 952 | 1.0520 | 0.8293 | |
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| 0.0004 | 35.0 | 980 | 0.9869 | 0.8537 | |
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| 0.0 | 36.0 | 1008 | 0.9764 | 0.8537 | |
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| 0.0001 | 37.0 | 1036 | 0.9356 | 0.8537 | |
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| 0.0001 | 38.0 | 1064 | 1.1522 | 0.8049 | |
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| 0.0 | 39.0 | 1092 | 1.0978 | 0.8049 | |
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| 0.0005 | 40.0 | 1120 | 1.0647 | 0.8293 | |
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| 0.0003 | 41.0 | 1148 | 1.2331 | 0.8049 | |
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| 0.0 | 42.0 | 1176 | 1.3110 | 0.8049 | |
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| 0.0 | 43.0 | 1204 | 1.2050 | 0.8049 | |
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| 0.0 | 44.0 | 1232 | 1.1647 | 0.8049 | |
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| 0.0002 | 45.0 | 1260 | 1.2154 | 0.8049 | |
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| 0.0001 | 46.0 | 1288 | 1.2000 | 0.8049 | |
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| 0.0001 | 47.0 | 1316 | 1.1915 | 0.8049 | |
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| 0.0 | 48.0 | 1344 | 1.1844 | 0.8049 | |
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| 0.0001 | 49.0 | 1372 | 1.1845 | 0.8049 | |
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| 0.0 | 50.0 | 1400 | 1.1845 | 0.8049 | |
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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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