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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_001_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: 0.6976744186046512 |
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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_001_fold3 |
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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: 2.7065 |
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- Accuracy: 0.6977 |
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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: 0.001 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.4764 | 1.0 | 28 | 1.3308 | 0.4651 | |
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| 1.3399 | 2.0 | 56 | 1.2727 | 0.5116 | |
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| 1.2309 | 3.0 | 84 | 1.0539 | 0.5349 | |
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| 1.0517 | 4.0 | 112 | 1.0384 | 0.6279 | |
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| 0.9736 | 5.0 | 140 | 1.1313 | 0.5349 | |
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| 1.0108 | 6.0 | 168 | 0.6569 | 0.8140 | |
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| 0.9287 | 7.0 | 196 | 0.7779 | 0.7674 | |
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| 0.9063 | 8.0 | 224 | 0.8802 | 0.5581 | |
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| 0.7994 | 9.0 | 252 | 1.1244 | 0.5581 | |
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| 0.8319 | 10.0 | 280 | 0.7284 | 0.7209 | |
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| 0.8096 | 11.0 | 308 | 0.7775 | 0.7209 | |
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| 0.8274 | 12.0 | 336 | 0.7683 | 0.6744 | |
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| 0.798 | 13.0 | 364 | 0.8219 | 0.6512 | |
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| 0.6756 | 14.0 | 392 | 0.5656 | 0.7442 | |
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| 0.9098 | 15.0 | 420 | 0.6922 | 0.6279 | |
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| 0.6261 | 16.0 | 448 | 1.0949 | 0.5814 | |
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| 0.6243 | 17.0 | 476 | 0.7154 | 0.7209 | |
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| 0.7247 | 18.0 | 504 | 0.6429 | 0.7674 | |
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| 0.6106 | 19.0 | 532 | 0.7927 | 0.6744 | |
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| 0.4831 | 20.0 | 560 | 0.6060 | 0.7674 | |
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| 0.5359 | 21.0 | 588 | 1.2593 | 0.5349 | |
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| 0.429 | 22.0 | 616 | 1.0232 | 0.6744 | |
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| 0.4536 | 23.0 | 644 | 1.2564 | 0.6744 | |
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| 0.2969 | 24.0 | 672 | 1.2153 | 0.6279 | |
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| 0.3018 | 25.0 | 700 | 1.3650 | 0.5814 | |
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| 0.2695 | 26.0 | 728 | 1.6759 | 0.6279 | |
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| 0.2235 | 27.0 | 756 | 1.8158 | 0.5814 | |
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| 0.2674 | 28.0 | 784 | 1.7475 | 0.6977 | |
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| 0.1711 | 29.0 | 812 | 1.5630 | 0.7209 | |
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| 0.1241 | 30.0 | 840 | 1.5976 | 0.7442 | |
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| 0.1378 | 31.0 | 868 | 1.8498 | 0.7209 | |
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| 0.1016 | 32.0 | 896 | 2.3022 | 0.6279 | |
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| 0.1245 | 33.0 | 924 | 2.0178 | 0.6047 | |
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| 0.1029 | 34.0 | 952 | 2.0725 | 0.6744 | |
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| 0.0329 | 35.0 | 980 | 1.6046 | 0.7674 | |
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| 0.1038 | 36.0 | 1008 | 2.3364 | 0.6047 | |
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| 0.055 | 37.0 | 1036 | 3.1044 | 0.5581 | |
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| 0.0031 | 38.0 | 1064 | 2.6896 | 0.6512 | |
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| 0.0537 | 39.0 | 1092 | 3.2350 | 0.6047 | |
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| 0.0484 | 40.0 | 1120 | 3.5002 | 0.5814 | |
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| 0.0311 | 41.0 | 1148 | 3.0948 | 0.6512 | |
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| 0.0491 | 42.0 | 1176 | 2.8268 | 0.6977 | |
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| 0.0023 | 43.0 | 1204 | 2.5306 | 0.6977 | |
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| 0.0192 | 44.0 | 1232 | 2.3977 | 0.6977 | |
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| 0.0339 | 45.0 | 1260 | 2.5488 | 0.6977 | |
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| 0.0369 | 46.0 | 1288 | 2.5878 | 0.7209 | |
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| 0.049 | 47.0 | 1316 | 2.7159 | 0.6977 | |
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| 0.0044 | 48.0 | 1344 | 2.7074 | 0.6977 | |
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| 0.0183 | 49.0 | 1372 | 2.7065 | 0.6977 | |
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| 0.0409 | 50.0 | 1400 | 2.7065 | 0.6977 | |
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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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