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--- |
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license: apache-2.0 |
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base_model: microsoft/beit-large-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_10x_beit_large_sgd_0001_fold1 |
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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: 0.8714524207011686 |
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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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# smids_10x_beit_large_sgd_0001_fold1 |
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This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3289 |
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- Accuracy: 0.8715 |
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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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| 0.9122 | 1.0 | 751 | 1.0277 | 0.4591 | |
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| 0.7509 | 2.0 | 1502 | 0.8635 | 0.6194 | |
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| 0.6317 | 3.0 | 2253 | 0.7448 | 0.7012 | |
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| 0.5452 | 4.0 | 3004 | 0.6612 | 0.7446 | |
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| 0.5954 | 5.0 | 3755 | 0.5972 | 0.7830 | |
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| 0.5075 | 6.0 | 4506 | 0.5495 | 0.7930 | |
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| 0.5045 | 7.0 | 5257 | 0.5158 | 0.8130 | |
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| 0.4666 | 8.0 | 6008 | 0.4891 | 0.8147 | |
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| 0.4159 | 9.0 | 6759 | 0.4686 | 0.8247 | |
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| 0.4231 | 10.0 | 7510 | 0.4504 | 0.8280 | |
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| 0.4497 | 11.0 | 8261 | 0.4359 | 0.8364 | |
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| 0.3539 | 12.0 | 9012 | 0.4229 | 0.8381 | |
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| 0.3554 | 13.0 | 9763 | 0.4122 | 0.8414 | |
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| 0.3441 | 14.0 | 10514 | 0.4038 | 0.8414 | |
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| 0.3331 | 15.0 | 11265 | 0.3962 | 0.8431 | |
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| 0.3376 | 16.0 | 12016 | 0.3885 | 0.8431 | |
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| 0.374 | 17.0 | 12767 | 0.3827 | 0.8431 | |
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| 0.3157 | 18.0 | 13518 | 0.3768 | 0.8464 | |
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| 0.3563 | 19.0 | 14269 | 0.3725 | 0.8514 | |
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| 0.3183 | 20.0 | 15020 | 0.3682 | 0.8548 | |
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| 0.2569 | 21.0 | 15771 | 0.3646 | 0.8598 | |
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| 0.312 | 22.0 | 16522 | 0.3608 | 0.8581 | |
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| 0.3262 | 23.0 | 17273 | 0.3576 | 0.8598 | |
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| 0.3722 | 24.0 | 18024 | 0.3550 | 0.8598 | |
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| 0.3339 | 25.0 | 18775 | 0.3524 | 0.8598 | |
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| 0.3725 | 26.0 | 19526 | 0.3497 | 0.8631 | |
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| 0.35 | 27.0 | 20277 | 0.3474 | 0.8664 | |
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| 0.3858 | 28.0 | 21028 | 0.3456 | 0.8648 | |
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| 0.3212 | 29.0 | 21779 | 0.3439 | 0.8664 | |
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| 0.3222 | 30.0 | 22530 | 0.3422 | 0.8681 | |
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| 0.2584 | 31.0 | 23281 | 0.3410 | 0.8664 | |
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| 0.3877 | 32.0 | 24032 | 0.3393 | 0.8698 | |
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| 0.3116 | 33.0 | 24783 | 0.3380 | 0.8698 | |
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| 0.3141 | 34.0 | 25534 | 0.3366 | 0.8715 | |
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| 0.3279 | 35.0 | 26285 | 0.3358 | 0.8681 | |
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| 0.2798 | 36.0 | 27036 | 0.3348 | 0.8715 | |
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| 0.3928 | 37.0 | 27787 | 0.3341 | 0.8715 | |
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| 0.3 | 38.0 | 28538 | 0.3331 | 0.8715 | |
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| 0.2471 | 39.0 | 29289 | 0.3324 | 0.8715 | |
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| 0.3456 | 40.0 | 30040 | 0.3317 | 0.8715 | |
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| 0.3078 | 41.0 | 30791 | 0.3311 | 0.8715 | |
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| 0.24 | 42.0 | 31542 | 0.3306 | 0.8715 | |
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| 0.289 | 43.0 | 32293 | 0.3302 | 0.8715 | |
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| 0.2977 | 44.0 | 33044 | 0.3297 | 0.8715 | |
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| 0.2559 | 45.0 | 33795 | 0.3294 | 0.8715 | |
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| 0.3508 | 46.0 | 34546 | 0.3292 | 0.8715 | |
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| 0.26 | 47.0 | 35297 | 0.3291 | 0.8715 | |
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| 0.3325 | 48.0 | 36048 | 0.3290 | 0.8715 | |
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| 0.2898 | 49.0 | 36799 | 0.3289 | 0.8715 | |
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| 0.2912 | 50.0 | 37550 | 0.3289 | 0.8715 | |
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### Framework versions |
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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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