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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_001_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: 0.34146341463414637 |
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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_001_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: 2.4962 |
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- Accuracy: 0.3415 |
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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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| 1.501 | 1.0 | 28 | 1.3919 | 0.2439 | |
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| 1.3993 | 2.0 | 56 | 1.4008 | 0.2683 | |
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| 1.4258 | 3.0 | 84 | 1.4098 | 0.2439 | |
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| 1.4011 | 4.0 | 112 | 1.3674 | 0.2683 | |
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| 1.4153 | 5.0 | 140 | 1.3306 | 0.2683 | |
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| 1.3649 | 6.0 | 168 | 1.4784 | 0.2195 | |
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| 1.3525 | 7.0 | 196 | 1.2906 | 0.4390 | |
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| 1.3374 | 8.0 | 224 | 1.1798 | 0.5122 | |
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| 1.2661 | 9.0 | 252 | 1.3479 | 0.5122 | |
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| 1.3011 | 10.0 | 280 | 1.3054 | 0.4878 | |
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| 1.2212 | 11.0 | 308 | 1.1612 | 0.5122 | |
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| 1.2579 | 12.0 | 336 | 1.2572 | 0.2683 | |
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| 1.2438 | 13.0 | 364 | 1.1160 | 0.4634 | |
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| 1.2218 | 14.0 | 392 | 1.1291 | 0.4878 | |
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| 1.2455 | 15.0 | 420 | 1.4587 | 0.4390 | |
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| 1.2528 | 16.0 | 448 | 1.3009 | 0.5122 | |
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| 1.2445 | 17.0 | 476 | 1.1915 | 0.5122 | |
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| 1.1729 | 18.0 | 504 | 1.3461 | 0.4390 | |
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| 1.2917 | 19.0 | 532 | 1.3956 | 0.3659 | |
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| 1.2335 | 20.0 | 560 | 1.1161 | 0.4146 | |
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| 1.1787 | 21.0 | 588 | 1.4220 | 0.4390 | |
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| 1.1076 | 22.0 | 616 | 1.2157 | 0.5122 | |
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| 1.1837 | 23.0 | 644 | 1.2878 | 0.4634 | |
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| 1.065 | 24.0 | 672 | 1.3373 | 0.3659 | |
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| 1.0753 | 25.0 | 700 | 1.2968 | 0.4634 | |
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| 1.0288 | 26.0 | 728 | 1.2996 | 0.4146 | |
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| 1.0679 | 27.0 | 756 | 1.2975 | 0.3902 | |
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| 1.0591 | 28.0 | 784 | 1.3051 | 0.4634 | |
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| 1.0148 | 29.0 | 812 | 1.2575 | 0.5854 | |
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| 1.0668 | 30.0 | 840 | 1.3174 | 0.3415 | |
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| 0.9767 | 31.0 | 868 | 1.3259 | 0.4390 | |
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| 0.9254 | 32.0 | 896 | 1.3236 | 0.4878 | |
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| 0.9064 | 33.0 | 924 | 1.5265 | 0.3902 | |
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| 0.9504 | 34.0 | 952 | 1.2456 | 0.4390 | |
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| 0.8534 | 35.0 | 980 | 1.2811 | 0.5122 | |
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| 0.8361 | 36.0 | 1008 | 1.2101 | 0.6098 | |
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| 0.7846 | 37.0 | 1036 | 1.3727 | 0.4390 | |
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| 0.7661 | 38.0 | 1064 | 1.4030 | 0.4878 | |
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| 0.8237 | 39.0 | 1092 | 1.3385 | 0.4634 | |
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| 0.7652 | 40.0 | 1120 | 1.6174 | 0.4146 | |
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| 0.6764 | 41.0 | 1148 | 1.6358 | 0.4390 | |
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| 0.5675 | 42.0 | 1176 | 1.7675 | 0.4390 | |
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| 0.5777 | 43.0 | 1204 | 1.8573 | 0.4390 | |
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| 0.5704 | 44.0 | 1232 | 2.0252 | 0.3902 | |
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| 0.5677 | 45.0 | 1260 | 2.0725 | 0.3902 | |
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| 0.4676 | 46.0 | 1288 | 2.4159 | 0.3171 | |
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| 0.4167 | 47.0 | 1316 | 2.4083 | 0.3415 | |
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| 0.416 | 48.0 | 1344 | 2.4826 | 0.3415 | |
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| 0.3715 | 49.0 | 1372 | 2.4962 | 0.3415 | |
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| 0.368 | 50.0 | 1400 | 2.4962 | 0.3415 | |
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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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