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--- |
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license: apache-2.0 |
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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: resnet-50-bottomCleanedData |
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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: train |
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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: 0.9761634506242906 |
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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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# resnet-50-bottomCleanedData |
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This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0822 |
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- Accuracy: 0.9762 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 7 |
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- total_train_batch_size: 56 |
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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: 0.01 |
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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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| 1.3323 | 1.0 | 141 | 1.3319 | 0.5187 | |
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| 1.1302 | 2.0 | 283 | 1.1059 | 0.5335 | |
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| 0.8793 | 2.99 | 424 | 0.7848 | 0.7094 | |
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| 0.7652 | 4.0 | 566 | 0.7255 | 0.7219 | |
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| 0.7708 | 4.99 | 707 | 0.5280 | 0.8173 | |
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| 0.6153 | 6.0 | 849 | 0.4221 | 0.8490 | |
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| 0.5895 | 7.0 | 991 | 0.4015 | 0.8570 | |
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| 0.5617 | 8.0 | 1132 | 0.2998 | 0.9001 | |
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| 0.517 | 9.0 | 1274 | 0.2737 | 0.9160 | |
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| 0.5366 | 9.99 | 1415 | 0.2229 | 0.9240 | |
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| 0.4645 | 11.0 | 1557 | 0.2038 | 0.9330 | |
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| 0.4114 | 11.99 | 1698 | 0.1851 | 0.9376 | |
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| 0.4528 | 13.0 | 1840 | 0.1796 | 0.9432 | |
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| 0.4182 | 14.0 | 1982 | 0.1578 | 0.9523 | |
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| 0.432 | 15.0 | 2123 | 0.1660 | 0.9421 | |
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| 0.4442 | 16.0 | 2265 | 0.1401 | 0.9557 | |
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| 0.4059 | 16.99 | 2406 | 0.1332 | 0.9591 | |
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| 0.3498 | 18.0 | 2548 | 0.1431 | 0.9535 | |
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| 0.3869 | 18.99 | 2689 | 0.1237 | 0.9512 | |
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| 0.3639 | 20.0 | 2831 | 0.1193 | 0.9603 | |
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| 0.3819 | 21.0 | 2973 | 0.1234 | 0.9557 | |
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| 0.3491 | 22.0 | 3114 | 0.1207 | 0.9569 | |
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| 0.3259 | 23.0 | 3256 | 0.1234 | 0.9591 | |
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| 0.3199 | 23.99 | 3397 | 0.1028 | 0.9659 | |
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| 0.3398 | 25.0 | 3539 | 0.1010 | 0.9603 | |
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| 0.3108 | 25.99 | 3680 | 0.1015 | 0.9671 | |
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| 0.3417 | 27.0 | 3822 | 0.1080 | 0.9614 | |
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| 0.3835 | 28.0 | 3964 | 0.1056 | 0.9591 | |
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| 0.3336 | 29.0 | 4105 | 0.1011 | 0.9637 | |
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| 0.3035 | 30.0 | 4247 | 0.0972 | 0.9614 | |
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| 0.2559 | 30.99 | 4388 | 0.0941 | 0.9659 | |
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| 0.378 | 32.0 | 4530 | 0.0963 | 0.9603 | |
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| 0.2932 | 32.99 | 4671 | 0.0916 | 0.9716 | |
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| 0.3072 | 34.0 | 4813 | 0.0917 | 0.9671 | |
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| 0.3081 | 35.0 | 4955 | 0.1025 | 0.9625 | |
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| 0.2724 | 36.0 | 5096 | 0.0874 | 0.9671 | |
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| 0.2621 | 37.0 | 5238 | 0.0847 | 0.9705 | |
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| 0.3521 | 37.99 | 5379 | 0.0829 | 0.9728 | |
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| 0.2883 | 39.0 | 5521 | 0.0860 | 0.9728 | |
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| 0.2617 | 39.99 | 5662 | 0.0898 | 0.9682 | |
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| 0.2893 | 41.0 | 5804 | 0.0877 | 0.9671 | |
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| 0.2994 | 42.0 | 5946 | 0.0822 | 0.9762 | |
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| 0.2483 | 43.0 | 6087 | 0.0834 | 0.9705 | |
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| 0.301 | 44.0 | 6229 | 0.0883 | 0.9694 | |
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| 0.2648 | 44.99 | 6370 | 0.0834 | 0.9705 | |
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| 0.2902 | 46.0 | 6512 | 0.0879 | 0.9648 | |
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| 0.299 | 46.99 | 6653 | 0.0843 | 0.9694 | |
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| 0.2726 | 48.0 | 6795 | 0.0920 | 0.9659 | |
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| 0.3252 | 49.0 | 6937 | 0.0857 | 0.9716 | |
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| 0.274 | 49.8 | 7050 | 0.0813 | 0.9762 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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