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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-LongSleeveCleanedData |
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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: 0.9787709497206704 |
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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-LongSleeveCleanedData |
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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: 0.0889 |
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- Accuracy: 0.9788 |
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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: 20 |
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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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| 0.9906 | 0.99 | 143 | 1.0394 | 0.6134 | |
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| 0.7315 | 2.0 | 287 | 0.6790 | 0.7631 | |
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| 0.559 | 3.0 | 431 | 0.4735 | 0.8547 | |
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| 0.4905 | 4.0 | 575 | 0.3148 | 0.8983 | |
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| 0.3465 | 5.0 | 719 | 0.2225 | 0.9363 | |
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| 0.3372 | 6.0 | 863 | 0.1839 | 0.9486 | |
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| 0.3349 | 7.0 | 1007 | 0.1617 | 0.9587 | |
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| 0.3159 | 7.99 | 1150 | 0.1323 | 0.9620 | |
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| 0.2805 | 9.0 | 1294 | 0.1660 | 0.9587 | |
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| 0.2657 | 10.0 | 1438 | 0.1456 | 0.9531 | |
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| 0.2929 | 11.0 | 1582 | 0.1086 | 0.9698 | |
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| 0.2763 | 12.0 | 1726 | 0.0886 | 0.9765 | |
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| 0.2475 | 13.0 | 1870 | 0.1041 | 0.9732 | |
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| 0.2148 | 14.0 | 2014 | 0.0955 | 0.9777 | |
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| 0.209 | 14.99 | 2157 | 0.1061 | 0.9709 | |
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| 0.2408 | 16.0 | 2301 | 0.0784 | 0.9743 | |
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| 0.222 | 17.0 | 2445 | 0.0839 | 0.9698 | |
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| 0.208 | 18.0 | 2589 | 0.0873 | 0.9732 | |
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| 0.2214 | 19.0 | 2733 | 0.0889 | 0.9788 | |
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| 0.2375 | 19.88 | 2860 | 0.0864 | 0.9743 | |
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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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