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--- |
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license: apache-2.0 |
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base_model: microsoft/resnet-50 |
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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-finetuned-student_kaggle |
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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: 1.0 |
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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-finetuned-student_kaggle |
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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: 0.0012 |
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- Accuracy: 1.0 |
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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: 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: 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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| 0.7142 | 1.0 | 47 | 0.6418 | 0.6101 | |
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| 0.3351 | 2.0 | 94 | 0.2597 | 0.8947 | |
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| 0.2574 | 3.0 | 141 | 0.1046 | 0.9780 | |
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| 0.1479 | 4.0 | 188 | 0.0616 | 0.9874 | |
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| 0.1284 | 5.0 | 235 | 0.0232 | 0.9953 | |
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| 0.077 | 6.0 | 282 | 0.0150 | 0.9953 | |
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| 0.103 | 7.0 | 329 | 0.0105 | 0.9984 | |
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| 0.0922 | 8.0 | 376 | 0.0094 | 0.9984 | |
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| 0.08 | 9.0 | 423 | 0.0056 | 1.0 | |
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| 0.0492 | 10.0 | 470 | 0.0045 | 1.0 | |
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| 0.0574 | 11.0 | 517 | 0.0043 | 1.0 | |
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| 0.0382 | 12.0 | 564 | 0.0023 | 1.0 | |
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| 0.0666 | 13.0 | 611 | 0.0022 | 1.0 | |
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| 0.0477 | 14.0 | 658 | 0.0022 | 1.0 | |
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| 0.0614 | 15.0 | 705 | 0.0023 | 1.0 | |
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| 0.0282 | 16.0 | 752 | 0.0014 | 1.0 | |
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| 0.0659 | 17.0 | 799 | 0.0016 | 1.0 | |
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| 0.0586 | 18.0 | 846 | 0.0010 | 1.0 | |
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| 0.0557 | 19.0 | 893 | 0.0013 | 1.0 | |
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| 0.07 | 20.0 | 940 | 0.0012 | 1.0 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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