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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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- cifar10_quality_drift |
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metrics: |
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- accuracy |
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- f1 |
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base_model: microsoft/resnet-50 |
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model-index: |
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- name: resnet-50-cifar10-quality-drift |
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results: |
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- task: |
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type: image-classification |
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name: Image Classification |
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dataset: |
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name: cifar10_quality_drift |
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type: cifar10_quality_drift |
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args: default |
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metrics: |
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- type: accuracy |
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value: 0.724 |
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name: Accuracy |
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- type: f1 |
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value: 0.7221970011456912 |
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name: F1 |
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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-cifar10-quality-drift |
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This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the cifar10_quality_drift dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8235 |
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- Accuracy: 0.724 |
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- F1: 0.7222 |
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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: 0.0002 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 1.7311 | 1.0 | 750 | 1.1310 | 0.6333 | 0.6300 | |
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| 1.1728 | 2.0 | 1500 | 0.8495 | 0.7153 | 0.7155 | |
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| 1.0322 | 3.0 | 2250 | 0.8235 | 0.724 | 0.7222 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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