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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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- fair_face |
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metrics: |
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- accuracy |
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model-index: |
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- name: trained-gender |
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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: fair_face |
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type: fair_face |
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config: '0.25' |
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split: validation |
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args: '0.25' |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8985758626985576 |
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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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# trained-gender |
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This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the fair_face dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2437 |
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- Accuracy: 0.8986 |
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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: 16 |
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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: 4 |
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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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| 0.4277 | 0.18 | 1000 | 0.4054 | 0.8089 | |
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| 0.315 | 0.37 | 2000 | 0.3487 | 0.8318 | |
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| 0.3082 | 0.55 | 3000 | 0.3052 | 0.8633 | |
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| 0.3235 | 0.74 | 4000 | 0.2899 | 0.8684 | |
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| 0.2505 | 0.92 | 5000 | 0.2693 | 0.8785 | |
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| 0.2484 | 1.11 | 6000 | 0.2547 | 0.8889 | |
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| 0.1933 | 1.29 | 7000 | 0.2521 | 0.8901 | |
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| 0.1497 | 1.48 | 8000 | 0.2443 | 0.8929 | |
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| 0.326 | 1.66 | 9000 | 0.2406 | 0.8958 | |
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| 0.215 | 1.84 | 10000 | 0.2381 | 0.9007 | |
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| 0.2035 | 2.03 | 11000 | 0.2437 | 0.8986 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.0 |
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