| --- |
| license: apache-2.0 |
| base_model: microsoft/resnet-50 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - fair_face |
| metrics: |
| - accuracy |
| model-index: |
| - name: trained-gender |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: fair_face |
| type: fair_face |
| config: '0.25' |
| split: validation |
| args: '0.25' |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.8985758626985576 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # trained-gender |
|
|
| This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the fair_face dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2437 |
| - Accuracy: 0.8986 |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| More information needed |
| |
| ## Training and evaluation data |
| |
| More information needed |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 0.0002 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 4 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 0.4277 | 0.18 | 1000 | 0.4054 | 0.8089 | |
| | 0.315 | 0.37 | 2000 | 0.3487 | 0.8318 | |
| | 0.3082 | 0.55 | 3000 | 0.3052 | 0.8633 | |
| | 0.3235 | 0.74 | 4000 | 0.2899 | 0.8684 | |
| | 0.2505 | 0.92 | 5000 | 0.2693 | 0.8785 | |
| | 0.2484 | 1.11 | 6000 | 0.2547 | 0.8889 | |
| | 0.1933 | 1.29 | 7000 | 0.2521 | 0.8901 | |
| | 0.1497 | 1.48 | 8000 | 0.2443 | 0.8929 | |
| | 0.326 | 1.66 | 9000 | 0.2406 | 0.8958 | |
| | 0.215 | 1.84 | 10000 | 0.2381 | 0.9007 | |
| | 0.2035 | 2.03 | 11000 | 0.2437 | 0.8986 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.34.0 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.5 |
| - Tokenizers 0.14.0 |
| |
