trained-age
This model is a fine-tuned version of microsoft/resnet-50 on the fair_face dataset. It achieves the following results on the evaluation set:
- Loss: 1.1340
- Accuracy: 0.5164
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 |
---|---|---|---|---|
1.3347 | 0.18 | 1000 | 1.3819 | 0.4296 |
1.3071 | 0.37 | 2000 | 1.2799 | 0.4642 |
1.297 | 0.55 | 3000 | 1.2503 | 0.4721 |
1.3121 | 0.74 | 4000 | 1.1661 | 0.4995 |
1.1806 | 0.92 | 5000 | 1.1137 | 0.5240 |
1.0839 | 1.11 | 6000 | 1.1340 | 0.5164 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
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Model tree for crangana/trained-age
Base model
microsoft/resnet-50Evaluation results
- Accuracy on fair_facevalidation set self-reported0.516