trained-race
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: 0.9830
- Accuracy: 0.6258
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 |
---|---|---|---|---|
1.3923 | 0.18 | 1000 | 1.3550 | 0.4712 |
1.1517 | 0.37 | 2000 | 1.1854 | 0.5429 |
1.2405 | 0.55 | 3000 | 1.1001 | 0.5754 |
1.0752 | 0.74 | 4000 | 1.0330 | 0.6018 |
1.0986 | 0.92 | 5000 | 0.9973 | 0.6173 |
1.0007 | 1.11 | 6000 | 0.9735 | 0.6279 |
0.9851 | 1.29 | 7000 | 0.9830 | 0.6258 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
- Downloads last month
- 235
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for crangana/trained-race
Base model
microsoft/resnet-50Space using crangana/trained-race 1
Evaluation results
- Accuracy on fair_facevalidation set self-reported0.626