metadata
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
datasets:
- fair_face
metrics:
- accuracy
model-index:
- name: trained-race
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: 0.625798794960745
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