metadata
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
datasets:
- fair_face
metrics:
- accuracy
model-index:
- name: trained-age
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: 0.5164323534781815
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