metadata

license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - generated_from_trainer
datasets:
  - fair_face
metrics:
  - accuracy
model-index:
  - name: vit-base-age-classification
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: fair_face
          type: fair_face
          config: '0.25'
          split: train
          args: '0.25'
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7656465622209595

vit-base-age-classification

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the fair_face dataset. It achieves the following results on the evaluation set:

Loss: 0.6669
Accuracy: 0.7656

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: 32
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.1069	1.0	385	0.9425	0.6209
0.8465	2.0	770	0.6669	0.7656

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1