metadata
base_model: nateraw/vit-age-classifier
datasets:
- imagefolder
library_name: transformers
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: results
results:
- task:
type: image-classification
name: Image Classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- type: accuracy
value: 0.44375
name: Accuracy
results
This model is a fine-tuned version of nateraw/vit-age-classifier on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.6666
- Accuracy: 0.4437
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.968 | 1.0 | 40 | 1.9059 | 0.3063 |
| 1.5965 | 2.0 | 80 | 1.7152 | 0.3937 |
| 1.4239 | 3.0 | 120 | 1.6666 | 0.4437 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1