metadata
library_name: transformers
base_model: nateraw/vit-age-classifier
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: results
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.55
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:
- Accuracy: 0.55
- Loss: 1.6263
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 2.1123 | 1.0 | 50 | 0.2412 | 2.0343 |
| 1.8449 | 2.0 | 100 | 0.4113 | 1.7485 |
| 1.7374 | 3.0 | 150 | 0.55 | 1.6263 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3