metadata
base_model: nateraw/vit-age-classifier
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: image_classification
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: 0.34375
image_classification
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: 1.8469
- Accuracy: 0.3438
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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.8 | 1 | 1.8452 | 0.3125 |
| No log | 1.6 | 2 | 1.8435 | 0.35 |
| No log | 2.4 | 3 | 1.8282 | 0.3688 |
| No log | 4.0 | 5 | 1.8112 | 0.3563 |
| No log | 4.8 | 6 | 1.8180 | 0.3312 |
| No log | 5.6 | 7 | 1.8291 | 0.3375 |
| No log | 6.4 | 8 | 1.8036 | 0.3563 |
| 1.6711 | 8.0 | 10 | 1.8134 | 0.3375 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1