metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: face_age_detection_base_v3_weighted
results: []
face_age_detection_base_v3_weighted
This model is a fine-tuned version of google/vit-base-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0928
- Accuracy: 0.9691
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1216 | 0.9968 | 157 | 0.1257 | 0.9567 |
| 0.1109 | 1.9952 | 314 | 0.1100 | 0.9637 |
| 0.0947 | 2.9937 | 471 | 0.1097 | 0.9640 |
| 0.0745 | 3.9984 | 629 | 0.0928 | 0.9679 |
| 0.0565 | 4.9968 | 786 | 0.0941 | 0.9668 |
| 0.0716 | 5.9889 | 942 | 0.0928 | 0.9691 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3