metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: FaceDataset
results: []
FaceDataset
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0251
- Accuracy: 0.9909
- Precision: 0.9909
- Recall: 0.9909
- F1: 0.9909
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.1021 | 1.0 | 243 | 0.0957 | 0.9781 | 0.9790 | 0.9781 | 0.9780 |
| 0.0457 | 2.0 | 486 | 0.0271 | 0.9909 | 0.9910 | 0.9909 | 0.9909 |
| 0.0191 | 3.0 | 729 | 0.0414 | 0.9872 | 0.9872 | 0.9872 | 0.9872 |
| 0.0082 | 4.0 | 972 | 0.0251 | 0.9909 | 0.9909 | 0.9909 | 0.9909 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2