metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
model-index:
- name: vit-base-nationality
results: []
vit-base-nationality
This model is a fine-tuned version of google/vit-base-patch16-224 on the pcuenq/oxford-pets dataset. It achieves the following results on the evaluation set:
- Loss: 1.2289
- Precision: 0.5992
- Recall: 0.6005
- Accuracy: 0.6005
- F1: 0.5861
- Score: 0.6005
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: 0.001
- train_batch_size: 64
- eval_batch_size: 8
- 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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 | Score |
|---|---|---|---|---|---|---|---|---|
| 1.2527 | 1.0 | 105 | 1.2744 | 0.5925 | 0.5820 | 0.5820 | 0.5631 | 0.5820 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3