metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-cifar100-cifar100
results: []
vit-cifar100-cifar100
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the cifar100 dataset. It achieves the following results on the evaluation set:
- Loss: 3.1612
- Accuracy: 0.2223
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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 3.7207 | 1.0 | 5313 | 3.8632 | 0.0985 |
| 3.5093 | 2.0 | 10626 | 3.5664 | 0.1472 |
| 3.3675 | 3.0 | 15939 | 3.4389 | 0.166 |
| 2.9505 | 4.0 | 21252 | 3.2326 | 0.2093 |
| 3.1158 | 5.0 | 26565 | 3.1612 | 0.2223 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.0.1+cu117
- Datasets 3.0.0
- Tokenizers 0.19.1