metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: imagenet2012-1k-subsampling-50-vit-base-patch16-224-in21k
results: []
imagenet2012-1k-subsampling-50-vit-base-patch16-224-in21k
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagenet2012-1k-subsampling-50 dataset. It achieves the following results on the evaluation set:
- Loss: 0.8563
- Accuracy: 0.8109
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: 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: 10.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 5.7852 | 1.0 | 5313 | 5.7565 | 0.6867 |
| 4.4299 | 2.0 | 10626 | 4.2553 | 0.7315 |
| 2.7934 | 3.0 | 15939 | 2.7094 | 0.7547 |
| 1.5784 | 4.0 | 21252 | 1.6554 | 0.7728 |
| 0.7426 | 5.0 | 26565 | 1.1836 | 0.7896 |
| 0.8495 | 6.0 | 31878 | 0.9912 | 0.8013 |
| 0.575 | 7.0 | 37191 | 0.9112 | 0.8041 |
| 0.7981 | 8.0 | 42504 | 0.8853 | 0.8052 |
| 0.7448 | 9.0 | 47817 | 0.8613 | 0.8113 |
| 0.3953 | 10.0 | 53130 | 0.8563 | 0.8109 |
Framework versions
- Transformers 4.38.0
- Pytorch 2.1.2+cu118
- Datasets 2.19.1
- Tokenizers 0.15.2