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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: cifar100-vit-base-patch16-224-in21k
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# cifar100-vit-base-patch16-224-in21k
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the cifar100 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2945
- Accuracy: 0.926
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3866 | 1.0 | 5313 | 1.0968 | 0.8747 |
| 0.6479 | 2.0 | 10626 | 0.4377 | 0.9004 |
| 0.6092 | 3.0 | 15939 | 0.3439 | 0.9081 |
| 0.4173 | 4.0 | 21252 | 0.3205 | 0.9169 |
| 0.4665 | 5.0 | 26565 | 0.3039 | 0.9175 |
| 0.3944 | 6.0 | 31878 | 0.3082 | 0.9201 |
| 0.303 | 7.0 | 37191 | 0.3011 | 0.9241 |
| 0.6128 | 8.0 | 42504 | 0.2983 | 0.9261 |
| 0.3794 | 9.0 | 47817 | 0.2945 | 0.926 |
| 0.3274 | 10.0 | 53130 | 0.3032 | 0.9269 |
### Framework versions
- Transformers 4.38.0
- Pytorch 2.1.2+cu118
- Datasets 2.19.1
- Tokenizers 0.15.2
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