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---
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-base-beans
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. -->
# vit-base-beans
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 beans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0634
- Accuracy: 0.9925
## 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: 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: 5.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2819 | 1.0 | 130 | 0.2152 | 0.9624 |
| 0.1301 | 2.0 | 260 | 0.1301 | 0.9699 |
| 0.138 | 3.0 | 390 | 0.0965 | 0.9774 |
| 0.087 | 4.0 | 520 | 0.0634 | 0.9925 |
| 0.1113 | 5.0 | 650 | 0.0788 | 0.9850 |
### Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.6.0+xpu
- Datasets 3.2.0
- Tokenizers 0.21.0
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