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license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- vision
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-beans_50
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.943939393939394
---
<!-- 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_50
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 imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1514
- Accuracy: 0.9439
## 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: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 468 | 0.1514 | 0.9439 |
| 0.2863 | 2.0 | 936 | 0.1917 | 0.9303 |
| 0.2377 | 3.0 | 1404 | 0.1725 | 0.9333 |
| 0.2142 | 4.0 | 1872 | 0.1782 | 0.9288 |
| 0.2058 | 5.0 | 2340 | 0.1788 | 0.9273 |
| 0.1899 | 6.0 | 2808 | 0.1824 | 0.9318 |
| 0.1838 | 7.0 | 3276 | 0.1879 | 0.9333 |
| 0.1757 | 8.0 | 3744 | 0.2391 | 0.9333 |
| 0.1852 | 9.0 | 4212 | 0.1725 | 0.9409 |
| 0.1634 | 10.0 | 4680 | 0.1762 | 0.9394 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
|