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---
license: apache-2.0
tags:
- image-classification
- vision
- generated_from_trainer
datasets:
- beans
metrics:
- accuracy
model-index:
- name: vit-base-beans
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: beans
type: beans
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9774436090225563
---
<!-- 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:
- Accuracy: 0.9774
- Loss: 0.0863
## 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
- distributed_type: tpu
- 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 | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 0.2576 | 1.0 | 130 | 0.9549 | 0.2310 |
| 0.2848 | 2.0 | 260 | 0.9925 | 0.1129 |
| 0.1504 | 3.0 | 390 | 0.9624 | 0.1124 |
| 0.0922 | 4.0 | 520 | 0.9925 | 0.0860 |
| 0.1633 | 5.0 | 650 | 0.9774 | 0.0863 |
### Framework versions
- Transformers 4.27.0.dev0
- Pytorch 2.0.0a0+git45d775c
- Datasets 2.9.1.dev0
- Tokenizers 0.12.1
|