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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: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8195488721804511
---
<!-- 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-huge-patch14-224-in21k](https://huggingface.co/google/vit-huge-patch14-224-in21k) on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9760
- Accuracy: 0.8195
## 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: 4
- eval_batch_size: 4
- seed: 1337
- 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 | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0596 | 1.0 | 259 | 1.0507 | 0.7143 |
| 1.0165 | 2.0 | 518 | 1.0165 | 0.7895 |
| 1.0113 | 3.0 | 777 | 0.9941 | 0.8045 |
| 1.0067 | 4.0 | 1036 | 0.9804 | 0.8195 |
| 0.9746 | 5.0 | 1295 | 0.9760 | 0.8195 |
### Framework versions
- Transformers 4.31.0.dev0
- Pytorch 1.13.1+cu117-with-pypi-cudnn
- Datasets 2.12.0
- Tokenizers 0.13.3
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