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---
license: apache-2.0
tags:
- generated_from_trainer
- image-classification
datasets:
- beans
metrics:
- accuracy
widget:
- src: https://huggingface.co/nateraw/vit-base-beans/resolve/main/healthy.jpeg
example_title: Healthy
- src: https://huggingface.co/nateraw/vit-base-beans/resolve/main/angular_leaf_spot.jpeg
example_title: Angular Leaf Spot
- src: https://huggingface.co/nateraw/vit-base-beans/resolve/main/bean_rust.jpeg
example_title: Bean Rust
model-index:
- name: vit-base-beans
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: beans
type: beans
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9774436090225563
- task:
type: image-classification
name: Image Classification
dataset:
name: beans
type: beans
config: default
split: test
metrics:
- name: Accuracy
type: accuracy
value: 0.9453125
verified: true
- name: Precision Macro
type: precision
value: 0.9453325082933705
verified: true
- name: Precision Micro
type: precision
value: 0.9453125
verified: true
- name: Precision Weighted
type: precision
value: 0.9452605321507761
verified: true
- name: Recall Macro
type: recall
value: 0.945736434108527
verified: true
- name: Recall Micro
type: recall
value: 0.9453125
verified: true
- name: Recall Weighted
type: recall
value: 0.9453125
verified: true
- name: F1 Macro
type: f1
value: 0.9451827242524917
verified: true
- name: F1 Micro
type: f1
value: 0.9453125
verified: true
- name: F1 Weighted
type: f1
value: 0.944936150332226
verified: true
- name: loss
type: loss
value: 0.26030588150024414
verified: true
---
<!-- 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: 0.0942
- Accuracy: 0.9774
## 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: 5.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2809 | 1.0 | 130 | 0.2287 | 0.9699 |
| 0.1097 | 2.0 | 260 | 0.1676 | 0.9624 |
| 0.1027 | 3.0 | 390 | 0.0942 | 0.9774 |
| 0.0923 | 4.0 | 520 | 0.1104 | 0.9699 |
| 0.1726 | 5.0 | 650 | 0.1030 | 0.9699 |
### Framework versions
- Transformers 4.10.0.dev0
- Pytorch 1.9.0+cu102
- Datasets 1.11.1.dev0
- Tokenizers 0.10.3
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