|
--- |
|
license: apache-2.0 |
|
tags: |
|
- image-classification |
|
- generated_from_trainer |
|
datasets: |
|
- beans |
|
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 |
|
metrics: |
|
- accuracy |
|
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: 0.9849624060150376 |
|
- task: |
|
type: image-classification |
|
name: Image Classification |
|
dataset: |
|
name: beans |
|
type: beans |
|
config: default |
|
split: test |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.96875 |
|
verified: true |
|
- name: Precision Macro |
|
type: precision |
|
value: 0.9716312056737588 |
|
verified: true |
|
- name: Precision Micro |
|
type: precision |
|
value: 0.96875 |
|
verified: true |
|
- name: Precision Weighted |
|
type: precision |
|
value: 0.9714095744680851 |
|
verified: true |
|
- name: Recall Macro |
|
type: recall |
|
value: 0.9689922480620154 |
|
verified: true |
|
- name: Recall Micro |
|
type: recall |
|
value: 0.96875 |
|
verified: true |
|
- name: Recall Weighted |
|
type: recall |
|
value: 0.96875 |
|
verified: true |
|
- name: F1 Macro |
|
type: f1 |
|
value: 0.9689250225835592 |
|
verified: true |
|
- name: F1 Micro |
|
type: f1 |
|
value: 0.96875 |
|
verified: true |
|
- name: F1 Weighted |
|
type: f1 |
|
value: 0.9686822493224932 |
|
verified: true |
|
- name: loss |
|
type: loss |
|
value: 0.1282731592655182 |
|
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: 0.0505 |
|
- Accuracy: 0.9850 |
|
|
|
## 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: 0.0002 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 8 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.1166 | 1.54 | 100 | 0.0764 | 0.9850 | |
|
| 0.1607 | 3.08 | 200 | 0.2114 | 0.9398 | |
|
| 0.0067 | 4.62 | 300 | 0.0692 | 0.9774 | |
|
| 0.005 | 6.15 | 400 | 0.0944 | 0.9624 | |
|
| 0.0043 | 7.69 | 500 | 0.0505 | 0.9850 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.16.2 |
|
- Pytorch 1.10.0+cu111 |
|
- Datasets 1.18.3 |
|
- Tokenizers 0.11.0 |
|
|
