|
--- |
|
license: apache-2.0 |
|
tags: |
|
- image-classification |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: beit-base-ches-demo-v0 |
|
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: 0.9870689655172413 |
|
widget: |
|
- src: https://imgs.mongabay.com/wp-content/uploads/sites/20/2020/04/07204605/amazon_coca_01.jpg |
|
example_title: Tree Canopy |
|
- src: https://images.ctfassets.net/nzn0tepgtyr1/4tyavnFHhmNuVky1ISq51k/64aaf596f6b8ee12d0f0e898679c8f4f/Hero_Image.jpg?w=1024&h=710&fl=progressive&q=50&fm=jpg&bg=transparent |
|
example_title: Low Vegetation |
|
- src: https://outline-prod.imgix.net/20170228-YxGtsv8J0ePP0rXcnle2?auto=format&q=60&w=1280&s=27916f48ed9226c2a2b7848de8d7c0d1 |
|
example_title: Impervious Surfaces |
|
- src: https://clarity.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/MapServer/tile/15/11883/10109 |
|
example_title: Water |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# beit-base-ches-demo-v0 |
|
|
|
This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co./microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0420 |
|
- Accuracy: 0.9871 |
|
|
|
## 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: 128 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 4 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.0183 | 3.45 | 300 | 0.0420 | 0.9871 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.24.0 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 2.7.0 |
|
- Tokenizers 0.13.2 |
|
|
