

# Model card

## Model description

This model has been trained with convnext_tiny_in22k with [Flowers-101 datasets in Kaggle](https://www.kaggle.com/competitions/tpu-getting-started).

**Useful graphs logged with wandb**

![image](https://user-images.githubusercontent.com/24592806/177065734-2d2920d2-adf2-4d73-8e89-a59e269544d4.png)
![image](https://user-images.githubusercontent.com/24592806/177065795-5c66ae3f-5e05-44c3-a6e5-0abb302c7d50.png)

## Intended uses & limitations

- The model can be used be for classifying flowers only.

**Limitations**

- Even if the picture uploaded is not of a flower, you can can notice [it will be predicted as of flower](https://www.kaggle.com/competitions/tpu-getting-started).
- The model on validation dataset has accuracy of 94.23%

![image](https://user-images.githubusercontent.com/24592806/177065484-1fae6a79-5dbe-471a-8c86-9c5aaa336bc6.png)


## Training and evaluation data

- The models has been trained and evaluated with [Flowers-101 datasets in Kaggle](https://www.kaggle.com/competitions/tpu-getting-started).
- We used a Random Splitter to train and evaluate data


{"tags": ["fastai", "image-classification"]}
fastai image-classification has_space region:us
TAGS
#fastai #image-classification #has_space #region-us 



# Model card

## Model description

This model has been trained with convnext_tiny_in22k with Flowers-101 datasets in Kaggle.

Useful graphs logged with wandb

!image
!image

## Intended uses & limitations

- The model can be used be for classifying flowers only.

Limitations

- Even if the picture uploaded is not of a flower, you can can notice it will be predicted as of flower.
- The model on validation dataset has accuracy of 94.23%

!image


## Training and evaluation data

- The models has been trained and evaluated with Flowers-101 datasets in Kaggle.
- We used a Random Splitter to train and evaluate data


# Model card ## Model description

This model has been trained with convnext_tiny_in22k with Flowers-101 datasets in Kaggle.

Useful graphs logged with wandb

!image
!image ## Intended uses & limitations

- The model can be used be for classifying flowers only.

Limitations

- Even if the picture uploaded is not of a flower, you can can notice it will be predicted as of flower.
- The model on validation dataset has accuracy of 94.23%

!image ## Training and evaluation data

- The models has been trained and evaluated with Flowers-101 datasets in Kaggle.
- We used a Random Splitter to train and evaluate data
TAGS
#fastai #image-classification #has_space #region-us 
 # Model card ## Model description

This model has been trained with convnext_tiny_in22k with Flowers-101 datasets in Kaggle.

Useful graphs logged with wandb

!image
!image ## Intended uses & limitations

- The model can be used be for classifying flowers only.

Limitations

- Even if the picture uploaded is not of a flower, you can can notice it will be predicted as of flower.
- The model on validation dataset has accuracy of 94.23%

!image ## Training and evaluation data

- The models has been trained and evaluated with Flowers-101 datasets in Kaggle.
- We used a Random Splitter to train and evaluate data
passage: TAGS
#fastai #image-classification #has_space #region-us 
# Model card## Model description

This model has been trained with convnext_tiny_in22k with Flowers-101 datasets in Kaggle.

Useful graphs logged with wandb

!image
!image## Intended uses & limitations

- The model can be used be for classifying flowers only.

Limitations

- Even if the picture uploaded is not of a flower, you can can notice it will be predicted as of flower.
- The model on validation dataset has accuracy of 94.23%

!image## Training and evaluation data

- The models has been trained and evaluated with Flowers-101 datasets in Kaggle.
- We used a Random Splitter to train and evaluate data