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---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- mit
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- extended
task_categories:
- image-classification
task_ids:
- multi-class-image-classification
pretty_name: Beans
dataset_info:
  features:
  - name: image_file_path
    dtype: string
  - name: image
    dtype: image
  - name: labels
    dtype:
      class_label:
        names:
          '0': angular_leaf_spot
          '1': bean_rust
          '2': healthy
  - name: embedding_foundation
    sequence: float32
  - name: embedding_ft
    sequence: float32
  - name: outlier_score_ft
    dtype: float64
  - name: outlier_score_foundation
    dtype: float64
  - name: nn_image
    dtype: image
  splits:
  - name: train
    num_bytes: 293531811.754
    num_examples: 1034
  download_size: 0
  dataset_size: 293531811.754
---
# Dataset Card for "beans-outlier"

📚 This dataset is an enhancved version of the [ibean project of the AIR lab](https://github.com/AI-Lab-Makerere/ibean/).

The workflow is described in the medium article: [Changes of Embeddings during Fine-Tuning of Transformers](https://medium.com/@markus.stoll/changes-of-embeddings-during-fine-tuning-c22aa1615921).

## Explore the Dataset

The open source data curation tool [Renumics Spotlight](https://github.com/Renumics/spotlight) allows you to explorer this dataset. You can find a Hugging Face Space running Spotlight with this dataset here: <https://huggingface.co/spaces/renumics/beans-outlier>
![Analyze with Spotlight](https://spotlight.renumics.com/resources/hf-beans-outlier.png)



Or you can explorer it locally:

```python
!pip install renumics-spotlight datasets
from renumics import spotlight
import datasets

ds = datasets.load_dataset("renumics/beansoutlier", split="train")
df = ds.to_pandas()
df["label_str"] = df["labels"].apply(lambda x: ds.features["labels"].int2str(x))
dtypes = {
    "nn_image": spotlight.Image,
    "image": spotlight.Image,
    "embedding_ft": spotlight.Embedding,
    "embedding_foundation": spotlight.Embedding,
}
spotlight.show(
    df,
    dtype=dtypes,
    layout="https://spotlight.renumics.com/resources/layout_pre_post_ft.json",
)
```