| --- |
| license: apache-2.0 |
| tags: |
| - en |
| - image classification |
| - fastai |
| model-index: |
| - name: ohbugger2k by flobbit |
| results: |
| - task: |
| name: image classification |
| type: image-classification |
| metrics: |
| - name: accuracy |
| type: acc |
| num_train_epochs: 7 |
| learning_rate: 0.002 |
| value: 46 |
| metrics: |
| - accuracy |
| pipeline_tag: image-classification |
| --- |
| |
| # Oh! Bugger! 2k Insect Classification |
| |
| ## Model description |
|
|
| The model is used to classify insect images into one of the 2000 North American species/classes. `resnet18` was used for training. |
|
|
| ## Intended uses & limitations |
| The model was trained on 130133 insect images spread over 2000 species with a minimum of 25 pics in a class. Some classes were trained on too few images. The training pics were not screened for quality. For example, giving the model a picture of a human finger will most likely return an insect species that had finger in a training pic. Or a pic of a bug on the siding of a house will likely return that type of match. |
| There are likely other biases in the training data. |
|
|
| ## Training and evaluation data |
|
|
| The images used in training were scraped from the internet. |
