usk-coffee-convnext-nano / gradio_article.md
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A newer version of the Gradio SDK is available: 5.7.0

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Dataset

The USK-Coffee dataset, made available at https://comvis.unsyiah.ac.id/usk-coffee/ is multi class image dataset derived from a coffee bean collection that includes 4 classes: peaberry, longberry, defect, and premium.

Training

Fast.ai was used to train this classifier with a Timm ConvNext nano vision learner, without heavy customization. The training was performed on the provided train split, and validation on the val split.

The final fine tuning of the training loop resulted in the following losses.

epoch train_loss valid_loss accuracy time
0 0.238523 0.383621 0.869375 00:25
1 0.257938 0.293417 0.907500 00:25
2 0.205048 0.412420 0.847500 00:25
3 0.170284 0.308219 0.901875 00:25
4 0.154471 0.308811 0.894375 00:26
5 0.107862 0.480474 0.874375 00:26
6 0.075452 0.506489 0.843125 00:26
7 0.060802 0.317052 0.906875 00:26
8 0.049216 0.242317 0.932500 00:26
9 0.040890 0.233353 0.935625 00:26

Examples

The example images provided in the demo are from the test split in the dataset, which was never made available to the model in the training process.