metadata
library_name: transformers
language:
- en
base_model:
- microsoft/deberta-base
pipeline_tag: text-classification
Model Card
This model is a finetuned version of microsoft/deberta-base on the Onion or Not dataset. The model was fine-tuned for 5 epochs with a learning rate of 2e-5 and a linear schedule. Random token dropout was implemented during training to avoid overfitting. The classification report is shown below:
Final Validation Accuracy: 93.31%
Final Classification Report:
precision recall f1-score support
NotOnion 0.94 0.96 0.95 3000
Onion 0.93 0.89 0.91 1800
accuracy 0.93 4800
macro avg 0.93 0.92 0.93 4800
weighted avg 0.93 0.93 0.93 4800
Running inference on a new sample gave the correct prediction:
Running example inference...
Text: Man With Fogged-Up Glasses Forced To Finish Soup Using Other Senses
Prediction: Onion
Confidence: 87.76%
Probabilities:
NotOnion: 12.24%
Onion: 87.76%