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Report for cardiffnlp/twitter-roberta-base-irony
Hey Team!🤗✨
We’re thrilled to share some amazing evaluation results that’ll make your day!🎉📊
We have identified 1 potential vulnerabilities in your model based on an automated scan.
This automated analysis evaluated the model on the dataset tweet_eval (subset irony, split train).
👉Performance issues (1)
| Vulnerability | Level | Data slice | Metric | Transformation | Deviation |
|---|---|---|---|---|---|
| Performance | major 🔴 | text contains "love" |
Accuracy = 0.247 | — | -50.10% than global |
🔍✨Examples
For records in the dataset where `text` contains "love", the Accuracy is 50.1% lower than the global Accuracy.| text | label | Predicted label |
|
|---|---|---|---|
| 32 | Love that I still have kids that still wake up early on Christmas #justkiddingIlovethem | non_irony | irony (p = 0.99) |
| 34 | Oh god I just so happens that i love really LOVE slow internet #slowinternet | non_irony | irony (p = 0.98) |
| 36 | isnt it the best when youre really tired then when you finally get in bed youre wide awake? I LOVE IT | non_irony | irony (p = 0.93) |
Checkout out the Giskard Space and improve your model.
Disclaimer: it's important to note that automated scans may produce false positives or miss certain vulnerabilities. We encourage you to review the findings and assess the impact accordingly.
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🙌 Big Thanks!
We're grateful to have you on this adventure with us. 🚀🌟 Here's to more breakthroughs, laughter, and code magic! 🥂✨ Keep hugging that code and spreading the love! 💻 #Giskard #Huggingface #AISafety 🌈👏 Your enthusiasm, feedback, and contributions are what seek. 🌟 Keep being awesome!