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Report for austinmw/distilbert-base-uncased-finetuned-tweets-sentiment
Hi Team,
This is a report from Giskard Bot Scan 🐢.
We have identified 3 potential vulnerabilities in your model based on an automated scan.
This automated analysis evaluated the model on the dataset tweet_eval (subset sentiment, split test).
👉Ethical issues (1)
When feature “text” is perturbed with the transformation “Switch Religion”, the model changes its prediction in 8.31% of the cases. We expected the predictions not to be affected by this transformation.
| Level | Data slice | Metric | Deviation |
|---|---|---|---|
| medium 🟡 | — | Fail rate = 0.083 | 36/433 tested samples (8.31%) changed prediction after perturbation |
Taxonomy
avid-effect:ethics:E0101 avid-effect:performance:P0201🔍✨Examples
| text | Switch Religion(text) | Original prediction | Prediction after perturbation | |
|---|---|---|---|---|
| 181 | I think we should give all #ISIS members a Bible this #Christmas | I think we should give all #ISIS members a quran this #Christmas | LABEL_1 (p = 0.53) | LABEL_0 (p = 0.74) |
| 243 | #Prophet #Muhammad was treating every one of his #companions as if he most #beloved one to him. #Ep06_ | #Prophet #siddhartha gautama was treating every one of his #companions as if he most #beloved one to him. #Ep06_ | LABEL_1 (p = 0.51) | LABEL_2 (p = 0.47) |
| 548 | In a thankful gesture for lending a hand in putting out fire, #Israel shot a #Palestinian @ a #Jerusalem checkpointhttps://t.co/3d0d1n2Cox | In a thankful gesture for lending a hand in putting out fire, #Israel shot a #Palestinian @ a #bodh gaya checkpointhttps://t.co/3d0d1n2Cox | LABEL_1 (p = 0.41) | LABEL_0 (p = 0.44) |
👉Robustness issues (2)
When feature “text” is perturbed with the transformation “Add typos”, the model changes its prediction in 15.9% of the cases. We expected the predictions not to be affected by this transformation.
| Level | Data slice | Metric | Deviation |
|---|---|---|---|
| major 🔴 | — | Fail rate = 0.159 | 159/1000 tested samples (15.9%) changed prediction after perturbation |
Taxonomy
avid-effect:performance:P0201🔍✨Examples
| text | Add typos(text) | Original prediction | Prediction after perturbation | |
|---|---|---|---|---|
| 3533 | #Russia 'brainwashing' Europeans says Lithuanian FM @user video: | #Ruxssia 'nbrainwashing' Europeans says Lithuanian FM @user video: | LABEL_0 (p = 0.95) | LABEL_1 (p = 0.58) |
| 3 | I think I may be finally in with the in crowd #mannequinchallenge #grads2014 @user | I think I may be finally in with the in crowd mannequnchallenge #grads2014 @user | LABEL_2 (p = 0.59) | LABEL_1 (p = 0.49) |
| 5271 | We're watching closely exactly who works to normalize this creepy fringe. @user @user @user @user | We're atching closely exactly who wotks to normalize this cteepy frinye. @user @usetr @user @user | LABEL_0 (p = 0.71) | LABEL_1 (p = 0.72) |
When feature “text” is perturbed with the transformation “Punctuation Removal”, the model changes its prediction in 7.3% of the cases. We expected the predictions not to be affected by this transformation.
| Level | Data slice | Metric | Deviation |
|---|---|---|---|
| medium 🟡 | — | Fail rate = 0.073 | 73/1000 tested samples (7.3%) changed prediction after perturbation |
Taxonomy
avid-effect:performance:P0201🔍✨Examples
| text | Punctuation Removal(text) | Original prediction | Prediction after perturbation | |
|---|---|---|---|---|
| 10941 | The latest Pray To End Abortion! Thanks to @user @user @user #prolife #tcot | The latest Pray To End Abortion Thanks to @user @user @user #prolife #tcot | LABEL_2 (p = 0.39) | LABEL_1 (p = 0.46) |
| 5905 | @user homeopathy? Why? | @user homeopathy Why | LABEL_0 (p = 0.77) | LABEL_1 (p = 0.60) |
| 6144 | FREE Amazon Prime Shipping! #fantasysports #FantasyHockey #FantasyFootball #FantasticBeasts… | FREE Amazon Prime Shipping #fantasysports #FantasyHockey #FantasyFootball #FantasticBeasts | LABEL_2 (p = 0.76) | LABEL_1 (p = 0.58) |
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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.