Report for textattack/bert-base-uncased-SST-2

#99
by giskard-bot - opened

Hi Team,

This is a report from Giskard Bot Scan 🐢.

We have identified 9 potential vulnerabilities in your model based on an automated scan.

This automated analysis evaluated the model on the dataset sst2 (subset default, split validation).

👉Robustness issues (1)
Vulnerability Level Data slice Metric Transformation Deviation
Robustness major 🔴 Fail rate = 0.125 Add typos 100/800 tested samples (12.5%) changed prediction after perturbation
🔍✨Examples When feature “text” is perturbed with the transformation “Add typos”, the model changes its prediction in 12.5% of the cases. We expected the predictions not to be affected by this transformation.
text Add typos(text) Original prediction Prediction after perturbation
16 the emotions are raw and will strike a nerve with anyone who 's ever had family trauma . the ekotions are raw andw ill strike a nerve with anyone wgo 's ever had family trauma . LABEL_1 (p = 1.00) LABEL_0 (p = 0.89)
22 holden caulfield did it better . holdsn caulfkeld did t better . LABEL_1 (p = 0.99) LABEL_0 (p = 0.98)
36 the weight of the piece , the unerring professionalism of the chilly production , and the fascination embedded in the lurid topic prove recommendation enough . he weight of the piec e hte unerring professionalism of the chilly production , and the fascination embeded in the lurid topic prove rrcommendatioh enough . LABEL_1 (p = 1.00) LABEL_0 (p = 0.98)
👉Performance issues (8)
Vulnerability Level Data slice Metric Transformation Deviation
Performance major 🔴 avg_word_length(text) < 4.618 AND avg_word_length(text) >= 4.483 Precision = 0.788 -14.19% than global
🔍✨Examples For records in the dataset where `avg_word_length(text)` < 4.618 AND `avg_word_length(text)` >= 4.483, the Precision is 14.19% lower than the global Precision.
text avg_word_length(text) label Predicted label
22 holden caulfield did it better . 4.5 LABEL_0 LABEL_1 (p = 0.99)
95 this riveting world war ii moral suspense story deals with the shadow side of american culture : racial prejudice in its ugly and diverse forms . 4.61538 LABEL_0 LABEL_1 (p = 1.00)
115 sam mendes has become valedictorian at the school for soft landings and easy ways out . 4.5 LABEL_0 LABEL_1 (p = 0.98)
Vulnerability Level Data slice Metric Transformation Deviation
Performance major 🔴 avg_whitespace(text) >= 0.178 AND avg_whitespace(text) < 0.182 Precision = 0.788 -14.19% than global
🔍✨Examples For records in the dataset where `avg_whitespace(text)` >= 0.178 AND `avg_whitespace(text)` < 0.182, the Precision is 14.19% lower than the global Precision.
text avg_whitespace(text) label Predicted label
22 holden caulfield did it better . 0.181818 LABEL_0 LABEL_1 (p = 0.99)
95 this riveting world war ii moral suspense story deals with the shadow side of american culture : racial prejudice in its ugly and diverse forms . 0.178082 LABEL_0 LABEL_1 (p = 1.00)
115 sam mendes has become valedictorian at the school for soft landings and easy ways out . 0.181818 LABEL_0 LABEL_1 (p = 0.98)
Vulnerability Level Data slice Metric Transformation Deviation
Performance major 🔴 avg_word_length(text) < 3.867 AND avg_word_length(text) >= 3.691 Recall = 0.840 -10.13% than global
🔍✨Examples For records in the dataset where `avg_word_length(text)` < 3.867 AND `avg_word_length(text)` >= 3.691, the Recall is 10.13% lower than the global Recall.
text avg_word_length(text) label Predicted label
92 you wo n't like roger , but you will quickly recognize him . 3.69231 LABEL_0 LABEL_1 (p = 1.00)
93 if steven soderbergh 's ` solaris ' is a failure it is a glorious failure . 3.75 LABEL_1 LABEL_0 (p = 0.59)
183 the lower your expectations , the more you 'll enjoy it . 3.83333 LABEL_0 LABEL_1 (p = 1.00)
Vulnerability Level Data slice Metric Transformation Deviation
Performance major 🔴 avg_whitespace(text) >= 0.205 AND avg_whitespace(text) < 0.213 Recall = 0.840 -10.13% than global
🔍✨Examples For records in the dataset where `avg_whitespace(text)` >= 0.205 AND `avg_whitespace(text)` < 0.213, the Recall is 10.13% lower than the global Recall.
text avg_whitespace(text) label Predicted label
92 you wo n't like roger , but you will quickly recognize him . 0.213115 LABEL_0 LABEL_1 (p = 1.00)
93 if steven soderbergh 's ` solaris ' is a failure it is a glorious failure . 0.210526 LABEL_1 LABEL_0 (p = 0.59)
183 the lower your expectations , the more you 'll enjoy it . 0.206897 LABEL_0 LABEL_1 (p = 1.00)
Vulnerability Level Data slice Metric Transformation Deviation
Performance medium 🟡 text contains "movie" Precision = 0.837 -8.81% than global
🔍✨Examples For records in the dataset where `text` contains "movie", the Precision is 8.81% lower than the global Precision.
text label Predicted label
69 this one is definitely one to skip , even for horror movie fanatics . LABEL_0 LABEL_1 (p = 0.95)
172 it seems like i have been waiting my whole life for this movie and now i ca n't wait for the sequel . LABEL_1 LABEL_0 (p = 0.72)
509 a movie that successfully crushes a best selling novel into a timeframe that mandates that you avoid the godzilla sized soda . LABEL_1 LABEL_0 (p = 0.91)
Vulnerability Level Data slice Metric Transformation Deviation
Performance medium 🟡 text_length(text) < 82.500 AND text_length(text) >= 73.500 Recall = 0.870 -6.97% than global
🔍✨Examples For records in the dataset where `text_length(text)` < 82.500 AND `text_length(text)` >= 73.500, the Recall is 6.97% lower than the global Recall.
text text_length(text) label Predicted label
93 if steven soderbergh 's ` solaris ' is a failure it is a glorious failure . 76 LABEL_1 LABEL_0 (p = 0.59)
142 what better message than ` love thyself ' could young women of any size receive ? 82 LABEL_1 LABEL_0 (p = 0.98)
411 i do n't mind having my heartstrings pulled , but do n't treat me like a fool . 80 LABEL_0 LABEL_1 (p = 0.95)
Vulnerability Level Data slice Metric Transformation Deviation
Performance medium 🟡 text_length(text) >= 165.500 AND text_length(text) < 183.500 Recall = 0.872 -6.73% than global
🔍✨Examples For records in the dataset where `text_length(text)` >= 165.500 AND `text_length(text)` < 183.500, the Recall is 6.73% lower than the global Recall.
text text_length(text) label Predicted label
266 a coda in every sense , the pinochet case splits time between a minute-by-minute account of the british court 's extradition chess game and the regime 's talking-head survivors . 179 LABEL_1 LABEL_0 (p = 0.85)
282 while there 's something intrinsically funny about sir anthony hopkins saying ` get in the car , bitch , ' this jerry bruckheimer production has little else to offer 166 LABEL_1 LABEL_0 (p = 1.00)
292 the story and the friendship proceeds in such a way that you 're watching a soap opera rather than a chronicle of the ups and downs that accompany lifelong friendships . 170 LABEL_0 LABEL_1 (p = 0.88)
Vulnerability Level Data slice Metric Transformation Deviation
Performance medium 🟡 text_length(text) < 98.500 AND text_length(text) >= 86.500 Precision = 0.861 -6.21% than global
🔍✨Examples For records in the dataset where `text_length(text)` < 98.500 AND `text_length(text)` >= 86.500, the Precision is 6.21% lower than the global Precision.
text text_length(text) label Predicted label
115 sam mendes has become valedictorian at the school for soft landings and easy ways out . 88 LABEL_0 LABEL_1 (p = 0.98)
230 reign of fire looks as if it was made without much thought -- and is best watched that way . 93 LABEL_1 LABEL_0 (p = 1.00)
519 moretti 's compelling anatomy of grief and the difficult process of adapting to loss . 87 LABEL_0 LABEL_1 (p = 1.00)

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