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Individual results

View in-depth performance of a single language model on a single test suite.

Region-by-region surprisal

Tip: hover over bars to see surprisal values. Surprisals are averaged over items. Error bars show 95% confidence intervals.
More info: view full details for model TinyLSTM or test suite Subject-Verb Number Agreement (with subject relative clause).

Sample item for Subject-Verb Number Agreement (with subject relative clause)

The first item of the test suite is shown below for quick reference. Please visit the page for Subject-Verb Number Agreement (with subject relative clause) to see the full list of items.

Item	Condition	intro	np_subject	that	embed_vp	the	embed_np	matrix_v	continuation
Item	Condition	intro	np_subject	that	embed_vp	the	embed_np	matrix_v	continuation
1	match_sing	The	author	that	hurt	the	senators	is	good
1	mismatch_sing	The	author	that	hurt	the	senators	are	good
1	match_plural	The	authors	that	hurt	the	senator	are	good
1	mismatch_plural	The	authors	that	hurt	the	senator	is	good

More info: view full details for test suite Subject-Verb Number Agreement (with subject relative clause).

Prediction performance for TinyLSTM on Subject-Verb Number Agreement (with subject relative clause)

Accuracy	Formula	Description
Accuracy	Prediction	Description
0.00%	(602,match_sing/7,matrix_v) < (604,mismatch_sing/7,matrix_v)	No description provided.
36.84%	(603,match_plural/7,matrix_v) < (601,mismatch_plural/7,matrix_v)	No description provided.

Tip: hover over region or condition names to highlight the corresponding entries in the Sample Item above. Predictions are evaluated on region-level surprisal values.
Need help? Take a look at the documentation.

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