Assessed Model

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Assessed Model has 39 facts recorded in Dontopedia across 1 reference.

39 facts·39 predicates·1 sources

Mostly:absorbed style of dataset(1), achieved perplexity(1), achieves decode speed(1)

Inbound mentions (22)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

`advocatesMoreTrainingData`Advocates More Training Data(1)

Xenonfunex:xenonfun

`assessesLanguageQualityOfModel`Assesses Language Quality of Model(1)

Xenonfunex:xenonfun

`assessesSpeedOfModel`Assesses Speed of Model(1)

Xenonfunex:xenonfun

`believesModelIsAtExpectedStage`Believes Model Is at Expected Stage(1)

Xenonfunex:xenonfun

`causesFluentGibberishStage`Causes Fluent Gibberish Stage(1)

Training Tokensex:training-tokens

`characterizesModelAsFluentGibberish`Characterizes Model As Fluent Gibberish(1)

Xenonfunex:xenonfun

`criticizesFactualInaccuracies`Criticizes Factual Inaccuracies(1)

Xenonfunex:xenonfun

`describesSpeedAsVeryFast`Describes Speed As Very Fast(1)

Xenonfunex:xenonfun

`droppedConsistently`Dropped Consistently(1)

Training Lossex:training-loss

`enablesLearningPotential`Enables Learning Potential(1)

Architectureex:architecture

`expectsPerformanceAtCurrentTrainingLevel`Expects Performance at Current Training Level(1)

Xenonfunex:xenonfun

`framesModelAsPromisingEarlyStage`Frames Model As Promising Early Stage(1)

This Assessmentex:this-assessment

`implicatesNeedForScaling`Implicates Need for Scaling(1)

Xenonfunex:xenonfun

`isWrongButDemonstratesAssociation`Is Wrong But Demonstrates Association(1)

Topic Association Cats Dogs Medicalex:topic-association-cats-dogs-medical

`mostlyGrammatical`Mostly Grammatical(1)

Sentence Structureex:sentence-structure

`producedEncyclopediaText`Produced Encyclopedia Text(1)

Once Upon a Time Promptex:once-upon-a-time-prompt

`providesPerformanceEvaluation`Provides Performance Evaluation(1)

This Assessmentex:this-assessment

`recommendsMoreDataForModel`Recommends More Data for Model(1)

Xenonfunex:xenonfun

`sometimesRunsToMaxTokens`Sometimes Runs to Max Tokens(1)

Eot Behaviorex:eot-behavior

`sometimesStopsAppropriately`Sometimes Stops Appropriately(1)

Eot Behaviorex:eot-behavior

`worksWell`Works Well(1)

O1 Recurrent Decodeex:o1-recurrent-decode

`wouldTeachQuestionAnswering`Would Teach Question Answering(1)

Conversation Datasetex:conversation-dataset

Other facts (39)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

39 facts

Predicate	Value	Ref
Absorbed Style of Dataset	Fineweb Edu	[1]
Achieved Perplexity	345	[1]
Achieves Decode Speed	265	[1]
Architecture Is Capable of Learning	Architecture	[1]
Associates2050 With	future predictions	[1]
Associates Cats and Dogs With	medical content	[1]
Associates Topic	Water Cycle	[1]
Cannot Stay on Single Subject	true	[1]
Commits to Domain Associations	Topic Association	[1]
Compares Unfavorably to Gpt2 in Tokens	Gpt 2 Small	[1]
Currently Produces Essay Fragments	true	[1]
Demonstrated Learning Capability	true	[1]
Does Not Understand What Is X As Question	What Is X Question	[1]
Exhibits Academic Register	Academic Register	[1]
Exhibits Eot Behavior	Eot Behavior	[1]
Exhibits Topic Association	Topic Association	[1]
Exhibits Topic Drift	Topic Coherence	[1]
Exists in Fluent But Shallow Semantic State	null	[1]
Has Effective Params	37400000	[1]
Has Language Quality Stage	Early-stage	[1]
Has Language Quality Utility	not yet useful	[1]
Has Learned Sentence Structure	Sentence Structure	[1]
Has Parameter Count	108000000	[1]
Has Prefill Time	14-27ms	[1]
Has Speed Rating	Excellent	[1]
Lacks Actual Question Answering	Question Answering	[1]
Lacks Factual Accuracy	Factual Accuracy	[1]
Lacks Story Structure	Story Structure	[1]
Makes Up Citations	true	[1]
Makes Up Dates	true	[1]
Makes Up Numbers	true	[1]
Presupposes Existence of Learned Behaviors	Sentence Structure	[1]
Received Tokens Percentage of Gpt2	0.007	[1]
Says Nothing Substantive	true	[1]
Sounds Educated	true	[1]
Trained on Total Tokens	273000000	[1]
Uses Compiled O1 Recurrent Decode	O1 Recurrent Decode	[1]
Uses Proper Punctuation	true	[1]
Uses Quotes	true	[1]

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

39 undated

—

absorbedStyleOfDatasetblah/watt-activation/part-162

ex:fineweb-edu

—

achievedPerplexityblah/watt-activation/part-162

345

—

achievesDecodeSpeedblah/watt-activation/part-162

265

—

architectureIsCapableOfLearningblah/watt-activation/part-162

ex:architecture

—

associates2050Withblah/watt-activation/part-162

future predictions

—

associatesCatsAndDogsWithblah/watt-activation/part-162

medical content

—

associatesTopicblah/watt-activation/part-162

ex:water-cycle

—

cannotStayOnSingleSubjectblah/watt-activation/part-162

true

—

commitsToDomainAssociationsblah/watt-activation/part-162

ex:topic-association

—

comparesUnfavorablyToGpt2InTokensblah/watt-activation/part-162

ex:gpt-2-small

—

currentlyProducesEssayFragmentsblah/watt-activation/part-162

true

—

demonstratedLearningCapabilityblah/watt-activation/part-162

true

—

doesNotUnderstandWhatIsXAsQuestionblah/watt-activation/part-162

ex:what-is-x-question

—

exhibitsAcademicRegisterblah/watt-activation/part-162

ex:academic-register

—

exhibitsEotBehaviorblah/watt-activation/part-162

ex:eot-behavior

—

exhibitsTopicAssociationblah/watt-activation/part-162

ex:topic-association

—

exhibitsTopicDriftblah/watt-activation/part-162

ex:topic-coherence

—

existsInFluentButShallowSemanticStateblah/watt-activation/part-162

null

—

hasEffectiveParamsblah/watt-activation/part-162

37400000

—

hasLanguageQualityStageblah/watt-activation/part-162

Early-stage

—

hasLanguageQualityUtilityblah/watt-activation/part-162

not yet useful

—

hasLearnedSentenceStructureblah/watt-activation/part-162

ex:sentence-structure

—

hasParameterCountblah/watt-activation/part-162

108000000

—

hasPrefillTimeblah/watt-activation/part-162

14-27ms

—

hasSpeedRatingblah/watt-activation/part-162

Excellent

—

lacksActualQuestionAnsweringblah/watt-activation/part-162

ex:question-answering

—

lacksFactualAccuracyblah/watt-activation/part-162

ex:factual-accuracy

—

lacksStoryStructureblah/watt-activation/part-162

ex:story-structure

—

makesUpCitationsblah/watt-activation/part-162

true

—

makesUpDatesblah/watt-activation/part-162

true

—

makesUpNumbersblah/watt-activation/part-162

true

—

presupposesExistenceOfLearnedBehaviorsblah/watt-activation/part-162

ex:sentence-structure

—

receivedTokensPercentageOfGpt2blah/watt-activation/part-162

0.007

—

saysNothingSubstantiveblah/watt-activation/part-162

true

—

soundsEducatedblah/watt-activation/part-162

true

—

trainedOnTotalTokensblah/watt-activation/part-162

273000000

—

usesCompiledO1RecurrentDecodeblah/watt-activation/part-162

ex:o1-recurrent-decode

—

usesProperPunctuationblah/watt-activation/part-162

true

—

usesQuotesblah/watt-activation/part-162

true

References (1)

1 references

[1]Part 16239 facts
ctx:discord/blah/watt-activation/part-162

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Assessed Model

Inbound mentions (22)

advocatesMoreTrainingDataAdvocates More Training Data(1)

assessesLanguageQualityOfModelAssesses Language Quality of Model(1)

assessesSpeedOfModelAssesses Speed of Model(1)

believesModelIsAtExpectedStageBelieves Model Is at Expected Stage(1)

causesFluentGibberishStageCauses Fluent Gibberish Stage(1)

characterizesModelAsFluentGibberishCharacterizes Model As Fluent Gibberish(1)

criticizesFactualInaccuraciesCriticizes Factual Inaccuracies(1)

describesSpeedAsVeryFastDescribes Speed As Very Fast(1)

droppedConsistentlyDropped Consistently(1)

enablesLearningPotentialEnables Learning Potential(1)

expectsPerformanceAtCurrentTrainingLevelExpects Performance at Current Training Level(1)

framesModelAsPromisingEarlyStageFrames Model As Promising Early Stage(1)

implicatesNeedForScalingImplicates Need for Scaling(1)

isWrongButDemonstratesAssociationIs Wrong But Demonstrates Association(1)

mostlyGrammaticalMostly Grammatical(1)

producedEncyclopediaTextProduced Encyclopedia Text(1)

providesPerformanceEvaluationProvides Performance Evaluation(1)

recommendsMoreDataForModelRecommends More Data for Model(1)

sometimesRunsToMaxTokensSometimes Runs to Max Tokens(1)

sometimesStopsAppropriatelySometimes Stops Appropriately(1)

worksWellWorks Well(1)

wouldTeachQuestionAnsweringWould Teach Question Answering(1)

Other facts (39)

Timeline

References (1)

See also

Keep researching

`advocatesMoreTrainingData`Advocates More Training Data(1)

`assessesLanguageQualityOfModel`Assesses Language Quality of Model(1)

`assessesSpeedOfModel`Assesses Speed of Model(1)

`believesModelIsAtExpectedStage`Believes Model Is at Expected Stage(1)

`causesFluentGibberishStage`Causes Fluent Gibberish Stage(1)

`characterizesModelAsFluentGibberish`Characterizes Model As Fluent Gibberish(1)

`criticizesFactualInaccuracies`Criticizes Factual Inaccuracies(1)

`describesSpeedAsVeryFast`Describes Speed As Very Fast(1)

`droppedConsistently`Dropped Consistently(1)

`enablesLearningPotential`Enables Learning Potential(1)

`expectsPerformanceAtCurrentTrainingLevel`Expects Performance at Current Training Level(1)

`framesModelAsPromisingEarlyStage`Frames Model As Promising Early Stage(1)

`implicatesNeedForScaling`Implicates Need for Scaling(1)

`isWrongButDemonstratesAssociation`Is Wrong But Demonstrates Association(1)

`mostlyGrammatical`Mostly Grammatical(1)

`producedEncyclopediaText`Produced Encyclopedia Text(1)

`providesPerformanceEvaluation`Provides Performance Evaluation(1)

`recommendsMoreDataForModel`Recommends More Data for Model(1)

`sometimesRunsToMaxTokens`Sometimes Runs to Max Tokens(1)

`sometimesStopsAppropriately`Sometimes Stops Appropriately(1)

`worksWell`Works Well(1)

`wouldTeachQuestionAnswering`Would Teach Question Answering(1)