/ Модель

Характеристики

Контекст
256 токенов
Архитектура
gpt2 · dense
Библиотека
transformers
Опубликована
7 мар 2025

babylm-subwords-2-gpt2_lm-model

Генерация текстаТекст → текст3 профессии

Дообученная GPT-2 для генерации текста и экспериментов с подсловным языковым моделированием в BabyLM.

133скачиваний за 30 дней0лайковвеса обновлены8 мар 2025

Бенчмарки

Как модель справилась с задачами пользователей ailist и что о ней публикуют открытые лидерборды

Тесты пользователейпока нет

Никто ещё не опубликовал тест этой модели. Соберите бенчмарк из своих задач — результат появится здесь.

  1. Добавьте модель в бенчмарк

    Вместе с другими моделями категории «Текст» — сравнение идёт внутри одной категории.

  2. Опишите свои задачи

    Напишите запросы, при необходимости приложите файлы и эталонные ответы.

  3. Запустите и опубликуйте

    Модели ответят на каждую задачу, судья оценит ответы. Опубликованный результат появится на этой странице.

Публичные оценки

Из открытых лидербордов. Сравнивайте результаты одного теста при одинаковых условиях — отсутствие оценки не значит, что модель хуже.

В подключённых источниках результатов для этой модели пока нет.

Что умеет модель

Описание составлено по карточке модели и метаданным Hugging Face

Это дообученная модель генерации текста на архитектуре GPT-2, предназначенная для экспериментов с языковым моделированием на подсловных единицах в рамках проекта BabyLM. Карточка приводит метрики оценки BabyLM и BLiMP, включая loss, perplexity, лексические и синтаксические показатели; результаты различаются по тестам и отдельным языковым явлениям.

Модель принимает текст и генерирует продолжение. В метаданных указан контекст длиной 256 токенов и формат весов safetensors. README не называет исходную модель, обучающий набор данных или лицензию, поэтому их нельзя установить по доступным сведениям.

Сценарии применения

  • генерация продолжения короткого текста
  • эксперименты с языковым моделированием на подсловах
  • оценка языковой модели на лексических и синтаксических тестах

Ограничения

Контекст ограничен 256 токенами; результаты на отдельных синтаксических тестах заметно различаются. README не сообщает лицензию и подробности обучающих данных.

Для каких профессий подходит3

Разделы каталога профессий, в задачах которых используется эта модель

Все профессии

Карточка модели

README от автора на Hugging Face, как он его опубликовал

Открыть на Hugging Face

babylm-subwords-2-gpt2_lm-model

This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 3.6434
  • Model Preparation Time: 0.0024
  • Perplexity: 38.2216
  • Bpc: 5.2563
  • Babyslm Test Lexical: 0.7310
  • Babyslm Test Syntactic: 0.7454
  • Blimp Supplement: 0.5693
  • Blimp Filtered: 0.7115
  • Blimp Supplement Hypernym: 0.5012
  • Blimp Supplement Qa Congruence Easy: 0.6406
  • Blimp Supplement Qa Congruence Tricky: 0.2667
  • Blimp Supplement Subject Aux Inversion: 0.7631
  • Blimp Supplement Turn Taking: 0.675
  • Blimp Adjunct Island Filtered: 0.7134
  • Blimp Anaphor Gender Agreement Filtered: 0.9248
  • Blimp Anaphor Number Agreement Filtered: 0.9506
  • Blimp Animate Subject Passive Filtered: 0.7419
  • Blimp Animate Subject Trans Filtered: 0.8678
  • Blimp Causative Filtered: 0.6932
  • Blimp Complex Np Island Filtered: 0.4444
  • Blimp Coordinate Structure Constraint Complex Left Branch Filtered: 0.4205
  • Blimp Coordinate Structure Constraint Object Extraction Filtered: 0.6133
  • Blimp Determiner Noun Agreement 1 Filtered: 0.9763
  • Blimp Determiner Noun Agreement 2 Filtered: 0.9409
  • Blimp Determiner Noun Agreement Irregular 1 Filtered: 0.8972
  • Blimp Determiner Noun Agreement Irregular 2 Filtered: 0.8890
  • Blimp Determiner Noun Agreement With Adj 2 Filtered: 0.9001
  • Blimp Determiner Noun Agreement With Adj Irregular 1 Filtered: 0.8524
  • Blimp Determiner Noun Agreement With Adj Irregular 2 Filtered: 0.8298
  • Blimp Determiner Noun Agreement With Adjective 1 Filtered: 0.9539
  • Blimp Distractor Agreement Relational Noun Filtered: 0.6294
  • Blimp Distractor Agreement Relative Clause Filtered: 0.5465
  • Blimp Drop Argument Filtered: 0.7043
  • Blimp Ellipsis N Bar 1 Filtered: 0.6185
  • Blimp Ellipsis N Bar 2 Filtered: 0.8261
  • Blimp Existential There Object Raising Filtered: 0.6798
  • Blimp Existential There Quantifiers 1 Filtered: 0.9548
  • Blimp Existential There Quantifiers 2 Filtered: 0.4061
  • Blimp Existential There Subject Raising Filtered: 0.8333
  • Blimp Expletive It Object Raising Filtered: 0.7628
  • Blimp Inchoative Filtered: 0.5860
  • Blimp Intransitive Filtered: 0.7339
  • Blimp Irregular Past Participle Adjectives Filtered: 0.6681
  • Blimp Irregular Past Participle Verbs Filtered: 0.7495
  • Blimp Irregular Plural Subject Verb Agreement 1 Filtered: 0.8433
  • Blimp Irregular Plural Subject Verb Agreement 2 Filtered: 0.8430
  • Blimp Left Branch Island Echo Question Filtered: 0.5977
  • Blimp Left Branch Island Simple Question Filtered: 0.5184
  • Blimp Matrix Question Npi Licensor Present Filtered: 0.2831
  • Blimp Npi Present 1 Filtered: 0.4345
  • Blimp Npi Present 2 Filtered: 0.5317
  • Blimp Only Npi Licensor Present Filtered: 0.7812
  • Blimp Only Npi Scope Filtered: 0.6452
  • Blimp Passive 1 Filtered: 0.8690
  • Blimp Passive 2 Filtered: 0.8339
  • Blimp Principle A C Command Filtered: 0.6279
  • Blimp Principle A Case 1 Filtered: 0.9978
  • Blimp Principle A Case 2 Filtered: 0.8678
  • Blimp Principle A Domain 1 Filtered: 0.9650
  • Blimp Principle A Domain 2 Filtered: 0.6066
  • Blimp Principle A Domain 3 Filtered: 0.5643
  • Blimp Principle A Reconstruction Filtered: 0.3630
  • Blimp Regular Plural Subject Verb Agreement 1 Filtered: 0.8337
  • Blimp Regular Plural Subject Verb Agreement 2 Filtered: 0.8508
  • Blimp Sentential Negation Npi Licensor Present Filtered: 0.9456
  • Blimp Sentential Negation Npi Scope Filtered: 0.4455
  • Blimp Sentential Subject Island Filtered: 0.4485
  • Blimp Superlative Quantifiers 1 Filtered: 0.6313
  • Blimp Superlative Quantifiers 2 Filtered: 0.7373
  • Blimp Tough Vs Raising 1 Filtered: 0.3956
  • Blimp Tough Vs Raising 2 Filtered: 0.7478
  • Blimp Transitive Filtered: 0.7039
  • Blimp Wh Island Filtered: 0.7042
  • Blimp Wh Questions Object Gap Filtered: 0.7055
  • Blimp Wh Questions Subject Gap Filtered: 0.8842
  • Blimp Wh Questions Subject Gap Long Distance Filtered: 0.9090
  • Blimp Wh Vs That No Gap Filtered: 0.9477
  • Blimp Wh Vs That No Gap Long Distance Filtered: 0.9566
  • Blimp Wh Vs That With Gap Filtered: 0.2622
  • Blimp Wh Vs That With Gap Long Distance Filtered: 0.0758

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.001
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 90000
  • training_steps: 400000

Training results

Training LossEpochStepValidation LossModel Preparation TimePerplexityBpcBabyslm Test LexicalBabyslm Test SyntacticBlimp SupplementBlimp FilteredBlimp Supplement HypernymBlimp Supplement Qa Congruence EasyBlimp Supplement Qa Congruence TrickyBlimp Supplement Subject Aux InversionBlimp Supplement Turn TakingBlimp Adjunct Island FilteredBlimp Anaphor Gender Agreement FilteredBlimp Anaphor Number Agreement FilteredBlimp Animate Subject Passive FilteredBlimp Animate Subject Trans FilteredBlimp Causative FilteredBlimp Complex Np Island FilteredBlimp Coordinate Structure Constraint Complex Left Branch FilteredBlimp Coordinate Structure Constraint Object Extraction FilteredBlimp Determiner Noun Agreement 1 FilteredBlimp Determiner Noun Agreement 2 FilteredBlimp Determiner Noun Agreement Irregular 1 FilteredBlimp Determiner Noun Agreement Irregular 2 FilteredBlimp Determiner Noun Agreement With Adj 2 FilteredBlimp Determiner Noun Agreement With Adj Irregular 1 FilteredBlimp Determiner Noun Agreement With Adj Irregular 2 FilteredBlimp Determiner Noun Agreement With Adjective 1 FilteredBlimp Distractor Agreement Relational Noun FilteredBlimp Distractor Agreement Relative Clause FilteredBlimp Drop Argument FilteredBlimp Ellipsis N Bar 1 FilteredBlimp Ellipsis N Bar 2 FilteredBlimp Existential There Object Raising FilteredBlimp Existential There Quantifiers 1 FilteredBlimp Existential There Quantifiers 2 FilteredBlimp Existential There Subject Raising FilteredBlimp Expletive It Object Raising FilteredBlimp Inchoative FilteredBlimp Intransitive FilteredBlimp Irregular Past Participle Adjectives FilteredBlimp Irregular Past Participle Verbs FilteredBlimp Irregular Plural Subject Verb Agreement 1 FilteredBlimp Irregular Plural Subject Verb Agreement 2 FilteredBlimp Left Branch Island Echo Question FilteredBlimp Left Branch Island Simple Question FilteredBlimp Matrix Question Npi Licensor Present FilteredBlimp Npi Present 1 FilteredBlimp Npi Present 2 FilteredBlimp Only Npi Licensor Present FilteredBlimp Only Npi Scope FilteredBlimp Passive 1 FilteredBlimp Passive 2 FilteredBlimp Principle A C Command FilteredBlimp Principle A Case 1 FilteredBlimp Principle A Case 2 FilteredBlimp Principle A Domain 1 FilteredBlimp Principle A Domain 2 FilteredBlimp Principle A Domain 3 FilteredBlimp Principle A Reconstruction FilteredBlimp Regular Plural Subject Verb Agreement 1 FilteredBlimp Regular Plural Subject Verb Agreement 2 FilteredBlimp Sentential Negation Npi Licensor Present FilteredBlimp Sentential Negation Npi Scope FilteredBlimp Sentential Subject Island FilteredBlimp Superlative Quantifiers 1 FilteredBlimp Superlative Quantifiers 2 FilteredBlimp Tough Vs Raising 1 FilteredBlimp Tough Vs Raising 2 FilteredBlimp Transitive FilteredBlimp Wh Island FilteredBlimp Wh Questions Object Gap FilteredBlimp Wh Questions Subject Gap FilteredBlimp Wh Questions Subject Gap Long Distance FilteredBlimp Wh Vs That No Gap FilteredBlimp Wh Vs That No Gap Long Distance FilteredBlimp Wh Vs That With Gap FilteredBlimp Wh Vs That With Gap Long Distance Filtered
3.53611.4408500004.03040.002456.28395.81470.70550.70740.57600.64540.53210.57810.36970.78560.61430.65410.85580.89260.69160.85370.55500.39480.31900.40990.94080.89470.74740.86590.82150.78270.77740.87780.35280.36510.69780.55860.79110.76350.92580.27770.81710.72730.49820.63710.56920.74840.74880.82400.60820.40060.17550.44440.46500.48750.43250.80120.82170.55070.99340.64810.97700.51040.52710.35370.77530.77880.94450.37080.41210.61490.64400.30490.76520.63130.59580.60070.87860.94750.92680.93940.18060.0934
3.33912.88161000003.85770.002447.35435.56540.72030.74930.55900.67760.50.54690.29700.79420.65710.63790.89080.95060.69270.86570.67850.40780.32010.50790.97310.88400.79880.87800.86400.80920.81070.92930.54060.42370.69130.58230.82250.74750.96670.36330.82680.74440.53570.67510.68470.74520.79980.82060.50160.37750.20780.44330.54600.67010.63680.78690.79180.60891.00.82620.99120.55190.52280.35570.82250.83490.92820.38350.41210.63740.74440.29850.78700.65090.57400.62170.87080.93230.88850.93370.27420.1165
3.17454.32241500003.75340.002442.66485.41500.72170.74570.57460.69360.52380.60940.25450.80320.68210.69720.92170.94840.70500.88520.64430.41130.33550.52580.97420.91510.82670.88900.86400.83010.83570.94530.58380.43630.72170.62720.84060.72170.96130.35680.85500.75230.55440.70160.68680.74100.80470.83630.60300.39010.25510.38390.50220.78460.63080.84400.82170.56551.00.84810.96610.58140.56750.36190.83600.83920.94890.38690.41830.65580.77480.36710.73480.69930.69900.65660.89200.93120.91990.95310.22630.0890
3.10325.76322000003.70400.002440.60955.34370.72730.74030.56920.70060.50120.60940.27270.76650.69640.68530.90220.96460.71170.87540.65650.41610.39510.54690.97740.92480.85900.88410.87350.84540.82620.94320.56850.48790.72830.59850.82730.74630.96990.47200.85390.76020.54970.72930.65040.74310.82340.85760.56810.48370.25620.42790.51970.80730.65230.85480.80290.61730.99890.81750.97260.61200.54840.33300.83820.85610.95650.45920.43500.57810.70180.33970.75980.69010.68230.67400.88080.93120.92920.95540.26880.0802
3.00317.20402500003.67890.002439.60215.30750.72660.74030.56950.70190.49640.59380.28480.77610.69640.69500.90730.94630.70170.86350.67480.43500.36200.59750.97420.93560.85320.88660.90220.82870.82260.94000.59770.51890.71090.63090.82970.71670.96990.37650.84630.77470.57540.72120.68470.77280.82460.82620.60510.46060.29060.45210.50880.79710.64870.86070.82170.63000.99780.85570.95950.60220.54730.35880.84270.84230.94340.39040.43290.54340.72410.36290.76200.70850.66150.66940.86860.90780.92800.9520.29710.0912
2.97068.64483000003.65880.002438.81645.27860.72790.74360.57460.70620.49520.6250.28480.77140.69640.71230.90940.95600.72400.87220.69560.43500.35980.61010.98060.93450.88550.89630.90010.84260.81190.94110.62310.54650.71410.60220.82610.73770.94840.41270.83770.76420.58360.72810.70760.73350.83580.83300.57760.48580.27660.44220.52840.77780.60690.87380.83060.61100.99780.83720.96940.61420.56960.32260.84380.84230.94450.43970.39960.64040.75250.34490.77930.71660.69060.67990.88750.90430.93610.95430.25240.0835
2.91710.08563500003.65320.002438.59785.27040.73150.74470.56080.70980.48930.59380.26060.77110.68930.72310.91760.94840.74640.87540.69800.44330.41940.59960.97630.93230.88400.89510.89160.85380.83210.95500.63830.53160.70110.60600.82970.68600.95810.40500.84310.75490.57430.71540.68160.75800.84950.85430.60610.53420.28850.40040.50980.77660.66070.86430.83720.61421.00.85900.97160.59450.55470.35680.84490.85930.93360.42590.44220.61700.71810.39350.75220.70280.68650.71830.89980.92420.93840.960.26550.0681
2.866811.52644000003.64340.002438.22165.25630.73100.74540.56930.71150.50120.64060.26670.76310.6750.71340.92480.95060.74190.86780.69320.44440.42050.61330.97630.94090.89720.88900.90010.85240.82980.95390.62940.54650.70430.61850.82610.67980.95480.40610.83330.76280.58600.73390.66810.74950.84330.84300.59770.51840.28310.43450.53170.78120.64520.86900.83390.62790.99780.86780.96500.60660.56430.36300.83370.85080.94560.44550.44850.63130.73730.39560.74780.70390.70420.70550.88420.90900.94770.95660.26220.0758

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu118
  • Datasets 2.18.0
  • Tokenizers 0.19.1

Как запустить

На своей GPU в ailist. Цена — по текущим предложениям провайдеров

GPU в ailist

Универсальный рантайм · transformers

Можно запустить

Подбираем GPU…

Класс архитектуры
GPT2LMHeadModel
Ревизия весов
f5da489

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