Model: ubffm/academic_text_classifier_en
Author: ubffm
Pipeline: text-classification
Library: transformers
Tags: transformers, tensorboard, safetensors, xlm-roberta, text-classification, generated_from_trainer, en, base_model:FacebookAI/xlm-roberta-base, base_model:finetune:FacebookAI/xlm-roberta-base, license:mit, endpoints_compatible, region:us
Base models (finetune): id: FacebookAI/xlm-roberta-base
Card metadata: library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags: generated_from_trainer
language: en
metrics: accuracy, precision, recall, f1
model-index: name: academic_main_text_classifier_en
widget: In the case of (ioii) and (1 lii), the passive transformation will apply to the embedded sentence, and in all four cases other operations will give the final surface forms of (8) and (g)., (10) (i) Noun Phrase — Verb — Noun Phrase — Sentence (/ — persuaded — a specialist — a specialist will examine John) (ii) Noun Phrase — Verb — Noun Phrase — Sentence (/ — persuaded — John — a specialist will examine John), 184 SOME RESIDUAL PROBLEMS, Peshkovskii, A. M. (1956). Russkii Sintaksis v Nauchnom Osveshchenii. Moscow., S -» NP^Aux^VP, (sincerity, [+N, —Count, +Abstract]) (boy, [+N, —Count, +Common, +Animate, +Human]) (may, [+M])
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Created: 2025-10-22 12:33:20