distilbert-base-uncased-finetuned-cola Open-Source Text Classification Model - Free to Judge the Grammatical Correctness of English Sentences

Distilbert Base Uncased Finetuned Cola

Developed by hchc

This model is a text classification model fine-tuned on the GLUE CoLA task based on the DistilBERT base model, used to determine the grammatical correctness of English sentences.

Text Classification

Transformers

Open Source License:Apache-2.0 #Grammar correctness detection #Text classification #Lightweight BERT

Downloads 17

Release Time : 3/2/2022

Model Overview

This is a fine-tuned DistilBERT model specifically designed for grammatical acceptability classification tasks (CoLA), capable of judging whether English sentences conform to grammatical rules.

Model Features

Efficient and lightweight

Based on the DistilBERT architecture, it is smaller and faster than standard BERT models while maintaining good performance.

Grammar judgment

Specifically optimized for grammatical acceptability classification tasks.

Good performance

Achieves a Matthews correlation coefficient of 0.545 on the CoLA task.

Model Capabilities

English grammar judgment

Text classification

Natural language understanding

Use Cases

Educational technology

Grammar checking

Used in English learning applications to automatically detect grammatical errors in student writing.

Can accurately identify sentences that do not conform to grammar.

Content moderation

Content quality filtering

Filtering low-quality content with poor grammar on social media platforms.

Improves the overall quality of platform content.

Training Loss	Epoch	Step	Validation Loss	Matthews Correlation
0.5221	1.0	535	0.5370	0.4246
0.3462	2.0	1070	0.5157	0.5183
0.2332	3.0	1605	0.6324	0.5166
0.1661	4.0	2140	0.7616	0.5370
0.1263	5.0	2675	0.8508	0.5452

Property	Details
Model Type	distilbert-base-uncased-finetuned-cola
Training Data	glue
Metrics	matthews_correlation
Evaluation Results	Loss: 0.8508, Matthews Correlation: 0.5452

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Distilbert Base Uncased Finetuned Cola

Model Overview

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