distilbert-base-uncased-becas-4 Open Source Text Classification Model - Accurately Implement Text Classification Tasks

Distilbert Base Uncased Becas 4

Developed by Evelyn18

A text classification model fine-tuned on the becasv2 dataset based on distilbert-base-uncased

Downloads 20

Release Time : 7/1/2022

Model Overview

This model is a lightweight version of DistilBERT, fine-tuned on the becasv2 dataset, suitable for text classification tasks.

Lightweight Architecture

Based on the DistilBERT architecture, it is more lightweight than standard BERT models while maintaining good performance.

Domain Fine-tuning

Specially fine-tuned on the becasv2 dataset, suitable for text classification tasks in specific domains.

Text Classification

Natural Language Understanding

Text Analysis

Domain-specific Text Classification

Classify texts in domains related to the becasv2 dataset

Achieved a loss value of 3.1357 on the evaluation set

Training Loss	Epoch	Step	Validation Loss
No log	1.0	9	4.9618
No log	2.0	18	4.1071
No log	3.0	27	3.5438
No log	4.0	36	3.2115
No log	5.0	45	2.9524
No log	6.0	54	3.0645
No log	7.0	63	2.9351
No log	8.0	72	3.1037
No log	9.0	81	3.1132
No log	10.0	90	3.1357

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