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Bert Base Uncased Scouting

Developed by amanm27
This model is a fine-tuned version based on bert-base-uncased. Specific application scenarios and training dataset information are not provided.
Downloads 39
Release Time : 3/10/2022

Model Overview

A fine-tuned model based on bert-base-uncased, suitable for natural language processing tasks. Specific uses require further information confirmation.

Model Features

BERT Base Architecture
Based on the widely used bert-base-uncased model, with strong language understanding capabilities
Fine-tuning Optimization
Fine-tuned for 3 epochs on a specific dataset, validation loss decreased from 1.7727 to 1.5572
Standard Training Configuration
Trained using the Adam optimizer and linear learning rate scheduler

Model Capabilities

Text understanding
Text feature extraction
Natural language processing

Use Cases

Natural Language Processing
Text Classification
Can be used for text classification tasks
Question Answering Systems
Potentially suitable for question answering system development
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