Distilbert-base-uncased-becasv2-1 Open-source Model - Free Deployment to Facilitate Various Text Processing Tasks

Distilbert Base Uncased Becasv2 1

Developed by Evelyn18

A fine-tuned version of the distilbert-base-uncased model on the becasv2 dataset, primarily used for text-related tasks.

Large Language Model

Transformers

Open Source License:Apache-2.0 #Lightweight BERT #Text Classification #Efficient Fine-tuning

Downloads 16

Release Time : 7/7/2022

Model Overview

This model is a fine-tuned version of DistilBERT, suitable for text classification or other natural language processing tasks. The specific application needs further confirmation based on the nature of the becasv2 dataset.

Model Features

Lightweight BERT

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

Domain Adaptation

Fine-tuned on the becasv2 dataset, potentially possessing domain-specific adaptation capabilities.

Efficient Training

Only requires 10 training epochs to achieve good results.

Model Capabilities

Text Classification

Natural Language Understanding

Text Feature Extraction

Use Cases

Text Analysis

Text Classification

Can be used for domain-specific text classification tasks.

Validation loss 2.9472

Training Loss	Epoch	Step	Validation Loss
No log	1.0	9	4.6722
No log	2.0	18	3.9450
No log	3.0	27	3.4890
No log	4.0	36	3.2251
No log	5.0	45	2.9906
No log	6.0	54	3.0790
No log	7.0	63	2.8791
No log	8.0	72	2.9654
No log	9.0	81	2.9460
No log	10.0	90	2.9472

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Distilbert Base Uncased Becasv2 1

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 distilbert-base-uncased-becasv2-1

🚀 Quick Start

📚 Documentation

Model description

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Training and evaluation data

🔧 Technical Details

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