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Distilbert Base Uncased Finetuned Ner
D
Distilbert Base Uncased Finetuned Ner
Developed by SnailPoo
該模型是基於DistilBERT基礎版本微調的命名實體識別(NER)模型，在未知數據集上訓練，評估集F1分數達0.8545。
Downloads 15
Release Time : 4/21/2022
Model Overview
基於蒸餾版BERT架構的輕量級NER模型，適用於英文文本中的命名實體識別任務。
Model Features
輕量高效
採用蒸餾技術壓縮的BERT架構，在保持性能的同時減少計算資源需求
高準確率
在評估集上達到96.38%的準確率和0.8545的F1分數
快速訓練
僅需3輪訓練即可達到較好效果，適合快速部署
Model Capabilities
英文文本實體識別
序列標註
實體分類
Use Cases
信息提取
新聞實體提取
從新聞文本中識別人名、地名、組織名等實體
可準確標記文本中的關鍵實體信息
文檔處理
合同關鍵信息提取
自動識別合同文檔中的各方名稱、日期、金額等關鍵實體
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