model_ner_master Open-source Model - Finetuned based on ModernBERT-base, effectively achieving precise named entity recognition

Model Ner Master

Developed by luisgasco

Model fine-tuned based on ModernBERT-base, achieving an F1 score of 0.3833 on the evaluation set

Downloads 35

Release Time : 5/13/2025

Model Overview

This model is a text processing model fine-tuned on the ModernBERT-base architecture, suitable for natural language processing tasks

ModernBERT-base fine-tuning

Fine-tuned based on the modern optimized BERT architecture

Lightweight training

Trained for only 2 epochs with a batch size of 16

Linear learning rate scheduling

Uses a linear learning rate scheduling strategy to optimize the training process

Text classification

Natural language understanding

Text analysis

Sentiment analysis

Can be used to analyze text sentiment tendencies

F1 score 0.3833 (on a specific dataset)

Training Loss	Epoch	Step	Validation Loss	F1
0.4165	0.1667	50	0.3038	0.0014
0.3627	0.3333	100	0.2643	0.0043
0.2776	0.5	150	0.2914	0.0146
0.229	0.6667	200	0.1869	0.1883
0.1945	0.8333	250	0.1671	0.2568
0.1574	1.0	300	0.1592	0.3238
0.1056	1.1667	350	0.1710	0.4048
0.1117	1.3333	400	0.1657	0.3649
0.117	1.5	450	0.1692	0.3792
0.1176	1.6667	500	0.1604	0.3802
0.0972	1.8333	550	0.1705	0.3515
0.1086	2.0	600	0.1590	0.3833

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