🧠
Asn Ner Roberta model by theophilusowiti
⭐ 40.6
🧠
Model

Asn Ner Roberta

by theophilusowiti hf-model--theophilusowiti--asn-ner-roberta
Nexus Index
40.6 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 12
R: Recency 98
Q: Quality 65
Tech Context
Vital Performance
175 DL / 30D
0.0%
Source →
Audited 40.6 FNI Score
Tiny - Params
- Context
175 Downloads
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID hf-model--theophilusowiti--asn-ner-roberta
License MIT
Provider huggingface
📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__theophilusowiti__asn_ner_roberta,
  author = {theophilusowiti},
  title = {Asn Ner Roberta Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/theophilusowiti/asn-ner-roberta}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
theophilusowiti. (2026). Asn Ner Roberta [Model]. Free2AITools. https://huggingface.co/theophilusowiti/asn-ner-roberta

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download
huggingface-cli download theophilusowiti/asn-ner-roberta
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
40.6
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 12
Recency (R) 98
Quality (Q) 65

đŸ’Ŧ Index Insight

FNI V2.0 for Asn Ner Roberta: Semantic (S:50), Authority (A:0), Popularity (P:12), Recency (R:98), Quality (Q:65).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit
Unbiased Data Node Refresh: VFS Live
---

🚀 What's Next?

📊

Find Training Datasets

Discover datasets compatible with this model

📈

Compare Benchmarks

See how this model ranks on standard tests

⚡

Deployment Guide

Understand deployment options

Technical Deep Dive

asn-ner-roberta

This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0640

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss
0.1341 1.0 1179 0.0871
0.0884 2.0 2358 0.0695
0.0686 3.0 3537 0.0640

Framework versions

  • Transformers 5.0.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2

⚠ī¸ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source →

📝 Limitations & Considerations

  • â€ĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • â€ĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • â€ĸ FNI scores are relative rankings and may change as new models are added.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub
175Downloads
Hub Discussions
🤗 Data Source: Hugging Face ↗
🔄 Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹī¸ Verify with original source

🛡ī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--theophilusowiti--asn-ner-roberta
slug
theophilusowiti--asn-ner-roberta
source
huggingface
author
theophilusowiti
license
MIT
tags
transformers, safetensors, roberta, token-classification, generated_from_trainer, base_model:facebookai/roberta-base, base_model:finetune:facebookai/roberta-base, license:mit, endpoints_compatible, region:us

⚙ī¸ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
token-classification

📊 Engagement & Metrics

downloads
175
stars
0
forks
0

Data indexed from public sources. Updated daily.