🧠
Roberta Base Finetuned Squad model by amitjohn007
⭐ 23.8
🧠
Model

Roberta Base Finetuned Squad

by amitjohn007 hf-model--amitjohn007--roberta-base-finetuned-squad
Nexus Index
23.8 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 1
R: Recency 8
Q: Quality 50
Tech Context
Vital Performance
6 DL / 30D
0.0%
Source →
Audited 23.8 FNI Score
Tiny - Params
- Context
6 Downloads
Restricted CC License
Model Information Summary
Entity Passport
Registry ID hf-model--amitjohn007--roberta-base-finetuned-squad
License CC-BY-4.0
Provider huggingface
📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__amitjohn007__roberta_base_finetuned_squad,
  author = {amitjohn007},
  title = {Roberta Base Finetuned Squad Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/amitjohn007/roberta-base-finetuned-squad}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
amitjohn007. (2026). Roberta Base Finetuned Squad [Model]. Free2AITools. https://huggingface.co/amitjohn007/roberta-base-finetuned-squad

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download
huggingface-cli download amitjohn007/roberta-base-finetuned-squad
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
23.8
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 1
Recency (R) 8
Quality (Q) 50

đŸ’Ŧ Index Insight

FNI V2.0 for Roberta Base Finetuned Squad: Semantic (S:50), Authority (A:0), Popularity (P:1), Recency (R:8), Quality (Q:50).

Free2AITools Nexus Index

Verification Authority

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

amitjohn007/roberta-base-finetuned-squad

This model is a fine-tuned version of deepset/roberta-base-squad2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.4173
  • Epoch: 2

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:

  • optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 16608, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
  • training_precision: mixed_float16

Training results

Train Loss Epoch
0.7396 0
0.5461 1
0.4173 2

Framework versions

  • Transformers 4.24.0
  • TensorFlow 2.9.2
  • Datasets 2.6.1
  • Tokenizers 0.13.2

⚠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
6Downloads
Hub Discussions
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AI Summary: Based on Hugging Face metadata. Not a recommendation.

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🛡ī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--amitjohn007--roberta-base-finetuned-squad
slug
amitjohn007--roberta-base-finetuned-squad
source
huggingface
author
amitjohn007
license
CC-BY-4.0
tags
transformers, tf, roberta, question-answering, generated_from_keras_callback, license:cc-by-4.0, endpoints_compatible, region:us

⚙ī¸ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
question-answering

📊 Engagement & Metrics

downloads
6
stars
0
forks
0

Data indexed from public sources. Updated daily.