🧠
testarbara model by kevinbram
⭐ 23.7
🧠
Model

testarbara

by kevinbram hf-model--kevinbram--testarbara
Nexus Index
23.7 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 1
R: Recency 7
Q: Quality 50
Tech Context
Vital Performance
4 DL / 30D
0.0%
Source →
Audited 23.7 FNI Score
Tiny - Params
- Context
4 Downloads
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID hf-model--kevinbram--testarbara
License Apache-2.0
Provider huggingface
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Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__kevinbram__testarbara,
  author = {kevinbram},
  title = {testarbara Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/kevinbram/testarbara}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
kevinbram. (2026). testarbara [Model]. Free2AITools. https://huggingface.co/kevinbram/testarbara

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download
huggingface-cli download kevinbram/testarbara
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
23.7
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 1
Recency (R) 7
Quality (Q) 50

đŸ’Ŧ Index Insight

FNI V2.0 for testarbara: Semantic (S:50), Authority (A:0), Popularity (P:1), Recency (R:7), 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

kevinbram/testarbara

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 1.4900
  • Train End Logits Accuracy: 0.6129
  • Train Start Logits Accuracy: 0.5735
  • Validation Loss: 1.1335
  • Validation End Logits Accuracy: 0.6908
  • Validation Start Logits Accuracy: 0.6545
  • Epoch: 0

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': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 11064, '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}
  • training_precision: float32

Training results

Train Loss Train End Logits Accuracy Train Start Logits Accuracy Validation Loss Validation End Logits Accuracy Validation Start Logits Accuracy Epoch
1.4900 0.6129 0.5735 1.1335 0.6908 0.6545 0

Framework versions

  • Transformers 4.20.1
  • TensorFlow 2.6.4
  • Datasets 2.1.0
  • Tokenizers 0.12.1

⚠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.

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📝 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

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4Downloads
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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--kevinbram--testarbara
slug
kevinbram--testarbara
source
huggingface
author
kevinbram
license
Apache-2.0
tags
transformers, tf, tensorboard, distilbert, question-answering, generated_from_keras_callback, license:apache-2.0, endpoints_compatible, region:us

⚙ī¸ Technical Specs

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

📊 Engagement & Metrics

downloads
4
stars
0
forks
0

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