🧠
My Awesome Model model by Mahmoud22
⭐ 24.1
🧠
Model

My Awesome Model

by Mahmoud22 hf-model--mahmoud22--my-awesome-model
Nexus Index
24.1 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 0
R: Recency 10
Q: Quality 50
Tech Context
Vital Performance
6 DL / 30D
0.0%
Source →
Audited 24.1 FNI Score
Tiny - Params
- Context
6 Downloads
Model Information Summary
Entity Passport
Registry ID hf-model--mahmoud22--my-awesome-model
Provider huggingface
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Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__mahmoud22__my_awesome_model,
  author = {Mahmoud22},
  title = {My Awesome Model Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/mahmoud22/my-awesome-model}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
Mahmoud22. (2026). My Awesome Model [Model]. Free2AITools. https://huggingface.co/mahmoud22/my-awesome-model

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download
huggingface-cli download mahmoud22/my-awesome-model
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
24.1
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 0
Recency (R) 10
Quality (Q) 50

đŸ’Ŧ Index Insight

FNI V2.0 for My Awesome Model: Semantic (S:50), Authority (A:0), Popularity (P:0), Recency (R:10), 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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Deployment Guide

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Technical Deep Dive

outputs

This model is a fine-tuned version of salti/AraElectra-base-finetuned-ARCD on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0151

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: 8e-05
  • train_batch_size: 48
  • eval_batch_size: 96
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
No log 1.0 172 0.0317
No log 2.0 344 0.0156
1.1794 3.0 516 0.0151

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.0
  • Datasets 2.1.0
  • 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.

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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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6Downloads
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--mahmoud22--my-awesome-model
slug
mahmoud22--my-awesome-model
source
huggingface
author
Mahmoud22
license
tags
transformers, pytorch, electra, fill-mask, generated_from_trainer, endpoints_compatible, region:us

⚙ī¸ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag
fill-mask

📊 Engagement & Metrics

downloads
6
stars
0
forks
0

Data indexed from public sources. Updated daily.