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Whisper Small Ar dataset by arbml
⭐ 25.6
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Dataset

Whisper Small Ar

by arbml hf-model--arbml--whisper-small-ar
Nexus Index
25.6 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 0
R: Recency 100
Q: Quality 23
Tech Context
Vital Performance
0 DL / 30D
0.0%
Data Integrity 25.6 FNI Score
- Size
- Rows
Parquet Format
- Tokens
Dataset Information Summary
Entity Passport
Registry ID hf-model--arbml--whisper-small-ar
Provider huggingface
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Cite this dataset

Academic & Research Attribution

BibTeX 
@misc{hf_model__arbml__whisper_small_ar,
  author = {arbml},
  title = {Whisper Small Ar Dataset},
  year = {2026},
  howpublished = {\url{https://free2aitools.com/dataset/hf-model--arbml--whisper-small-ar}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
arbml. (2026). Whisper Small Ar [Dataset]. Free2AITools. https://free2aitools.com/dataset/hf-model--arbml--whisper-small-ar

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
25.6
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 0
Recency (R) 100
Quality (Q) 23

đŸ’Ŧ Index Insight

FNI V2.0 for Whisper Small Ar: Semantic (S:50), Authority (A:0), Popularity (P:0), Recency (R:100), Quality (Q:23).

Free2AITools Nexus Index

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HuggingFace API GitHub Metadata Arxiv Citation DB System Audit
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Schema structure is shown in the Field Logic panel when available.

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Dataset Specification

openai/whisper-small

This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9750
  • Wer: 21.3693

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: 1e-05
  • train_batch_size: 64
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3559 0.1 1000 0.9147 29.3252
0.3154 0.2 2000 1.1353 26.5718
0.359 0.3 3000 0.9208 25.3987
0.273 0.4 4000 0.9591 24.3877
0.2326 0.5 5000 0.9207 21.9052
0.2992 1.04 6000 0.9445 22.4556
0.2265 1.14 7000 0.9660 21.2230
0.2059 1.24 8000 0.9785 20.9551
0.2239 1.34 9000 0.9637 21.6300
0.2163 1.44 10000 0.9750 21.3693

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2
🤗 Data Source: Hugging Face ↗
🔄 Daily sync (03:00 UTC)

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

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🛡ī¸ Dataset Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--arbml--whisper-small-ar
slug
arbml--whisper-small-ar
source
huggingface
author
arbml
license
tags

⚙ī¸ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag

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