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Whisper Large2 Czech Cv11 V2 dataset by mikr
⭐ 26.7
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Dataset

Whisper Large2 Czech Cv11 V2

by mikr hf-model--mikr--whisper-large2-czech-cv11-v2
Nexus Index
26.7 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 0
R: Recency 100
Q: Quality 38
Tech Context
Vital Performance
0 DL / 30D
0.0%
Data Integrity 26.7 FNI Score
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Parquet Format
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Dataset Information Summary
Entity Passport
Registry ID hf-model--mikr--whisper-large2-czech-cv11-v2
Provider huggingface
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Cite this dataset

Academic & Research Attribution

BibTeX 
@misc{hf_model__mikr__whisper_large2_czech_cv11_v2,
  author = {mikr},
  title = {Whisper Large2 Czech Cv11 V2 Dataset},
  year = {2026},
  howpublished = {\url{https://free2aitools.com/dataset/hf-model--mikr--whisper-large2-czech-cv11-v2}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
mikr. (2026). Whisper Large2 Czech Cv11 V2 [Dataset]. Free2AITools. https://free2aitools.com/dataset/hf-model--mikr--whisper-large2-czech-cv11-v2

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
26.7
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 0
Recency (R) 100
Quality (Q) 38

đŸ’Ŧ Index Insight

FNI V2.0 for Whisper Large2 Czech Cv11 V2: Semantic (S:50), Authority (A:0), Popularity (P:0), Recency (R:100), Quality (Q:38).

Free2AITools Nexus Index

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Dataset Specification

Whisper Large-v2 Czech CV11 v2

This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0 cs dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2120
  • Wer: 9.0459

Model description

Fine tuned with deepspeed optimization and batch_size: 32.

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: 32
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000

Training results

Training Loss Epoch Step Validation Loss Wer
0.0106 4.24 1000 0.1625 9.9888
0.0034 8.47 2000 0.1841 9.8304
0.0011 12.71 3000 0.1917 9.4031
0.0004 16.95 4000 0.2075 9.1177
0.0003 21.19 5000 0.2120 9.0459

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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Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--mikr--whisper-large2-czech-cv11-v2
slug
mikr--whisper-large2-czech-cv11-v2
source
huggingface
author
mikr
license
tags

⚙ī¸ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag

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