🧠
Vit Base Patch16 224 In21k Wwwwii model by Zynovia
⭐ 24
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Model

Vit Base Patch16 224 In21k Wwwwii

by Zynovia hf-model--zynovia--vit-base-patch16-224-in21k-wwwwii
Nexus Index
24.0 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 3
R: Recency 7
Q: Quality 50
Tech Context
21.504K Ctx
Vital Performance
27 DL / 30D
0.0%
Source →
Audited 24 FNI Score
Tiny - Params
21k Context
27 Downloads
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID hf-model--zynovia--vit-base-patch16-224-in21k-wwwwii
License Apache-2.0
Provider huggingface
📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__zynovia__vit_base_patch16_224_in21k_wwwwii,
  author = {Zynovia},
  title = {Vit Base Patch16 224 In21k Wwwwii Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/zynovia/vit-base-patch16-224-in21k-wwwwii}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
Zynovia. (2026). Vit Base Patch16 224 In21k Wwwwii [Model]. Free2AITools. https://huggingface.co/zynovia/vit-base-patch16-224-in21k-wwwwii

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download
huggingface-cli download zynovia/vit-base-patch16-224-in21k-wwwwii
đŸ“Ļ Install Lib
pip install -U transformers

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
24.0
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 3
Recency (R) 7
Quality (Q) 50

đŸ’Ŧ Index Insight

FNI V2.0 for Vit Base Patch16 224 In21k Wwwwii: Semantic (S:50), Authority (A:0), Popularity (P:3), 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

Zynovia/vit-base-patch16-224-in21k-wwwwii

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.8976
  • Train Accuracy: 0.8813
  • Train Top-3-accuracy: 0.9721
  • Validation Loss: 1.6144
  • Validation Accuracy: 0.5845
  • Validation Top-3-accuracy: 0.7845
  • Epoch: 4

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: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 6e-05, 'decay_steps': 4122, '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': 0.001}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
  • training_precision: mixed_float16

Training results

Train Loss Train Accuracy Train Top-3-accuracy Validation Loss Validation Accuracy Validation Top-3-accuracy Epoch
3.4972 0.1475 0.3067 3.0825 0.3240 0.5178 0
2.7352 0.4129 0.6613 2.4838 0.4543 0.6930 1
2.0429 0.6153 0.8315 1.9934 0.5690 0.7550 2
1.4246 0.7672 0.9166 1.6714 0.5876 0.8016 3
0.8976 0.8813 0.9721 1.6144 0.5845 0.7845 4

Framework versions

  • Transformers 4.21.2
  • TensorFlow 2.8.2
  • Datasets 2.4.0
  • 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.

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
27Downloads
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--zynovia--vit-base-patch16-224-in21k-wwwwii
slug
zynovia--vit-base-patch16-224-in21k-wwwwii
source
huggingface
author
Zynovia
license
Apache-2.0
tags
transformers, tf, tensorboard, vit, image-classification, generated_from_keras_callback, license:apache-2.0, endpoints_compatible, region:us

⚙ī¸ Technical Specs

architecture
null
params billions
null
context length
21,504
pipeline tag
image-classification

📊 Engagement & Metrics

downloads
27
stars
0
forks
0

Data indexed from public sources. Updated daily.