🧠
Vit Base Patch16 224 In21k Wwwwii model by Imene
⭐ 23.8
🧠
Model

Vit Base Patch16 224 In21k Wwwwii

by Imene hf-model--imene--vit-base-patch16-224-in21k-wwwwii
Nexus Index
23.8 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 2
R: Recency 7
Q: Quality 50
Tech Context
21.504K Ctx
Vital Performance
13 DL / 30D
0.0%
Source →
Audited 23.8 FNI Score
Tiny - Params
21k Context
13 Downloads
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID hf-model--imene--vit-base-patch16-224-in21k-wwwwii
License Apache-2.0
Provider huggingface
📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__imene__vit_base_patch16_224_in21k_wwwwii,
  author = {Imene},
  title = {Vit Base Patch16 224 In21k Wwwwii Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/imene/vit-base-patch16-224-in21k-wwwwii}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
Imene. (2026). Vit Base Patch16 224 In21k Wwwwii [Model]. Free2AITools. https://huggingface.co/imene/vit-base-patch16-224-in21k-wwwwii

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

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

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
23.8
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 2
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:2), Recency (R:7), Quality (Q:50).

Free2AITools Nexus Index

Verification Authority

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Technical Deep Dive

Imene/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: 0.8024
  • Train Accuracy: 0.9939
  • Train Top-3-accuracy: 0.9997
  • Validation Loss: 1.6739
  • Validation Accuracy: 0.6267
  • Validation Top-3-accuracy: 0.8349
  • Epoch: 9

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': 4e-05, 'decay_steps': 1620, '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
3.6793 0.125 0.2805 3.4078 0.2151 0.4756 0
3.1763 0.3448 0.6265 3.0167 0.4209 0.6640 1
2.7546 0.5419 0.7852 2.6634 0.5326 0.7651 2
2.3537 0.6855 0.8843 2.3971 0.5547 0.7860 3
1.9989 0.7814 0.9279 2.2236 0.5837 0.7907 4
1.6670 0.875 0.9698 2.0757 0.5977 0.7907 5
1.3815 0.9352 0.9890 1.8921 0.6198 0.8174 6
1.1407 0.9651 0.9956 1.7976 0.6244 0.8174 7
0.9451 0.9866 0.9983 1.7227 0.6349 0.8267 8
0.8024 0.9939 0.9997 1.6739 0.6267 0.8349 9

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.

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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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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--imene--vit-base-patch16-224-in21k-wwwwii
slug
imene--vit-base-patch16-224-in21k-wwwwii
source
huggingface
author
Imene
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
13
stars
0
forks
0

Data indexed from public sources. Updated daily.