🧠
Tiny Mlm Rotten Tomatoes Custom Tokenizer model by muhtasham
⭐ 24
🧠
Model

Tiny Mlm Rotten Tomatoes Custom Tokenizer

by muhtasham hf-model--muhtasham--tiny-mlm-rotten_tomatoes-custom-tokenizer
Nexus Index
24.0 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 1
R: Recency 9
Q: Quality 50
Tech Context
Vital Performance
7 DL / 30D
0.0%
Source →
Audited 24 FNI Score
Tiny - Params
- Context
7 Downloads
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID hf-model--muhtasham--tiny-mlm-rotten_tomatoes-custom-tokenizer
License Apache-2.0
Provider huggingface
📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__muhtasham__tiny_mlm_rotten_tomatoes_custom_tokenizer,
  author = {muhtasham},
  title = {Tiny Mlm Rotten Tomatoes Custom Tokenizer Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/muhtasham/tiny-mlm-rotten_tomatoes-custom-tokenizer}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
muhtasham. (2026). Tiny Mlm Rotten Tomatoes Custom Tokenizer [Model]. Free2AITools. https://huggingface.co/muhtasham/tiny-mlm-rotten_tomatoes-custom-tokenizer

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

🤗 HF Download
huggingface-cli download muhtasham/tiny-mlm-rotten_tomatoes-custom-tokenizer
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) 1
Recency (R) 9
Quality (Q) 50

đŸ’Ŧ Index Insight

FNI V2.0 for Tiny Mlm Rotten Tomatoes Custom Tokenizer: Semantic (S:50), Authority (A:0), Popularity (P:1), Recency (R:9), Quality (Q:50).

Free2AITools Nexus Index

Verification Authority

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Technical Deep Dive

tiny-mlm-rotten_tomatoes-custom-tokenizer

This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 7.5806

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: 3e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant
  • num_epochs: 200

Training results

Training Loss Epoch Step Validation Loss
8.3064 0.47 500 7.6122
7.4122 0.94 1000 7.5410
7.153 1.41 1500 7.4469
7.1952 1.87 2000 7.6796
7.0818 2.34 2500 7.5542
7.0123 2.81 3000 7.5806

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu116
  • Datasets 2.8.1.dev0
  • 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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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--muhtasham--tiny-mlm-rotten_tomatoes-custom-tokenizer
slug
muhtasham--tiny-mlm-rotten_tomatoes-custom-tokenizer
source
huggingface
author
muhtasham
license
Apache-2.0
tags
transformers, pytorch, bert, fill-mask, generated_from_trainer, license:apache-2.0, endpoints_compatible, region:us

⚙ī¸ Technical Specs

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

📊 Engagement & Metrics

downloads
7
stars
0
forks
0

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