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T5 Small Finetuned Cnn V2 dataset by ubikpt
⭐ 25.6
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Dataset

T5 Small Finetuned Cnn V2

by ubikpt hf-model--ubikpt--t5-small-finetuned-cnn-v2
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
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- Rows
Parquet Format
- Tokens
Dataset Information Summary
Entity Passport
Registry ID hf-model--ubikpt--t5-small-finetuned-cnn-v2
Provider huggingface
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Cite this dataset

Academic & Research Attribution

BibTeX 
@misc{hf_model__ubikpt__t5_small_finetuned_cnn_v2,
  author = {ubikpt},
  title = {T5 Small Finetuned Cnn V2 Dataset},
  year = {2026},
  howpublished = {\url{https://free2aitools.com/dataset/hf-model--ubikpt--t5-small-finetuned-cnn-v2}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
ubikpt. (2026). T5 Small Finetuned Cnn V2 [Dataset]. Free2AITools. https://free2aitools.com/dataset/hf-model--ubikpt--t5-small-finetuned-cnn-v2

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 T5 Small Finetuned Cnn V2: 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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Dataset Specification

t5-small-finetuned-cnn-v2

This model is a fine-tuned version of t5-small on the cnn_dailymail dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5474
  • Rouge1: 35.154
  • Rouge2: 18.683
  • Rougel: 30.8481
  • Rougelsum: 32.9638

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: 5.6e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 8

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
1.8823 1.0 35890 1.5878 34.9676 18.4927 30.6753 32.7702
1.7871 2.0 71780 1.5709 34.9205 18.5556 30.6514 32.745
1.7507 3.0 107670 1.5586 34.9825 18.4964 30.6724 32.7644
1.7253 4.0 143560 1.5584 35.074 18.6171 30.8007 32.9132
1.705 5.0 179450 1.5528 35.023 18.5787 30.7014 32.8396
1.6894 6.0 215340 1.5518 35.0583 18.6754 30.791 32.8814
1.6776 7.0 251230 1.5468 35.2236 18.6812 30.8944 33.0362
1.6687 8.0 287120 1.5474 35.154 18.683 30.8481 32.9638

Framework versions

  • Transformers 4.14.0
  • Pytorch 1.5.0
  • Datasets 2.3.2
  • Tokenizers 0.10.3
🤗 Data Source: Hugging Face ↗
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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--ubikpt--t5-small-finetuned-cnn-v2
slug
ubikpt--t5-small-finetuned-cnn-v2
source
huggingface
author
ubikpt
license
tags

⚙ī¸ Technical Specs

architecture
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params billions
null
context length
null
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