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Model

Distilbert Base Uncased Finetuned Emotion

Name: Distilbert Base Uncased Finetuned Emotion
Author: Danilo31312025

by Danilo31312025 hf-model--danilo31312025--distilbert-base-uncased-finetuned-emotion

Free2AITools Nexus Index

39.0 Top 100%

S: Semantic 50

A: Authority 0

P: Popularity 2

R: Recency 97

Q: Quality 65

Tech Context

0.07B Params

512 Ctx

Vital Performance

51 DL / 30D

0.0%

Source →

Audited 39 FNI Score

Tiny 0.07B Params

1k Context

51 Downloads

8G GPU ~2GB Est. VRAM

Dense DISTILBERTFORSEQUENCECLASSIFICATION Architecture

Commercial APACHE License

Model Information Summary
Entity Passport
Registry ID	hf-model--danilo31312025--distilbert-base-uncased-finetuned-emotion
License	Apache-2.0
Provider	huggingface

💾

Compute Threshold

~1.4GB VRAM

Interactive

Analyze Hardware

Hardware Compatibility Test

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* Static estimation for 4-Bit Quantization.

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Cite this model

Academic & Research Attribution

BibTeX

@misc{hf_model__danilo31312025__distilbert_base_uncased_finetuned_emotion,
  author = {Danilo31312025},
  title = {Distilbert Base Uncased Finetuned Emotion Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/Danilo31312025/distilbert-base-uncased-finetuned-emotion}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}

APA Style

Danilo31312025. (2026). Distilbert Base Uncased Finetuned Emotion [Model]. Free2AITools. https://huggingface.co/Danilo31312025/distilbert-base-uncased-finetuned-emotion

🔬Technical Deep Dive

Full Specifications [+]

Quick Commands

🦙 Ollama Run

ollama run distilbert-base-uncased-finetuned-emotion

🤗 HF Download

huggingface-cli download danilo31312025/distilbert-base-uncased-finetuned-emotion

📦 Install Lib

pip install -U transformers

⚖️ Free2AITools Nexus Index V2.0

Methodology Index Protocol

Semantic (S) 50

Authority (A) 0

Popularity (P) 2

Recency (R) 97

Quality (Q) 65

💬 Index Insight

FNI V2.0 for Distilbert Base Uncased Finetuned Emotion: Semantic (S:50), Authority (A:0), Popularity (P:2), Recency (R:97), Quality (Q:65).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit

Unbiased Data Node Refresh: VFS Live

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🚀 What's Next?

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Deployment Guide

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Technical Deep Dive

distilbert-base-uncased-finetuned-emotion

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2151
Accuracy: 0.927
F1: 0.9268

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: 2e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.8024	1.0	250	0.3018	0.911	0.9107
0.2440	2.0	500	0.2151	0.927	0.9268

Framework versions

Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2

⚠️ 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

• Benchmark scores may vary based on evaluation methodology and hardware configuration.
• VRAM requirements are estimates; actual usage depends on quantization and batch size.
• 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

51Downloads

Hub Discussions

🤗 Data Source: Hugging Face ↗

🔄 Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹ️ Verify with original source

🛡️ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id: hf-model--danilo31312025--distilbert-base-uncased-finetuned-emotion
slug: danilo31312025--distilbert-base-uncased-finetuned-emotion
source: huggingface
author: Danilo31312025
license: Apache-2.0
tags: transformers, safetensors, distilbert, text-classification, generated_from_trainer, base_model:distilbert/distilbert-base-uncased, license:apache-2.0, text-embeddings-inference, endpoints_compatible, region:us

⚙️ Technical Specs

architecture: DistilBertForSequenceClassification
params billions: 0.07
context length: 512
pipeline tag: text-classification
vram gb: 1.4
vram is estimated: true
vram formula: VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads: 51
stars: 0
forks: 0

Data indexed from public sources. Updated daily.