ayousanz / modernbert-vtuber-finetuned

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Model's Last Updated: February 17 2025
text-classification

Introduction of modernbert-vtuber-finetuned

Model Details of modernbert-vtuber-finetuned

ModernBERT-VTuber Finetuned

このモデルは sbintuitions/modernbert-ja-130m をベースに、YouTube チャンネルのタイトル・説明などのテキスト情報から VTuber か否かを判定するためにファインチューニングしたモデルです。

モデル詳細
  • ベースモデル: ModernBERT-Ja-130M
  • タスク: 2値分類(VTuber: 1, 非VTuber: 0)
  • トレーニングデータ: YouTube のチャンネルメタデータ(タイトル、説明、テキスト)
  • トレーニングパラメータ:
    • エポック数: 3
    • バッチサイズ: 4(デバイス毎)
    • 学習率: 2e-5
    • 混合精度 (fp16) を Trainer 側で有効化
使い方

以下のコード例で推論できます。

from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline

tokenizer = AutoTokenizer.from_pretrained("your_username/modernbert-vtuber-finetuned")
model = AutoModelForSequenceClassification.from_pretrained("your_username/modernbert-vtuber-finetuned")
vtuber_classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)
result = vtuber_classifier("この動画では、バーチャルなキャラクターがリアルタイムに動く様子を配信しています。")
print(result)

# 入力文章の判定結果:
# {'isVTuber': True, 'rate': 100.0}

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