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Model: AcroYAMALEX/acro-yamalex-llmjp-4-math-cot Source: Original Platform
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README.md
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---
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language:
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- ja
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license: mit
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library_name: transformers
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tags:
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- math
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- chain-of-thought
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- reasoning
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- japanese
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- sft
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- llm-jp
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base_model: llm-jp/llm-jp-4-8b-v4-8b-decay2m-ipt_v3.1-instruct4
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pipeline_tag: text-generation
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---
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# acro-yamalex-llmjp-4-math-cot（モデル）
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日本語数学推論のためのChain-of-Thought (CoT) モデルです。
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[llm-jp-4-8b](https://huggingface.co/llm-jp/llm-jp-4-8b-v4-8b-decay2m-ipt_v3.1-instruct4)をベースに、306,366件の日本語CoTデータセットでSFT（教師あり微調整）を行いました。
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本モデルは[FT-LLM2026コンペティション](https://llm-jp.github.io/tuning-competition/)における我々のアプローチの中間成果物です。このCoTモデルをベースとして、さらにTIRデータでSFTを行い最終モデルを構築しています。
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## モデル概要
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| 項目 | 値 |
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|---|---|
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| ベースモデル | [llm-jp-4-8b](https://huggingface.co/llm-jp/llm-jp-4-8b-v4-8b-decay2m-ipt_v3.1-instruct4) (80億パラメータ) |
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| 学習手法 | SFT（教師あり微調整）/ フルパラメータ |
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| 学習データ | 日本語CoTデータセット（306,366件） |
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| フレームワーク | NeMo + Megatron-LM |
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| 精度 | bf16-mixed |
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## 学習設定
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[OpenMathReasoning](https://arxiv.org/abs/2504.16891)（NVIDIAのAIMO-2優勝手法）の学習手法に倣い、以下の設定でSFTを実施しました。
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| パラメータ | 値 |
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|---|---|
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| 学習率 | 2e-5 |
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| エポック数 | 2 |
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| バッチサイズ | 96 |
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| 最大系列長 | 4,096 |
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| オプティマイザ | AdamW (β₁=0.9, β₂=0.98) |
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| 重み減衰 | 0.1 |
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| ウォームアップ | 20 steps |
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| スケジューラ | CosineAnnealing |
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| 精度 | bf16-mixed |
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| PEFT | なし（フルパラメータ） |
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## 学習データ
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StackMathQAの問題に対してDeepSeek V3を用いて日本語CoT形式の解法を生成し、回答検証（文字列一致・数値比較・LLMジャッジ）を経て306,366件のデータを構築しました。
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詳細は[CoTデータセットのページ](https://huggingface.co/datasets/AcroYAMALEX/acro-yamalex-llmjp-4-math-cot)を参照してください。
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## 使い方
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "AcroYAMALEX/acro-yamalex-llmjp-4-math-cot"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype="bfloat16", device_map="auto")
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prompt = """あなたは熟練した数学の専門家であり、注意深い問題解決者です。与えられた数学の問題に対して、ステップバイステップで思考し、最終的な答えを \\boxed{...} で示してください。
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### 指示:
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1から100までの自然数の和を求めてください。
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### 応答:
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"""
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inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
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outputs = model.generate(**inputs, max_new_tokens=2048, temperature=0.7)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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## 入出力フォーマット
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### 入力
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システムプロンプトで数学の専門家としての役割を指定し、ユーザーメッセージとして数学の問題を与えます。
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### 出力
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`<think>`タグで囲まれた思考過程と、`\boxed{}`形式の最終回答を生成します。
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```
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<think>
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1からnまでの自然数の和の公式は n(n+1)/2 です。
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n = 100 を代入すると...
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</think>
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1から100までの自然数の和は、公式 n(n+1)/2 を用いて計算できます。
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$$\frac{100 \times 101}{2} = 5050$$
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$$\boxed{5050}$$
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```
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## 関連リソース
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| リソース | リンク |
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|---|---|
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| CoTデータセット | [AcroYAMALEX/acro-yamalex-llmjp-4-math-cot](https://huggingface.co/datasets/AcroYAMALEX/acro-yamalex-llmjp-4-math-cot) |
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| TIRデータセット | [AcroYAMALEX/acro-yamalex-llmjp-4-math-tir](https://huggingface.co/datasets/AcroYAMALEX/acro-yamalex-llmjp-4-math-tir) |
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| TIRモデル（最終モデル） | [AcroYAMALEX/acro-yamalex-llmjp-4-math-tir](https://huggingface.co/AcroYAMALEX/acro-yamalex-llmjp-4-math-tir) |
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| 論文 | NLP2026にて発表予定 |
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## 参考文献
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- Ivan Moshkov et al. "AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset." arXiv:2504.16891, 2025.
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- Ting Zhang et al. "StackMathQA: A Curated Collection of 2 Million Mathematical Questions and Answers Sourced from Stack Exchange." 2024.
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- DeepSeek-AI. "DeepSeek-V3 Technical Report." arXiv:2412.19437, 2024.
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## 著者
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佐々木峻・山本大輝・樋口慎・吉岡駿（アクロクエストテクノロジー株式会社）
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## ライセンス
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MIT License
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config.json
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"head_dim": 128,
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 4096,
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"mlp_bias": false,
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"num_attention_heads": 32,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rope_theta": 500000,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.47.0",
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"use_cache": true,
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"vocab_size": 196608
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}
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||||
}
|
||||
}
|
||||
51
special_tokens_map.json
Normal file
51
special_tokens_map.json
Normal file
@@ -0,0 +1,51 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|bos|>",
|
||||
"lstrip": false,
|
||||
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|
||||
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|
||||
"single_word": false
|
||||
},
|
||||
"cls_token": {
|
||||
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||||
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|
||||
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||||
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||||
"single_word": false
|
||||
},
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||||
"eos_token": {
|
||||
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|
||||
"rstrip": false,
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||||
"single_word": false
|
||||
},
|
||||
"mask_token": {
|
||||
"content": "<|mask|>",
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||||
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|
||||
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||||
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|
||||
"single_word": false
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||||
},
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||||
"pad_token": {
|
||||
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||||
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||||
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|
||||
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||||
},
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||||
"sep_token": {
|
||||
"content": "<|sep|>",
|
||||
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|
||||
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|
||||
"rstrip": false,
|
||||
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|
||||
},
|
||||
"unk_token": {
|
||||
"content": "<|unk|>",
|
||||
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|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:93acf74eb5b234011e9eb42549c312551eb6726a16b9b0f8ed8920dfafe1298d
|
||||
size 12868527
|
||||
2837
tokenizer_config.json
Normal file
2837
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user