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{"cells":[{"cell_type":"markdown","metadata":{"id":"Y7Wdw0O6o2xa"},"source":["# 最終課題コンペ用 Fine-tuning テンプレート（unsloth）\n","\n","最終課題コンペにて Fine-tuning を行ないたい方に向けの Fine-tuning コードです。\n","こちらは L4 を利用できない受講生の方向けにUnslothを用いたものとなっております。\n","Google Colab の無料版で利用可能な T4 でも動作可能になっています。\n","環境設定の難易度が高いので、慎重に取り組んでいただければと思います。\n","\n","\n","### terminalでのconda環境構築（Omnicampusの環境などの場合）\n","事前にterminalで環境構築の必要があります。Google Colabでは不要です。  \n","```\n","# conda環境の構築\n","wget \"https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-$(uname)-$(uname -m).sh\"  \n","\n","# このコマンドではいくつか質問があるので答えて下さい。おそらくインストール先のデフォルトは/root/miniforge3かと思います  \n","bash Miniforge3-$(uname)-$(uname -m).sh  \n","\n","# 以下、インストール先が/root/miniforge3であることを前提とします  \n","export PATH=/root/miniforge3/bin:$PATH  \n","conda init  \n","\n","# ここで一度、terminalを立ち上げ直す必要があります。  \n","# 以下のリンク先に従い環境を作ります。  \n","# https://docs.unsloth.ai/get-started/installation/conda-install  \n","conda create --name unsloth_env python=3.10 pytorch-cuda=12.1 pytorch cudatoolkit xformers -c pytorch -c nvidia -c xformers -y  \n","conda activate unsloth_env  \n","pip install \"unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git\"  \n","pip install --no-deps \"trl<0.9.0\" peft accelerate bitsandbytes  \n","\n","# jupyter notebook用のセットアップ。  \n","conda install -c conda-forge ipykernel  \n","python -m ipykernel install --user --name=unsloth_env --display-name \"Python (unsloth_env)\"  \n","```"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":2447,"status":"ok","timestamp":1734275884602,"user":{"displayName":"菊池満帆","userId":"10441799421875206511"},"user_tz":-540},"id":"cfLPgVFUxua2","outputId":"583990d6-be2e-4f27-e8a9-eac00603e67f"},"outputs":[{"output_type":"stream","name":"stdout","text":["Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"]}],"source":["from google.colab import drive\n","drive.mount('/content/drive')"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":2834,"status":"ok","timestamp":1734275887435,"user":{"displayName":"菊池満帆","userId":"10441799421875206511"},"user_tz":-540},"id":"ixz8RP8ci7be","outputId":"d57a0356-12ff-44f0-ccfc-bbda85a64ffd"},"outputs":[{"output_type":"stream","name":"stdout","text":["Requirement already satisfied: datasets in /usr/local/lib/python3.10/dist-packages (3.2.0)\n","Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from datasets) (3.16.1)\n","Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from datasets) (1.26.4)\n","Requirement already satisfied: pyarrow>=15.0.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (17.0.0)\n","Requirement already satisfied: dill<0.3.9,>=0.3.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (0.3.8)\n","Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from datasets) (2.2.2)\n","Requirement already satisfied: requests>=2.32.2 in /usr/local/lib/python3.10/dist-packages (from datasets) (2.32.3)\n","Requirement already satisfied: tqdm>=4.66.3 in /usr/local/lib/python3.10/dist-packages (from datasets) (4.66.6)\n","Requirement already satisfied: xxhash in /usr/local/lib/python3.10/dist-packages (from datasets) (3.5.0)\n","Requirement already satisfied: multiprocess<0.70.17 in /usr/local/lib/python3.10/dist-packages (from datasets) (0.70.16)\n","Requirement already satisfied: fsspec<=2024.9.0,>=2023.1.0 in /usr/local/lib/python3.10/dist-packages (from fsspec[http]<=2024.9.0,>=2023.1.0->datasets) (2024.9.0)\n","Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from datasets) (3.11.10)\n","Requirement already satisfied: huggingface-hub>=0.23.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (0.26.5)\n","Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from datasets) (24.2)\n","Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (6.0.2)\n","Requirement already satisfied: aiohappyeyeballs>=2.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (2.4.4)\n","Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.3.1)\n","Requirement already satisfied: async-timeout<6.0,>=4.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (4.0.3)\n","Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (24.2.0)\n","Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.5.0)\n","Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (6.1.0)\n","Requirement already satisfied: propcache>=0.2.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (0.2.1)\n","Requirement already satisfied: yarl<2.0,>=1.17.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.18.3)\n","Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.23.0->datasets) (4.12.2)\n","Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.32.2->datasets) (3.4.0)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.32.2->datasets) (3.10)\n","Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.32.2->datasets) (2.2.3)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.32.2->datasets) (2024.8.30)\n","Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2.8.2)\n","Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2024.2)\n","Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2024.2)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas->datasets) (1.17.0)\n"]}],"source":["!pip install datasets"]},{"cell_type":"code","source":["# import os\n","# import json\n","# import pandas as pd\n","\n","# # ディレクトリパス\n","# data_dir = \"/content/drive/MyDrive/2024メタバース工学部LLM/03.教材（講義前後にUP予定）/05.最終課題/サンプルコード/Distribution20241221_all\"\n","\n","# # ディレクトリ内のすべてのJSONファイルを取得\n","# json_files = [os.path.join(data_dir, f) for f in os.listdir(data_dir) if f.endswith(\".json\")]\n","\n","# # JSONファイルを読み込み、縦に統合\n","# all_data = []\n","# for json_file in json_files:\n","#     try:\n","#         with open(json_file, 'r', encoding='utf-8') as f:\n","#             data = json.load(f)  # JSONをロード\n","#             if isinstance(data, list):  # JSONがリスト形式の場合\n","#                 all_data.extend(data)  # リストを結合\n","#             else:\n","#                 all_data.append(data)  # オブジェクトの場合そのまま追加\n","#     except json.JSONDecodeError as e:\n","#         print(f\"Error decoding JSON in file {json_file}: {e}\")\n","#     except Exception as e:\n","#         print(f\"Error reading file {json_file}: {e}\")\n","\n","# # 統合されたデータをDataFrameに変換\n","# if all_data:  # データが存在する場合のみ実行\n","#     merged_data = pd.DataFrame(all_data)\n","#     # 結果を保存（必要に応じて）\n","#     output_path = os.path.join(data_dir, \"merged_data.json\")\n","#     merged_data.to_json(output_path, orient=\"records\", force_ascii=False, indent=4)\n","#     print(f\"統合されたデータは {output_path} に保存されました。\")\n","# else:\n","#     print(\"統合するデータが見つかりませんでした。\")\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"xm2oh2vC4090","executionInfo":{"status":"ok","timestamp":1734275887847,"user_tz":-540,"elapsed":415,"user":{"displayName":"菊池満帆","userId":"10441799421875206511"}},"outputId":"a780a925-3eda-4e05-8314-901fcf5a8628"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Error decoding JSON in file /content/drive/MyDrive/2024メタバース工学部LLM/03.教材（講義前後にUP予定）/05.最終課題/サンプルコード/Distribution20241221_all/ichikara-instruction-003-002-1.json: Invalid \\escape: line 3765 column 324 (char 672927)\n","Error decoding JSON in file /content/drive/MyDrive/2024メタバース工学部LLM/03.教材（講義前後にUP予定）/05.最終課題/サンプルコード/Distribution20241221_all/ichikara-instruction-003-003-1.json: Invalid \\escape: line 5917 column 443 (char 1022307)\n","統合されたデータは /content/drive/MyDrive/2024メタバース工学部LLM/03.教材（講義前後にUP予定）/05.最終課題/サンプルコード/Distribution20241221_all/merged_data.json に保存されました。\n"]}]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":11200,"status":"ok","timestamp":1734275899044,"user":{"displayName":"菊池満帆","userId":"10441799421875206511"},"user_tz":-540},"id":"NeKrhsB3Q_3H","colab":{"base_uri":"https://localhost:8080/"},"outputId":"48a4b66a-e9dc-4806-888a-403eafd223a3"},"outputs":[{"output_type":"stream","name":"stdout","text":["Found existing installation: unsloth 2024.12.4\n","Uninstalling unsloth-2024.12.4:\n","  Successfully uninstalled unsloth-2024.12.4\n","Collecting unsloth@ git+https://github.com/unslothai/unsloth.git (from unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git)\n","  Cloning https://github.com/unslothai/unsloth.git to /tmp/pip-install-l7sfds2s/unsloth_c59ff28c769e422fa9a79df247958f09\n","  Running command git clone --filter=blob:none --quiet https://github.com/unslothai/unsloth.git /tmp/pip-install-l7sfds2s/unsloth_c59ff28c769e422fa9a79df247958f09\n","  Resolved https://github.com/unslothai/unsloth.git to commit 85f1fa096afde5efe2fb8521d8ceec8d13a00715\n","  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n","  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n","  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n","Requirement already satisfied: unsloth_zoo>=2024.11.8 in /usr/local/lib/python3.10/dist-packages (from unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2024.12.1)\n","Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (24.2)\n","Requirement already satisfied: tyro in /usr/local/lib/python3.10/dist-packages (from unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (0.9.2)\n","Requirement already satisfied: transformers>=4.46.1 in /usr/local/lib/python3.10/dist-packages (from unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (4.46.3)\n","Requirement already satisfied: datasets>=2.16.0 in /usr/local/lib/python3.10/dist-packages (from unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (3.2.0)\n","Requirement already satisfied: sentencepiece>=0.2.0 in /usr/local/lib/python3.10/dist-packages (from unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (0.2.0)\n","Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (4.66.6)\n","Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (5.9.5)\n","Requirement already satisfied: wheel>=0.42.0 in /usr/local/lib/python3.10/dist-packages (from unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (0.45.1)\n","Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (1.26.4)\n","Requirement already satisfied: protobuf<4.0.0 in /usr/local/lib/python3.10/dist-packages (from unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (3.20.3)\n","Requirement already satisfied: huggingface_hub in /usr/local/lib/python3.10/dist-packages (from unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (0.26.5)\n","Requirement already satisfied: hf_transfer in /usr/local/lib/python3.10/dist-packages (from unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (0.1.8)\n","Requirement already satisfied: bitsandbytes>=0.43.3 in /usr/local/lib/python3.10/dist-packages (from unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (0.45.0)\n","Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (from bitsandbytes>=0.43.3->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2.5.1+cu121)\n","Requirement already satisfied: typing_extensions>=4.8.0 in /usr/local/lib/python3.10/dist-packages (from bitsandbytes>=0.43.3->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (4.12.2)\n","Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (3.16.1)\n","Requirement already satisfied: pyarrow>=15.0.0 in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (17.0.0)\n","Requirement already satisfied: dill<0.3.9,>=0.3.0 in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (0.3.8)\n","Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ 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git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2024.9.0)\n","Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (3.11.10)\n","Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from datasets>=2.16.0->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (6.0.2)\n","Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers>=4.46.1->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2024.9.11)\n","Requirement already satisfied: tokenizers<0.21,>=0.20 in /usr/local/lib/python3.10/dist-packages (from 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git+https://github.com/unslothai/unsloth.git) (1.18.3)\n","Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.32.2->datasets>=2.16.0->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (3.4.0)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.32.2->datasets>=2.16.0->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (3.10)\n","Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.32.2->datasets>=2.16.0->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2.2.3)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.32.2->datasets>=2.16.0->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2024.8.30)\n","Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich>=11.1.0->tyro->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (3.0.0)\n","Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from rich>=11.1.0->tyro->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2.18.0)\n","Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch->bitsandbytes>=0.43.3->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (3.4.2)\n","Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch->bitsandbytes>=0.43.3->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (3.1.4)\n","Requirement already satisfied: sympy==1.13.1 in /usr/local/lib/python3.10/dist-packages (from torch->bitsandbytes>=0.43.3->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (1.13.1)\n","Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from sympy==1.13.1->torch->bitsandbytes>=0.43.3->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (1.3.0)\n","Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets>=2.16.0->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2.8.2)\n","Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets>=2.16.0->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2024.2)\n","Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets>=2.16.0->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (2024.2)\n","Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich>=11.1.0->tyro->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (0.1.2)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas->datasets>=2.16.0->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (1.17.0)\n","Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch->bitsandbytes>=0.43.3->unsloth@ git+https://github.com/unslothai/unsloth.git->unsloth[colab-new]@ git+https://github.com/unslothai/unsloth.git) (3.0.2)\n","Building wheels for collected packages: unsloth\n","  Building wheel for unsloth (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n","  Created wheel for unsloth: filename=unsloth-2024.12.4-py3-none-any.whl size=173746 sha256=c7779439cf6598a9c98a91b7bafa3a0be666bdd2dd8b69ba9a6ac1bd71e8a9d4\n","  Stored in directory: /tmp/pip-ephem-wheel-cache-_jca5i07/wheels/ed/d4/e9/76fb290ee3df0a5fc21ce5c2c788e29e9607a2353d8342fd0d\n","Successfully built unsloth\n","Installing collected packages: unsloth\n","Successfully installed unsloth-2024.12.4\n"]}],"source":["# Google Colab の場合は上記の環境構築手順を行なわず、単にこのセルから実行していってください。\n","!pip uninstall unsloth -y\n","!pip install --upgrade --no-cache-dir \"unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git\""]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":6057,"status":"ok","timestamp":1734275905100,"user":{"displayName":"菊池満帆","userId":"10441799421875206511"},"user_tz":-540},"id":"knPVRpxkXSNW","colab":{"base_uri":"https://localhost:8080/"},"outputId":"a4d449ce-8298-477a-84ab-5cddeb75fd15"},"outputs":[{"output_type":"stream","name":"stdout","text":["Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (2.5.1+cu121)\n","Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch) (3.16.1)\n","Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.10/dist-packages (from torch) (4.12.2)\n","Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch) (3.4.2)\n","Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch) (3.1.4)\n","Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch) (2024.9.0)\n","Requirement already satisfied: sympy==1.13.1 in /usr/local/lib/python3.10/dist-packages (from torch) (1.13.1)\n","Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from sympy==1.13.1->torch) (1.3.0)\n","Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch) (3.0.2)\n","Requirement already satisfied: xformers in /usr/local/lib/python3.10/dist-packages (0.0.28.post3)\n","Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from xformers) (1.26.4)\n","Requirement already satisfied: torch==2.5.1 in /usr/local/lib/python3.10/dist-packages (from xformers) (2.5.1+cu121)\n","Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch==2.5.1->xformers) (3.16.1)\n","Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.10/dist-packages (from torch==2.5.1->xformers) (4.12.2)\n","Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch==2.5.1->xformers) (3.4.2)\n","Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch==2.5.1->xformers) (3.1.4)\n","Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch==2.5.1->xformers) (2024.9.0)\n","Requirement already satisfied: sympy==1.13.1 in /usr/local/lib/python3.10/dist-packages (from torch==2.5.1->xformers) (1.13.1)\n","Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from sympy==1.13.1->torch==2.5.1->xformers) (1.3.0)\n","Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch==2.5.1->xformers) (3.0.2)\n"]}],"source":["# Google Colab のデフォルトで入っているパッケージをアップグレード（Moriyasu さんありがとうございます）\n","!pip install --upgrade torch\n","!pip install --upgrade xformers"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":2929,"status":"ok","timestamp":1734275908028,"user":{"displayName":"菊池満帆","userId":"10441799421875206511"},"user_tz":-540},"id":"kAKC2CnIkEgO","colab":{"base_uri":"https://localhost:8080/"},"outputId":"807c679e-c5dd-454b-a46b-46ac7a1fb0db"},"outputs":[{"output_type":"stream","name":"stdout","text":["Requirement already satisfied: ipywidgets in /usr/local/lib/python3.10/dist-packages (8.1.5)\n","Requirement already satisfied: comm>=0.1.3 in /usr/local/lib/python3.10/dist-packages (from ipywidgets) (0.2.2)\n","Requirement already satisfied: ipython>=6.1.0 in /usr/local/lib/python3.10/dist-packages (from ipywidgets) (7.34.0)\n","Requirement already satisfied: traitlets>=4.3.1 in /usr/local/lib/python3.10/dist-packages (from ipywidgets) (5.7.1)\n","Requirement already satisfied: widgetsnbextension~=4.0.12 in /usr/local/lib/python3.10/dist-packages (from ipywidgets) (4.0.13)\n","Requirement already satisfied: jupyterlab-widgets~=3.0.12 in /usr/local/lib/python3.10/dist-packages (from ipywidgets) (3.0.13)\n","Requirement already satisfied: setuptools>=18.5 in /usr/local/lib/python3.10/dist-packages (from ipython>=6.1.0->ipywidgets) (75.1.0)\n","Requirement already satisfied: jedi>=0.16 in /usr/local/lib/python3.10/dist-packages (from ipython>=6.1.0->ipywidgets) (0.19.2)\n","Requirement already satisfied: decorator in /usr/local/lib/python3.10/dist-packages (from ipython>=6.1.0->ipywidgets) (4.4.2)\n","Requirement already satisfied: pickleshare in /usr/local/lib/python3.10/dist-packages (from ipython>=6.1.0->ipywidgets) (0.7.5)\n","Requirement already satisfied: prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from ipython>=6.1.0->ipywidgets) (3.0.48)\n","Requirement already satisfied: pygments in /usr/local/lib/python3.10/dist-packages (from ipython>=6.1.0->ipywidgets) (2.18.0)\n","Requirement already satisfied: backcall in /usr/local/lib/python3.10/dist-packages (from ipython>=6.1.0->ipywidgets) (0.2.0)\n","Requirement already satisfied: matplotlib-inline in /usr/local/lib/python3.10/dist-packages (from ipython>=6.1.0->ipywidgets) (0.1.7)\n","Requirement already satisfied: pexpect>4.3 in /usr/local/lib/python3.10/dist-packages (from ipython>=6.1.0->ipywidgets) (4.9.0)\n","Requirement already satisfied: parso<0.9.0,>=0.8.4 in /usr/local/lib/python3.10/dist-packages (from jedi>=0.16->ipython>=6.1.0->ipywidgets) (0.8.4)\n","Requirement already satisfied: ptyprocess>=0.5 in /usr/local/lib/python3.10/dist-packages (from pexpect>4.3->ipython>=6.1.0->ipywidgets) (0.7.0)\n","Requirement already satisfied: wcwidth in /usr/local/lib/python3.10/dist-packages (from prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0->ipython>=6.1.0->ipywidgets) (0.2.13)\n"]}],"source":["# notebookでインタラクティブな表示を可能とする（ただし、うまく動かない場合あり）\n","# Google Colabでは実行不要\n","!pip install ipywidgets --upgrade"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"6-t3HhxN8joX"},"outputs":[],"source":["# Install Flash Attention 2 for softcapping support\n","import torch\n","#if torch.cuda.get_device_capability()[0] >= 8:\n","    #!pip install --no-deps packaging ninja einops \"flash-attn>=2.6.3\""]},{"cell_type":"markdown","metadata":{"id":"25o4Cq9id4YC"},"source":["## モデルのロード\n","以下のコードでモデルを読み込みます。  \n","受講生の方からご指摘頂いたのですが、unslothでgemma2を読み込むと、自動でunslothが作成した非公式モデルがダウンロードされるようです。  \n","対処方法がわからない受講生はLLM-jp-3のみをご利用ください！  "]},{"cell_type":"code","execution_count":null,"metadata":{"id":"WAaS0RKXgG72"},"outputs":[],"source":["# Hugging Face Token を指定\n","# 下記の URL から Hugging Face Token を取得できますので下記の HF_TOKEN に入れてください。\n","# Write権限を付与してください。\n","# https://huggingface.co/settings/tokens\n","HF_TOKEN = \"input_yourpassword\" #@param {type:\"string\"}\n","\n","# あるいは Google Colab シークレットを使う場合、左のサイドバーより🔑マークをクリック\n","# HF_TOKEN という名前で Value に Hugging Face Token を入れてください。\n","# ノートブックからのアクセスのトグルをオンにし、下記の二行のコードのコメントアウトを外してください。\n","\n","# from google.colab import userdata\n","# HF_TOKEN=userdata.get('HF_TOKEN')"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"_fo4ylzJ0Ft9"},"outputs":[],"source":["from google.colab import output\n","output.enable_custom_widget_manager()"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":140171,"status":"ok","timestamp":1734276050012,"user":{"displayName":"菊池満帆","userId":"10441799421875206511"},"user_tz":-540},"id":"LbmtYWUH8p_J","colab":{"base_uri":"https://localhost:8080/","height":243,"referenced_widgets":["6835b97849554a26850917c7fd5ee7c0","c4a6e3ac8efe4f4b83268803744f02f1","d09e8feeebf94bb1bc36f18bc1bffe06","33a98b120a1d4f5495f7352a92b85c65","ed713975227a4ed49cfd5d39f49b93b7","f5b2137b874146e7bc02105a57818b6e","f9b50cdf659547329596a0f7d7060f69","1b88cf54738a48b582921f79b38f375a","1950c83da8fa40629dda25aed593bf43","3f98740e7ea24e1ea5302d0d37ac2778","7de23801c473415ba0eec75fff065969"]},"outputId":"2464455b-55ee-436a-ac64-58486032fd91"},"outputs":[{"output_type":"stream","name":"stdout","text":["🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n","🦥 Unsloth Zoo will now patch everything to make training faster!\n","Unsloth: WARNING `trust_remote_code` is True.\n","Are you certain you want to do remote code execution?\n","==((====))==  Unsloth 2024.12.4: Fast Llama patching. Transformers:4.46.3.\n","   \\\\   /|    GPU: NVIDIA L4. Max memory: 22.168 GB. Platform: Linux.\n","O^O/ \\_/ \\    Torch: 2.5.1+cu121. CUDA: 8.9. CUDA Toolkit: 12.1. Triton: 3.1.0\n","\\        /    Bfloat16 = TRUE. FA [Xformers = 0.0.28.post3. FA2 = False]\n"," \"-____-\"     Free Apache license: http://github.com/unslothai/unsloth\n","Unsloth: Fast downloading is enabled - ignore downloading bars which are red colored!\n"]},{"output_type":"display_data","data":{"text/plain":["Loading checkpoint shards:   0%|          | 0/6 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"6835b97849554a26850917c7fd5ee7c0"}},"metadata":{"application/vnd.jupyter.widget-view+json":{"colab":{"custom_widget_manager":{"url":"https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"}}}}},{"output_type":"stream","name":"stderr","text":["Unsloth: Dropout = 0 is supported for fast patching. You are using dropout = 0.05.\n","Unsloth will patch all other layers, except LoRA matrices, causing a performance hit.\n","Unsloth 2024.12.4 patched 40 layers with 0 QKV layers, 0 O layers and 0 MLP layers.\n"]}],"source":["# llm-jp/llm-jp-3-13bを4bit量子化のqLoRA設定でロード。\n","\n","from unsloth import FastLanguageModel\n","import torch\n","max_seq_length = 512 # unslothではRoPEをサポートしているのでコンテキスト長は自由に設定可能\n","dtype = None # Noneにしておけば自動で設定\n","load_in_4bit = True # 今回は13Bモデルを扱うためTrue\n","\n","model_id = \"llm-jp/llm-jp-3-13b\"\n","new_model_id = \"llm-jp-3-13b-it_all\" #Fine-Tuningしたモデルにつけたい名前、it: Instruction Tuning\n","# FastLanguageModel インスタンスを作成\n","model, tokenizer = FastLanguageModel.from_pretrained(\n","    model_name=model_id,\n","    dtype=dtype,\n","    load_in_4bit=load_in_4bit,\n","    trust_remote_code=True,\n",")\n","\n","# SFT用のモデルを用意\n","model = FastLanguageModel.get_peft_model(\n","    model,\n","    r = 32,\n","    target_modules = [\"q_proj\", \"k_proj\", \"v_proj\", \"o_proj\",\n","                      \"gate_proj\", \"up_proj\", \"down_proj\",],\n","    lora_alpha = 32,\n","    lora_dropout = 0.05,\n","    bias = \"none\",\n","    use_gradient_checkpointing = \"unsloth\",\n","    random_state = 3407,\n","    use_rslora = False,\n","    loftq_config = None,\n","    max_seq_length = max_seq_length,\n",")"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":1760,"status":"ok","timestamp":1734276252461,"user":{"displayName":"菊池満帆","userId":"10441799421875206511"},"user_tz":-540},"id":"RT0wnFkYjNpO","colab":{"base_uri":"https://localhost:8080/","height":17,"referenced_widgets":["6ec87cbd5fbc4524a0471ce316dc9fe9","f55f0ff24a0546e38fef4253f0a28f48","069760ee887e4e5399035cce62663a6c","8ac935bf7f074c13a7f602c9b7806a3b","4ab2b1588a3847fc9b4873ff48be2236","c6b060870b4e494b8889737f391e0abb","5dfd00859f814fcfbd4a35cfd1ca02d4","687510f5bfd24231abb1b4e78fc6f5ff","d9cf82ec99ec4ad0bc3458d04bde7ef7","2adb6ceb51d845d696de7eb6ba61d893","61786eb1fb124524b70165ff9c9ec628","9e3e2e445a3b494da83617c29de8a501","3af182b9b3e14987911e1c16722f10bb","860ec9d31673448bbb4e91bd6fb91c45","6e45635eaebf4aefaaf4725d2d394231","98dee73476d34d8fa261ccef67758d5c","0057684690f74773a29ad0d3ea909939","b8698a5619874879a4090c6f15491559","89efc700406f410785ca812a881011d2","e16e60b8f84d4bf1b65e50047acef754","fddf6b83e2b44661b3cd4700bb291b0a"]},"outputId":"9d1a0a8b-572f-4a4f-9211-ce2b10642d9c"},"outputs":[{"output_type":"display_data","data":{"text/plain":["Generating train split: 0 examples [00:00, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"6ec87cbd5fbc4524a0471ce316dc9fe9"}},"metadata":{"application/vnd.jupyter.widget-view+json":{"colab":{"custom_widget_manager":{"url":"https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"}}}}}],"source":["# 学習に用いるデータセットの指定\n","# 今回はLLM-jp の公開している Ichikara Instruction を使います。データにアクセスするためには申請が必要ですので、使いたい方のみ申請をしてください。\n","# Ichikara Instruciton を Hugging Face Hub にて公開することはお控えください。\n","# また、CC-BY-NC-SAですのでモデルはライセンスを継承する前提でお使いください。\n","\n","# 下記のリンクから申請を終えた先に Google Drive があり、Distribution20241221_all というフォルダごとダウンロードしてください。\n","# 今回は「ichikara-instruction-003-001-1.json」を使います。必要であれば展開（!unzip など）し、データセットのパスを適切に指定してください。\n","# omnicampusの開発環境では取得したデータを左側にドラッグアンドドロップしてお使いください。\n","# Google Colab の場合も左のサイドバーよりドラッグ&ドロップでアップデートしてください。\n","\n","# https://liat-aip.sakura.ne.jp/wp/llmのための日本語インストラクションデータ作成/llmのための日本語インストラクションデータ-公開/\n","# 関根聡, 安藤まや, 後藤美知子, 鈴木久美, 河原大輔, 井之上直也, 乾健太郎. ichikara-instruction: LLMのための日本語インストラクションデータの構築. 言語処理学会第30回年次大会(2024)\n","\n","from datasets import load_dataset\n","\n","dataset = load_dataset(\"json\", data_files=\"/content/drive/MyDrive/2024メタバース工学部LLM/03.教材（講義前後にUP予定）/05.最終課題/サンプルコード/Distribution20241221_all/ichikara-instruction-003-001-1.json\")\n","# パスの指定にご注意ください。アップロードしたファイルを右クリックし、「パスをコピー」をクリック、上記の data_files と合致していることをご確認ください。Omnicampus のディレクトリ構造とは異なるかもしれません。"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":1420,"status":"ok","timestamp":1734276259072,"user":{"displayName":"菊池満帆","userId":"10441799421875206511"},"user_tz":-540},"id":"BANlYJFSKf-K","colab":{"base_uri":"https://localhost:8080/","height":121,"referenced_widgets":["3682e09010bb471cae2d4bd4cbb440f2","f0e321b2548144cd88f93cdca1854514","75fd5d4ab2de486290db5e43d25c36d1","5e30f648e6444b96ade8b4eaeb18d851","9b824398d37543e7a6912de7952cfcd3","312d9fe06afb4b039f3eedb5355c2588","90530cc9a71f41709d9977f638a01b3a","f8fd3f805f5d49c2b9e2068b854e629a","ee5b3621653d4b1e93706edf4ca80b0c","0d0c091446a94f9ab7a0e245a9dd8ffb","c6685e69084941b08d60a94366230332"]},"outputId":"fb9a1e81-f9fc-4187-c62d-9bc903d334c5"},"outputs":[{"output_type":"display_data","data":{"text/plain":["Map (num_proc=4):   0%|          | 0/5806 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"3682e09010bb471cae2d4bd4cbb440f2"}},"metadata":{"application/vnd.jupyter.widget-view+json":{"colab":{"custom_widget_manager":{"url":"https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"}}}}},{"output_type":"execute_result","data":{"text/plain":["DatasetDict({\n","    train: Dataset({\n","        features: ['ID', 'text', 'output', 'formatted_text'],\n","        num_rows: 5806\n","    })\n","})"]},"metadata":{},"execution_count":13}],"source":["# 学習時のプロンプトフォーマットの定義\n","prompt = \"\"\"### 指示\n","{}\n","### 回答\n","{}\"\"\"\n","\n","\n","\"\"\"\n","formatting_prompts_func: 各データをプロンプトに合わせた形式に合わせる\n","\"\"\"\n","EOS_TOKEN = tokenizer.eos_token # トークナイザーのEOSトークン（文末トークン）\n","def formatting_prompts_func(examples):\n","    input = examples[\"text\"] # 入力データ\n","    output = examples[\"output\"] # 出力データ\n","    text = prompt.format(input, output) + EOS_TOKEN # プロンプトの作成\n","    return { \"formatted_text\" : text, } # 新しいフィールド \"formatted_text\" を返す\n","pass\n","\n","# # 各データにフォーマットを適用\n","dataset = dataset.map(\n","    formatting_prompts_func,\n","    num_proc= 4, # 並列処理数を指定\n",")\n","\n","dataset"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":542,"status":"ok","timestamp":1734276260177,"user":{"displayName":"菊池満帆","userId":"10441799421875206511"},"user_tz":-540},"id":"8NhF0GLaTkUZ","colab":{"base_uri":"https://localhost:8080/"},"outputId":"09786225-50f4-4989-d5c6-b1730025e653"},"outputs":[{"output_type":"stream","name":"stdout","text":["### 指示\n","上司と部下の間に挟まれて困った状況になりました。どうしたらいいのでしょうか。\n","### 回答\n","上司と部下の間に挟まれて困ってしまう、というのはよくある問題です。解決するためのいくつかの方法をアドバイスします。\n","\n","1.双方の話を元に提案をする：上司と部下、それぞれの考えをよく聞くために、よく会話をしましょう。互いの意見に誤解があるようなら、それを解消し、双方の考えを整理しましょう。その上で、具体例を挙げて、解決のための提案ができるとよいでしょう。\n","\n","2.中立性を保つ：どちらか一方の味方をするのではなく、あくまで中立の立場を保ち、それを双方に明らかにしましょう。感情ではなく、意見に寄り添うことが大切です。\n","\n","3.利害の発生しない第三者：もし既にかなりこじれてしまっている場合は、あなたを含めた関係者だけでは解決が難しい場合もあります。更に上の立場の人物や、他の部署で上司にも意見ができるような人物、人事部門の担当者などに間に立ってもらえないか検討しましょう。\n","\n","4.自分のメンタルケア：意見の異なる人同士に挟まれてしまうことは、あなたに大きなストレスを与えます。心身の健康を損なわないように、気分転換や気晴らしを意識的にするようにしましょう。</s>\n"]}],"source":["# データを確認\n","print(dataset[\"train\"][\"formatted_text\"][3])"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":2852,"status":"ok","timestamp":1734276265702,"user":{"displayName":"菊池満帆","userId":"10441799421875206511"},"user_tz":-540},"id":"GHSyrGcEQ_3I","colab":{"base_uri":"https://localhost:8080/","height":17,"referenced_widgets":["9e2c0203ea3141ed9f2fc9c7dc448ee1","01c1270916b44c20b13c671b6b4a15e0","4706c9cd9f2d41989f87d20e22851530","42947fb0c8fb4962b53692c17208c3ea","7a69af4df4554bb6a1f3ee7f26042618","7f39f252a22d48d492aee310782a5529","f599606e39f24112b7ae757c27966dee","d4000de9ba4c467ca4dcb926ae8514d0","19fad2440b2b4ff9a67c7a2bd871b155","8e5030a391224a21bf5b4305a20a59c5","fb1361bc24a2451aa3c352844125775e"]},"outputId":"17e30814-3754-4d6d-ff03-e4da62b24eaf"},"outputs":[{"output_type":"display_data","data":{"text/plain":["Map:   0%|          | 0/5806 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"9e2c0203ea3141ed9f2fc9c7dc448ee1"}},"metadata":{"application/vnd.jupyter.widget-view+json":{"colab":{"custom_widget_manager":{"url":"https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"}}}}}],"source":["\"\"\"\n","training_arguments: 学習の設定\n","\n","  - output_dir:\n","      -トレーニング後のモデルを保存するディレクトリ\n","\n","  - per_device_train_batch_size:\n","      - デバイスごとのトレーニングバッチサイズ\n","\n","  - per_device_eval_batch_size:\n","      - デバイスごとの評価バッチサイズ\n","\n","  - gradient_accumulation_steps:\n","      - 勾配を更新する前にステップを積み重ねる回数\n","\n","  - optim:\n","      - オプティマイザの設定\n","\n","  - num_train_epochs:\n","      - エポック数\n","\n","  - eval_strategy:\n","      - 評価の戦略 (\"no\"/\"steps\"/\"epoch\")\n","\n","  - eval_steps:\n","      - eval_strategyが\"steps\"のとき、評価を行うstep間隔\n","\n","  - logging_strategy:\n","      - ログ記録の戦略\n","\n","  - logging_steps:\n","      - ログを出力するステップ間隔\n","\n","  - warmup_steps:\n","      - 学習率のウォームアップステップ数\n","\n","  - save_steps:\n","      - モデルを保存するステップ間隔\n","\n","  - save_total_limit:\n","      - 保存しておくcheckpointの数\n","\n","  - max_steps:\n","      - トレーニングの最大ステップ数\n","\n","  - learning_rate:\n","      - 学習率\n","\n","  - fp16:\n","      - 16bit浮動小数点の使用設定（第8回演習を参考にすると良いです）\n","\n","  - bf16:\n","      - BFloat16の使用設定\n","\n","  - group_by_length:\n","      -  入力シーケンスの長さによりバッチをグループ化 (トレーニングの効率化)\n","\n","  - report_to:\n","      - ログの送信先 (\"wandb\"/\"tensorboard\"など)\n","\"\"\"\n","from trl import SFTTrainer\n","from transformers import TrainingArguments\n","from unsloth import is_bfloat16_supported\n","\n","trainer = SFTTrainer(\n","    model = model,\n","    tokenizer = tokenizer,\n","    train_dataset=dataset[\"train\"],\n","    max_seq_length = max_seq_length,\n","    dataset_text_field=\"formatted_text\",\n","    packing = False,\n","    args = TrainingArguments(\n","        per_device_train_batch_size = 2,\n","        gradient_accumulation_steps = 4,\n","        num_train_epochs = 1,\n","        logging_steps = 10,\n","        warmup_steps = 10,\n","        save_steps=100,\n","        save_total_limit=2,\n","        max_steps=-1,\n","        learning_rate = 2e-4,\n","        fp16 = not is_bfloat16_supported(),\n","        bf16 = is_bfloat16_supported(),\n","        group_by_length=True,\n","        seed = 3407,\n","        output_dir = \"outputs\",\n","        report_to = \"none\",\n","    ),\n",")"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":402,"status":"ok","timestamp":1734276267701,"user":{"displayName":"菊池満帆","userId":"10441799421875206511"},"user_tz":-540},"id":"f3U8FUkwTx_K","colab":{"base_uri":"https://localhost:8080/"},"outputId":"b35d7759-a29d-4914-88d2-40a7a71bfb23"},"outputs":[{"output_type":"stream","name":"stdout","text":["GPU = NVIDIA L4. Max memory = 22.168 GB.\n","8.656 GB of memory reserved.\n"]}],"source":["#@title 現在のメモリ使用量を表示\n","gpu_stats = torch.cuda.get_device_properties(0)\n","start_gpu_memory = round(torch.cuda.max_memory_reserved() / 1024 / 1024 / 1024, 3)\n","max_memory = round(gpu_stats.total_memory / 1024 / 1024 / 1024, 3)\n","print(f\"GPU = {gpu_stats.name}. Max memory = {max_memory} GB.\")\n","print(f\"{start_gpu_memory} GB of memory reserved.\")"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":4491354,"status":"ok","timestamp":1734280759054,"user":{"displayName":"菊池満帆","userId":"10441799421875206511"},"user_tz":-540},"id":"xjrchK4hSr0b","colab":{"base_uri":"https://localhost:8080/","height":1000},"outputId":"1768a3df-d7db-4255-e25d-ea4482478207"},"outputs":[{"output_type":"stream","name":"stderr","text":["==((====))==  Unsloth - 2x faster free finetuning | Num GPUs = 1\n","   \\\\   /|    Num examples = 5,806 | Num Epochs = 1\n","O^O/ \\_/ \\    Batch size per device = 2 | Gradient Accumulation steps = 4\n","\\        /    Total batch size = 8 | Total steps = 725\n"," \"-____-\"     Number of trainable parameters = 125,173,760\n"]},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":["\n","    <div>\n","      \n","      <progress value='725' max='725' style='width:300px; height:20px; vertical-align: middle;'></progress>\n","      [725/725 1:14:32, Epoch 0/1]\n","    </div>\n","    <table border=\"1\" class=\"dataframe\">\n","  <thead>\n"," <tr style=\"text-align: left;\">\n","      <th>Step</th>\n","      <th>Training Loss</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <td>10</td>\n","      <td>2.163000</td>\n","    </tr>\n","    <tr>\n","      <td>20</td>\n","      <td>1.991100</td>\n","    </tr>\n","    <tr>\n","      <td>30</td>\n","      <td>1.849500</td>\n","    </tr>\n","    <tr>\n","      <td>40</td>\n","      <td>1.790100</td>\n","    </tr>\n","    <tr>\n","      <td>50</td>\n","      <td>1.691200</td>\n","    </tr>\n","    <tr>\n","      <td>60</td>\n","      <td>1.853300</td>\n","    </tr>\n","    <tr>\n","      <td>70</td>\n","      <td>1.883600</td>\n","    </tr>\n","    <tr>\n","      <td>80</td>\n","      <td>1.859800</td>\n","    </tr>\n","    <tr>\n","      <td>90</td>\n","      <td>1.722000</td>\n","    </tr>\n","    <tr>\n","      <td>100</td>\n","      <td>1.648500</td>\n","    </tr>\n","    <tr>\n","      <td>110</td>\n","      <td>1.974900</td>\n","    </tr>\n","    <tr>\n","      <td>120</td>\n","      <td>1.849200</td>\n","    </tr>\n","    <tr>\n","      <td>130</td>\n","      <td>1.769100</td>\n","    </tr>\n","    <tr>\n","      <td>140</td>\n","      <td>1.664900</td>\n","    </tr>\n","    <tr>\n","      <td>150</td>\n","      <td>1.541700</td>\n","    </tr>\n","    <tr>\n","      <td>160</td>\n","      <td>1.965900</td>\n","    </tr>\n","    <tr>\n","      <td>170</td>\n","      <td>1.801900</td>\n","    </tr>\n","    <tr>\n","      <td>180</td>\n","      <td>1.820800</td>\n","    </tr>\n","    <tr>\n","      <td>190</td>\n","      <td>1.746900</td>\n","    </tr>\n","    <tr>\n","      <td>200</td>\n","      <td>1.547600</td>\n","    </tr>\n","    <tr>\n","      <td>210</td>\n","      <td>1.896400</td>\n","    </tr>\n","    <tr>\n","      <td>220</td>\n","      <td>1.731700</td>\n","    </tr>\n","    <tr>\n","      <td>230</td>\n","      <td>1.743000</td>\n","    </tr>\n","    <tr>\n","      <td>240</td>\n","      <td>1.618800</td>\n","    </tr>\n","    <tr>\n","      <td>250</td>\n","      <td>1.566300</td>\n","    </tr>\n","    <tr>\n","      <td>260</td>\n","      <td>1.906500</td>\n","    </tr>\n","    <tr>\n","      <td>270</td>\n","      <td>1.763500</td>\n","    </tr>\n","    <tr>\n","      <td>280</td>\n","      <td>1.710100</td>\n","    </tr>\n","    <tr>\n","      <td>290</td>\n","      <td>1.722800</td>\n","    </tr>\n","    <tr>\n","      <td>300</td>\n","      <td>1.495200</td>\n","    </tr>\n","    <tr>\n","      <td>310</td>\n","      <td>1.860900</td>\n","    </tr>\n","    <tr>\n","      <td>320</td>\n","      <td>1.686700</td>\n","    </tr>\n","    <tr>\n","      <td>330</td>\n","      <td>1.732300</td>\n","    </tr>\n","    <tr>\n","      <td>340</td>\n","      <td>1.561300</td>\n","    </tr>\n","    <tr>\n","      <td>350</td>\n","      <td>1.371700</td>\n","    </tr>\n","    <tr>\n","      <td>360</td>\n","      <td>1.809600</td>\n","    </tr>\n","    <tr>\n","      <td>370</td>\n","      <td>1.742700</td>\n","    </tr>\n","    <tr>\n","      <td>380</td>\n","      <td>1.658000</td>\n","    </tr>\n","    <tr>\n","      <td>390</td>\n","      <td>1.521600</td>\n","    </tr>\n","    <tr>\n","      <td>400</td>\n","      <td>1.258800</td>\n","    </tr>\n","    <tr>\n","      <td>410</td>\n","      <td>1.833100</td>\n","    </tr>\n","    <tr>\n","      <td>420</td>\n","      <td>1.653200</td>\n","    </tr>\n","    <tr>\n","      <td>430</td>\n","      <td>1.611900</td>\n","    </tr>\n","    <tr>\n","      <td>440</td>\n","      <td>1.501300</td>\n","    </tr>\n","    <tr>\n","      <td>450</td>\n","      <td>1.260800</td>\n","    </tr>\n","    <tr>\n","      <td>460</td>\n","      <td>1.927100</td>\n","    </tr>\n","    <tr>\n","      <td>470</td>\n","      <td>1.713000</td>\n","    </tr>\n","    <tr>\n","      <td>480</td>\n","      <td>1.639300</td>\n","    </tr>\n","    <tr>\n","      <td>490</td>\n","      <td>1.494300</td>\n","    </tr>\n","    <tr>\n","      <td>500</td>\n","      <td>1.298300</td>\n","    </tr>\n","    <tr>\n","      <td>510</td>\n","      <td>1.716600</td>\n","    </tr>\n","    <tr>\n","      <td>520</td>\n","      <td>1.655600</td>\n","    </tr>\n","    <tr>\n","      <td>530</td>\n","      <td>1.532200</td>\n","    </tr>\n","    <tr>\n","      <td>540</td>\n","      <td>1.493700</td>\n","    </tr>\n","    <tr>\n","      <td>550</td>\n","      <td>1.181300</td>\n","    </tr>\n","    <tr>\n","      <td>560</td>\n","      <td>1.767600</td>\n","    </tr>\n","    <tr>\n","      <td>570</td>\n","      <td>1.577500</td>\n","    </tr>\n","    <tr>\n","      <td>580</td>\n","      <td>1.515700</td>\n","    </tr>\n","    <tr>\n","      <td>590</td>\n","      <td>1.453400</td>\n","    </tr>\n","    <tr>\n","      <td>600</td>\n","      <td>1.336300</td>\n","    </tr>\n","    <tr>\n","      <td>610</td>\n","      <td>1.773400</td>\n","    </tr>\n","    <tr>\n","      <td>620</td>\n","      <td>1.642600</td>\n","    </tr>\n","    <tr>\n","      <td>630</td>\n","      <td>1.448900</td>\n","    </tr>\n","    <tr>\n","      <td>640</td>\n","      <td>1.374000</td>\n","    </tr>\n","    <tr>\n","      <td>650</td>\n","      <td>1.115100</td>\n","    </tr>\n","    <tr>\n","      <td>660</td>\n","      <td>1.749800</td>\n","    </tr>\n","    <tr>\n","      <td>670</td>\n","      <td>1.627600</td>\n","    </tr>\n","    <tr>\n","      <td>680</td>\n","      <td>1.514000</td>\n","    </tr>\n","    <tr>\n","      <td>690</td>\n","      <td>1.365500</td>\n","    </tr>\n","    <tr>\n","      <td>700</td>\n","      <td>1.079500</td>\n","    </tr>\n","    <tr>\n","      <td>710</td>\n","      <td>1.662800</td>\n","    </tr>\n","    <tr>\n","      <td>720</td>\n","      <td>1.400700</td>\n","    </tr>\n","  </tbody>\n","</table><p>"]},"metadata":{}}],"source":["#@title 学習実行\n","trainer_stats = trainer.train()"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"z_P7-b0_Q_3J"},"outputs":[],"source":["# ELYZA-tasks-100-TVの読み込み。事前にファイルをアップロードしてください\n","# データセットの読み込み。\n","# omnicampusの開発環境では、左にタスクのjsonlをドラッグアンドドロップしてから実行。\n","import json\n","datasets = []\n","with open(\"/content/drive/MyDrive/2024メタバース工学部LLM/03.教材（講義前後にUP予定）/05.最終課題/elyza-tasks-100-TV_0.jsonl\", \"r\") as f:\n","    item = \"\"\n","    for line in f:\n","      line = line.strip()\n","      item += line\n","      if item.endswith(\"}\"):\n","        datasets.append(json.loads(item))\n","        item = \"\""]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":656833,"status":"ok","timestamp":1734281415883,"user":{"displayName":"菊池満帆","userId":"10441799421875206511"},"user_tz":-540},"id":"ZsbwPAOJQ_3J","colab":{"base_uri":"https://localhost:8080/"},"outputId":"1888df37-047d-46a4-90e7-e887df723122"},"outputs":[{"output_type":"stream","name":"stderr","text":["100%|██████████| 100/100 [10:56<00:00,  6.57s/it]\n"]}],"source":["# 学習したモデルを用いてタスクを実行\n","from tqdm import tqdm\n","\n","# 推論するためにモデルのモードを変更\n","FastLanguageModel.for_inference(model)\n","\n","results = []\n","for dt in tqdm(datasets):\n","  input = dt[\"input\"]\n","\n","  prompt = f\"\"\"### 指示\\n{input}\\n### 回答\\n\"\"\"\n","\n","  inputs = tokenizer([prompt], return_tensors = \"pt\").to(model.device)\n","\n","  outputs = model.generate(**inputs, max_new_tokens = 512, use_cache = True, do_sample=False, repetition_penalty=1.2)\n","  prediction = tokenizer.decode(outputs[0], skip_special_tokens=True).split('\\n### 回答')[-1]\n","\n","  results.append({\"task_id\": dt[\"task_id\"], \"input\": input, \"output\": prediction})"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":14,"status":"ok","timestamp":1734281415883,"user":{"displayName":"菊池満帆","userId":"10441799421875206511"},"user_tz":-540},"id":"AUZb3AG8_aTK","colab":{"base_uri":"https://localhost:8080/"},"outputId":"38b6ed74-2238-41a3-d205-f2aac7d668fe"},"outputs":[{"output_type":"stream","name":"stdout","text":["/content\n"]}],"source":["import os\n","print(os.getcwd())\n"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":14,"status":"ok","timestamp":1734281415884,"user":{"displayName":"菊池満帆","userId":"10441799421875206511"},"user_tz":-540},"id":"3rFK3Vo9_3pa","colab":{"base_uri":"https://localhost:8080/"},"outputId":"c3628819-db48-4e34-97ec-fc82af1acf74"},"outputs":[{"output_type":"stream","name":"stdout","text":["現在のカレントディレクトリ: /content/drive/MyDrive/2024メタバース工学部LLM/03.教材（講義前後にUP予定）/05.最終課題/サンプルコード\n"]}],"source":["import os\n","\n","# 移動したいディレクトリのパスを指定\n","new_directory = \"/content/drive/MyDrive/2024メタバース工学部LLM/03.教材（講義前後にUP予定）/05.最終課題/サンプルコード\"\n","\n","# カレントディレクトリを変更\n","os.chdir(new_directory)\n","\n","# 確認: カレントディレクトリを表示\n","print(\"現在のカレントディレクトリ:\", os.getcwd())"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"pd8VbKeIQ_3J"},"outputs":[],"source":["# jsonlで保存\n","with open(f\"{new_model_id}_output.jsonl\", 'w', encoding='utf-8') as f:\n","    for result in results:\n","        json.dump(result, f, ensure_ascii=False)\n","        f.write('\\n')"]},{"cell_type":"markdown","metadata":{"id":"SZrFExsmCdXq"},"source":["モデルとトークナイザーをHugging Faceにアップロードします。  \n","本コードではLoRAのアダブタのみを保存します。  \n","このアダプタを用いた推論方法はModel_Inference_Template_unsloth_20241127.ipynbをご参照ください。  \n","  \n","一旦privateでアップロードしてください。  \n","https://docs.unsloth.ai/basics/saving-and-using-models"]},{"cell_type":"code","execution_count":null,"metadata":{"executionInfo":{"elapsed":15252,"status":"ok","timestamp":1734281431124,"user":{"displayName":"菊池満帆","userId":"10441799421875206511"},"user_tz":-540},"id":"GsLyYfZlF2qE","colab":{"base_uri":"https://localhost:8080/","height":86,"referenced_widgets":["d8673be4d10d4846a6e91be87364b83f","f401e60436144eab852362d090d05acd","f2f1cc4aa9b64e9190f60401ba7a2bcf","a6ea23e5a0ae484eb2b542b6eb4f5f60","ad5f7937ee5244d2b26f73d26997dbc8","c23411519d2048ac807a400ddf0e4b26","5fb2a7403eae415e97201e7f39c4a913","2b148c6af6a242da8808079dc64fec61","f00d9f56370e4172b9ab68e9785d0ab6","2cd1eef9e3a341e4aa7df850e309a612","77a8189354ac4c7a871bd3dd172706c0","f0d4bad1c7ba48a890f6bb9daeebf2bc","2142f9910e8f4fa9a838c69588609361","24492813d0a84f8b89e89239ba5c9037","5b3d91b8499c45ad9b9cc644e1c28e32","f8d4aa4659c5440dbcead8ba21d66265","6b917b2174034acab6f97551cab4fb51","db8d2a58f62843d8ac6583b6b6e1628f","a234e9d9850446e7b2f406a59a4313ce","17862f160633428ab5f7fca35812c01a","5624ab4dbe064a4880ea7a58b47b1574","10e5812322a6405cbea9a839f56cbbe8"]},"outputId":"1cd43188-36f4-47aa-bc8f-97e295345c74"},"outputs":[{"output_type":"stream","name":"stdout","text":["Unsloth: Saving LoRA adapters. Please wait...\n"]},{"output_type":"display_data","data":{"text/plain":["  0%|          | 0/1 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"d8673be4d10d4846a6e91be87364b83f"}},"metadata":{"application/vnd.jupyter.widget-view+json":{"colab":{"custom_widget_manager":{"url":"https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"}}}}},{"output_type":"display_data","data":{"text/plain":["adapter_model.safetensors:   0%|          | 0.00/501M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"10e5812322a6405cbea9a839f56cbbe8"}},"metadata":{"application/vnd.jupyter.widget-view+json":{"colab":{"custom_widget_manager":{"url":"https://ssl.gstatic.com/colaboratory-static/widgets/colab-cdn-widget-manager/2b70e893a8ba7c0f/manager.min.js"}}}}},{"output_type":"stream","name":"stderr","text":["No files have been modified since last commit. Skipping to prevent empty commit.\n","WARNING:huggingface_hub.hf_api:No files have been modified since last commit. Skipping to prevent empty commit.\n"]},{"output_type":"stream","name":"stdout","text":["Saved lora model to https://huggingface.co/llm-jp-3-13b-it_ichikara_all_lora\n"]}],"source":["# LoRAアダプタだけ保存\n","model.push_to_hub_merged(\n","    new_model_id+\"_lora\",\n","    tokenizer=tokenizer,\n","    save_method=\"lora\",\n","    token=HF_TOKEN,\n","    private=True\n",")"]}],"metadata":{"accelerator":"GPU","colab":{"gpuType":"L4","machine_shape":"hm","provenance":[]},"kernelspec":{"display_name":"Python 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