diff --git a/README.md b/README.md index 9b5d4cc3f..4cd6fbda4 100644 --- a/README.md +++ b/README.md @@ -32,6 +32,7 @@ Features: - [Bare Metal Cloud GPU](#bare-metal-cloud-gpu) - [Windows](#windows) - [Mac](#mac) + - [Google Colab](#google-colab) - [Launching on public clouds via SkyPilot](#launching-on-public-clouds-via-skypilot) - [Dataset](#dataset) - [How to Add Custom Prompts](#how-to-add-custom-prompts) @@ -269,6 +270,10 @@ pip3 install -e '.' ``` More info: [mac.md](/docs/mac.qmd) +#### Google Colab + +Please use this example [notebook](examples/colab-notebooks/colab-axolotl-example.ipynb). + #### Launching on public clouds via SkyPilot To launch on GPU instances (both on-demand and spot instances) on 7+ clouds (GCP, AWS, Azure, OCI, and more), you can use [SkyPilot](https://skypilot.readthedocs.io/en/latest/index.html): diff --git a/examples/mistral/Mistral-7b-example/README.md b/examples/mistral/Mistral-7b-example/README.md deleted file mode 100644 index 2d5ac87a1..000000000 --- a/examples/mistral/Mistral-7b-example/README.md +++ /dev/null @@ -1,12 +0,0 @@ -# Description -This repository presents an in-depth guide for fine-tuning Mistral-7b or any other compatible model using Axolotl, tailored specifically for chatbot development. It streamlines the process of fine-tuning and uploading the enhanced model to HuggingFace πŸ€—, thereby serving as an invaluable tool for developers in the AI and chatbot domain. - -**What’s Inside:** - -Beginner-Friendly Instructions: Comprehensive steps to guide you through fine-tuning your chosen model, including details on the data structure (jsonl), configuration, and the code itself. - -Hardware Utilized: For reference, the fine-tuning in this guide was performed using 4x NVIDIA GeForce RTX 3090 (rented 2.1.2-cuda12.1-cudnn8-devel). - -**Uploading to HuggingFace πŸ€—:** -To upload your fine-tuned model to Hugging Face, include the following files: -![Screenshot 2024-01-19 213932](https://github.com/OpenAccess-AI-Collective/axolotl/assets/138583191/d660eb84-2d76-46a1-9846-cf0aeb3006d9) diff --git a/examples/mistral/Mistral-7b-example/code.ipynb b/examples/mistral/Mistral-7b-example/code.ipynb deleted file mode 100644 index 7e84d8124..000000000 --- a/examples/mistral/Mistral-7b-example/code.ipynb +++ /dev/null @@ -1,970 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "3fe31229-8f6b-48bc-a86d-af8e5466d11c", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "GPU available? True\n", - "BF16 is supported? True\n" - ] - } - ], - "source": [ - "# Check if GPU is available I used 4x NVIDIA GeForce RTX 3090 (rented 2.1.2-cuda12.1-cudnn8-devel)\n", - "import torch\n", - "print('GPU available?', torch.cuda.is_available())\n", - "print('BF16 is supported?', torch.cuda.is_bf16_supported())" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "1dee845b-f3cb-4b1e-bdd9-1a918eac140b", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Collecting huggingface_hub\n", - " Downloading huggingface_hub-0.20.1-py3-none-any.whl.metadata (12 kB)\n", - "Requirement already satisfied: filelock in /opt/conda/lib/python3.10/site-packages (from huggingface_hub) (3.9.0)\n", - "Requirement already satisfied: fsspec>=2023.5.0 in /opt/conda/lib/python3.10/site-packages (from huggingface_hub) (2023.10.0)\n", - "Requirement already satisfied: requests in /opt/conda/lib/python3.10/site-packages (from huggingface_hub) (2.31.0)\n", - "Requirement already satisfied: tqdm>=4.42.1 in /opt/conda/lib/python3.10/site-packages (from huggingface_hub) (4.65.0)\n", - "Requirement already satisfied: pyyaml>=5.1 in /opt/conda/lib/python3.10/site-packages (from huggingface_hub) (6.0.1)\n", - "Requirement already satisfied: typing-extensions>=3.7.4.3 in /opt/conda/lib/python3.10/site-packages (from huggingface_hub) (4.7.1)\n", - "Requirement already satisfied: packaging>=20.9 in /opt/conda/lib/python3.10/site-packages (from huggingface_hub) (23.1)\n", - "Requirement already satisfied: charset-normalizer<4,>=2 in /opt/conda/lib/python3.10/site-packages (from requests->huggingface_hub) (2.0.4)\n", - "Requirement already satisfied: idna<4,>=2.5 in /opt/conda/lib/python3.10/site-packages (from requests->huggingface_hub) (3.4)\n", - "Requirement already satisfied: urllib3<3,>=1.21.1 in /opt/conda/lib/python3.10/site-packages (from requests->huggingface_hub) (1.26.18)\n", - "Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.10/site-packages (from requests->huggingface_hub) (2023.7.22)\n", - "Downloading huggingface_hub-0.20.1-py3-none-any.whl (330 kB)\n", - "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m330.1/330.1 kB\u001b[0m \u001b[31m8.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m:00:01\u001b[0m\n", - "\u001b[?25hInstalling collected packages: huggingface_hub\n", - "Successfully installed huggingface_hub-0.20.1\n", - "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. 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"\u001b[?25hDownloading smmap-5.0.1-py3-none-any.whl (24 kB)\n", - "Building wheels for collected packages: flash-attn, optimum, rouge-score, deepspeed, fire, ffmpy, wavedrom\n", - " Building wheel for flash-attn (setup.py) ... \u001b[?25ldone\n", - "\u001b[?25h Created wheel for flash-attn: filename=flash_attn-2.3.3-cp310-cp310-linux_x86_64.whl size=57042553 sha256=b1df92cb5bd7657d38b789dd48e907aa3e0bd2715c817eb85f3c4320bb11fb3f\n", - " Stored in directory: /root/.cache/pip/wheels/e5/e6/fa/941802ec61d1afd320d27160ab1db98e6dba65381f84b76d4a\n", - " Building wheel for optimum (pyproject.toml) ... \u001b[?25ldone\n", - "\u001b[?25h Created wheel for optimum: filename=optimum-1.13.2-py3-none-any.whl size=395599 sha256=ff3a73120e1b6eeeda28f76e3fc8cd4cd826e5d66c869b7848ba150e7af79c62\n", - " Stored in directory: /root/.cache/pip/wheels/6e/b7/2c/79405d98f0943373d8546daeae25a3d377f7659ca0cbe48699\n", - " Building wheel for rouge-score (setup.py) ... \u001b[?25ldone\n", - "\u001b[?25h Created wheel for rouge-score: filename=rouge_score-0.1.2-py3-none-any.whl size=24932 sha256=8118ecbbcd3529085e794c803f0ddb182fc6c6d3e8a494103b49a94abf1bec37\n", - " Stored in directory: /root/.cache/pip/wheels/5f/dd/89/461065a73be61a532ff8599a28e9beef17985c9e9c31e541b4\n", - " Building wheel for deepspeed (setup.py) ... \u001b[?25ldone\n", - "\u001b[?25h Created wheel for deepspeed: filename=deepspeed-0.12.6-py3-none-any.whl size=1306729 sha256=35c46b6f0275b0d3063522e0af4f3cbd9ec1c310114d8917d87cbe2bf43346e2\n", - " Stored in directory: /root/.cache/pip/wheels/a3/dc/a2/f585faaed4dec84108916dcc8e8a7c129a216df8202ca32984\n", - " Building wheel for fire (setup.py) ... \u001b[?25ldone\n", - "\u001b[?25h Created wheel for fire: filename=fire-0.5.0-py2.py3-none-any.whl size=116934 sha256=e76d5185f237f34ec69bb8aa657497bef07408978e4f7efdaef48663bb8cd4ef\n", - " Stored in directory: /root/.cache/pip/wheels/90/d4/f7/9404e5db0116bd4d43e5666eaa3e70ab53723e1e3ea40c9a95\n", - " Building wheel for ffmpy (setup.py) ... \u001b[?25ldone\n", - "\u001b[?25h Created wheel for ffmpy: filename=ffmpy-0.3.1-py3-none-any.whl size=5579 sha256=da3b54dc0ac1a825a1a233315970ac80b8b4c53ebd9cb2a2cfdeab118f453a64\n", - " Stored in directory: /root/.cache/pip/wheels/01/a6/d1/1c0828c304a4283b2c1639a09ad86f83d7c487ef34c6b4a1bf\n", - " Building wheel for wavedrom (setup.py) ... \u001b[?25ldone\n", - "\u001b[?25h Created wheel for wavedrom: filename=wavedrom-2.0.3.post3-py2.py3-none-any.whl size=30052 sha256=7f0cbd15d63ee9c120190bac122ab51bbbfc91ee374bc3c046fadb320816c17e\n", - " Stored in directory: /root/.cache/pip/wheels/9c/52/8c/38b454b42f712f325e26f633287484c7dc1ad469e1580c5954\n", - "Successfully built flash-attn optimum rouge-score deepspeed fire ffmpy wavedrom\n", - "Installing collected packages: sentencepiece, pydub, py-cpuinfo, ninja, nh3, hjson, ffmpy, bitsandbytes, appdirs, addict, xxhash, wrapt, werkzeug, websockets, tzdata, typing-extensions, threadpoolctl, termcolor, tensorboard-data-server, svgwrite, smmap, shortuuid, setproctitle, sentry-sdk, semantic-version, scipy, safetensors, rouge, regex, python-multipart, pyparsing, pynvml, pyasn1, pyarrow-hotfix, pyarrow, protobuf, orjson, oauthlib, multidict, mdurl, markdown2, markdown, llvmlite, kiwisolver, joblib, jmespath, importlib-resources, humanfriendly, hf_transfer, h11, grpcio, google-crc32c, gekko, frozenlist, fonttools, einops, docker-pycreds, dill, cycler, contourpy, colorama, cachetools, async-timeout, art, aioitertools, aiofiles, absl-py, yarl, wavedrom, uvicorn, tiktoken, scikit-learn, rsa, responses, requests-oauthlib, pydantic, pyasn1-modules, pandas, numba, nltk, multiprocess, matplotlib, markdown-it-py, httpcore, googleapis-common-protos, google-resumable-media, gitdb, fire, coloredlogs, botocore, aiosignal, xformers, tokenizers, starlette, rouge-score, rich, httpx, google-auth, GitPython, flash-attn, deepspeed, aiohttp, accelerate, wandb, transformers, gradio-client, google-auth-oauthlib, google-api-core, fastapi, altair, aiobotocore, tensorboard, s3fs, peft, gradio, google-cloud-core, fschat, datasets, bert-score, optimum, google-cloud-storage, evaluate, auto-gptq, gcsfs, axolotl\n", - " Attempting uninstall: typing-extensions\n", - " Found existing installation: typing_extensions 4.7.1\n", - " Uninstalling typing_extensions-4.7.1:\n", - " Successfully uninstalled typing_extensions-4.7.1\n", - " Running setup.py develop for axolotl\n", - "Successfully installed GitPython-3.1.40 absl-py-2.0.0 accelerate-0.24.1 addict-2.4.0 aiobotocore-2.7.0 aiofiles-23.2.1 aiohttp-3.9.1 aioitertools-0.11.0 aiosignal-1.3.1 altair-5.2.0 appdirs-1.4.4 art-6.1 async-timeout-4.0.3 auto-gptq-0.5.1 axolotl-0.3.0 bert-score-0.3.13 bitsandbytes-0.41.3.post2 botocore-1.31.64 cachetools-5.3.2 colorama-0.4.6 coloredlogs-15.0.1 contourpy-1.2.0 cycler-0.12.1 datasets-2.16.0 deepspeed-0.12.6 dill-0.3.7 docker-pycreds-0.4.0 einops-0.7.0 evaluate-0.4.0 fastapi-0.108.0 ffmpy-0.3.1 fire-0.5.0 flash-attn-2.3.3 fonttools-4.47.0 frozenlist-1.4.1 fschat-0.2.34 gcsfs-2023.10.0 gekko-1.0.6 gitdb-4.0.11 google-api-core-2.15.0 google-auth-2.25.2 google-auth-oauthlib-1.2.0 google-cloud-core-2.4.1 google-cloud-storage-2.14.0 google-crc32c-1.5.0 google-resumable-media-2.7.0 googleapis-common-protos-1.62.0 gradio-3.50.2 gradio-client-0.6.1 grpcio-1.60.0 h11-0.14.0 hf_transfer-0.1.4 hjson-3.1.0 httpcore-1.0.2 httpx-0.26.0 humanfriendly-10.0 importlib-resources-6.1.1 jmespath-1.0.1 joblib-1.3.2 kiwisolver-1.4.5 llvmlite-0.41.1 markdown-3.5.1 markdown-it-py-3.0.0 markdown2-2.4.12 matplotlib-3.8.2 mdurl-0.1.2 multidict-6.0.4 multiprocess-0.70.15 nh3-0.2.15 ninja-1.11.1.1 nltk-3.8.1 numba-0.58.1 oauthlib-3.2.2 optimum-1.13.2 orjson-3.9.10 pandas-2.1.4 peft-0.6.0 protobuf-4.23.4 py-cpuinfo-9.0.0 pyarrow-14.0.2 pyarrow-hotfix-0.6 pyasn1-0.5.1 pyasn1-modules-0.3.0 pydantic-1.10.13 pydub-0.25.1 pynvml-11.5.0 pyparsing-3.1.1 python-multipart-0.0.6 regex-2023.12.25 requests-oauthlib-1.3.1 responses-0.18.0 rich-13.7.0 rouge-1.0.1 rouge-score-0.1.2 rsa-4.9 s3fs-2023.10.0 safetensors-0.4.1 scikit-learn-1.2.2 scipy-1.11.4 semantic-version-2.10.0 sentencepiece-0.1.99 sentry-sdk-1.39.1 setproctitle-1.3.3 shortuuid-1.0.11 smmap-5.0.1 starlette-0.32.0.post1 svgwrite-1.4.3 tensorboard-2.15.1 tensorboard-data-server-0.7.2 termcolor-2.4.0 threadpoolctl-3.2.0 tiktoken-0.5.2 tokenizers-0.15.0 transformers-4.36.2 typing-extensions-4.8.0 tzdata-2023.3 uvicorn-0.25.0 wandb-0.16.1 wavedrom-2.0.3.post3 websockets-11.0.3 werkzeug-3.0.1 wrapt-1.16.0 xformers-0.0.23 xxhash-3.4.1 yarl-1.9.4\n", - "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n", - "\u001b[0mCollecting git+https://github.com/huggingface/peft.git\n", - " Cloning https://github.com/huggingface/peft.git to /tmp/pip-req-build-hka8xgk2\n", - " Running command git clone --filter=blob:none --quiet https://github.com/huggingface/peft.git /tmp/pip-req-build-hka8xgk2\n", - " Resolved https://github.com/huggingface/peft.git to commit cf04d0353f0343cbf66627228c4495f51669af34\n", - " Installing build dependencies ... \u001b[?25ldone\n", - "\u001b[?25h Getting requirements to build wheel ... \u001b[?25ldone\n", - "\u001b[?25h Preparing metadata (pyproject.toml) ... \u001b[?25ldone\n", - "\u001b[?25hRequirement already satisfied: numpy>=1.17 in /opt/conda/lib/python3.10/site-packages (from peft==0.7.2.dev0) (1.26.0)\n", - "Requirement already satisfied: packaging>=20.0 in /opt/conda/lib/python3.10/site-packages (from peft==0.7.2.dev0) (23.1)\n", - "Requirement already satisfied: psutil in /opt/conda/lib/python3.10/site-packages (from peft==0.7.2.dev0) (5.9.0)\n", - 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"Building wheels for collected packages: peft\n", - " Building wheel for peft (pyproject.toml) ... \u001b[?25ldone\n", - "\u001b[?25h Created wheel for peft: filename=peft-0.7.2.dev0-py3-none-any.whl size=169456 sha256=4c70d23e759fa6abb3827fb2f3a8683be3b24d78777d0f403bbc2c0548e5dd4b\n", - " Stored in directory: /tmp/pip-ephem-wheel-cache-my5ncou6/wheels/d7/c7/de/1368fac8590e1b103ddc2ec2a28ad51d83aded1a3830e8a087\n", - "Successfully built peft\n", - "Installing collected packages: peft\n", - " Attempting uninstall: peft\n", - " Found existing installation: peft 0.6.0\n", - " Uninstalling peft-0.6.0:\n", - " Successfully uninstalled peft-0.6.0\n", - "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", - "axolotl 0.3.0 requires peft==0.6.0, but you have peft 0.7.2.dev0 which is incompatible.\u001b[0m\u001b[31m\n", - "\u001b[0mSuccessfully installed peft-0.7.2.dev0\n", - "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n", - "\u001b[0m" - ] - } - ], - "source": [ - "#instaling what is needed inside axolotl file\n", - "!pip install packaging\n", - "!pip install -e '.[flash-attn,deepspeed]'\n", - "!pip install -U git+https://github.com/huggingface/peft.git" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "82d1a380-1e87-48fe-89fe-25331326014d", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The following values were not passed to `accelerate launch` and had defaults used instead:\n", - "\t`--num_processes` was set to a value of `3`\n", - "\t\tMore than one GPU was found, enabling multi-GPU training.\n", - "\t\tIf this was unintended please pass in `--num_processes=1`.\n", - "\t`--num_machines` was set to a value of `1`\n", - "\t`--mixed_precision` was set to a value of `'no'`\n", - "\t`--dynamo_backend` was set to a value of `'no'`\n", - "To avoid this warning pass in values for each of the problematic parameters or run `accelerate config`.\n", - "/opt/conda/lib/python3.10/site-packages/transformers/deepspeed.py:23: FutureWarning: transformers.deepspeed module is deprecated and will be removed in a future version. Please import deepspeed modules directly from transformers.integrations\n", - " warnings.warn(\n", - "[2023-12-28 15:44:09,979] [INFO] [datasets.:58] [PID:2814] PyTorch version 2.1.1 available.\n", - "/opt/conda/lib/python3.10/site-packages/transformers/deepspeed.py:23: FutureWarning: transformers.deepspeed module is deprecated and will be removed in a future version. Please import deepspeed modules directly from transformers.integrations\n", - " warnings.warn(\n", - "/opt/conda/lib/python3.10/site-packages/transformers/deepspeed.py:23: FutureWarning: transformers.deepspeed module is deprecated and will be removed in a future version. Please import deepspeed modules directly from transformers.integrations\n", - " warnings.warn(\n", - "[2023-12-28 15:44:10,011] [INFO] [datasets.:58] [PID:2812] PyTorch version 2.1.1 available.\n", - "[2023-12-28 15:44:10,013] [INFO] [datasets.:58] [PID:2813] PyTorch version 2.1.1 available.\n", - "[2023-12-28 15:44:10,805] [INFO] [axolotl.normalize_config:150] [PID:2814] [RANK:2] GPU memory usage baseline: 0.000GB (+0.317GB misc)\u001b[39m\n", - "[2023-12-28 15:44:10,830] [INFO] [real_accelerator.py:161:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n", - "[2023-12-28 15:44:10,842] [INFO] [axolotl.normalize_config:150] [PID:2813] [RANK:1] GPU memory usage baseline: 0.000GB (+0.317GB misc)\u001b[39m\n", - "[2023-12-28 15:44:10,865] [INFO] [real_accelerator.py:161:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n", - "[2023-12-28 15:44:10,869] [INFO] [axolotl.normalize_config:150] [PID:2812] [RANK:0] GPU memory usage baseline: 0.000GB (+0.351GB misc)\u001b[39m\n", - "[2023-12-28 15:44:10,887] [INFO] [real_accelerator.py:161:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n", - "[2023-12-28 15:44:10,961] [INFO] [comm.py:637:init_distributed] cdb=None\n", - "[2023-12-28 15:44:10,994] [INFO] [comm.py:637:init_distributed] cdb=None\n", - "[2023-12-28 15:44:11,015] [INFO] [comm.py:637:init_distributed] cdb=None\n", - "[2023-12-28 15:44:11,015] [INFO] [comm.py:668:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl\n", - " dP dP dP \n", - " 88 88 88 \n", - " .d8888b. dP. .dP .d8888b. 88 .d8888b. d8888P 88 \n", - " 88' `88 `8bd8' 88' `88 88 88' `88 88 88 \n", - " 88. .88 .d88b. 88. .88 88 88. .88 88 88 \n", - " `88888P8 dP' `dP `88888P' dP `88888P' dP dP \n", - " \n", - " \n", - "\n", - "[2023-12-28 15:44:11,412] [DEBUG] [axolotl.load_tokenizer:184] [PID:2812] [RANK:0] EOS: 2 / \u001b[39m\n", - "[2023-12-28 15:44:11,412] [DEBUG] [axolotl.load_tokenizer:185] [PID:2812] [RANK:0] BOS: 1 / \u001b[39m\n", - "[2023-12-28 15:44:11,412] [DEBUG] [axolotl.load_tokenizer:186] [PID:2812] [RANK:0] PAD: 2 / \u001b[39m\n", - "[2023-12-28 15:44:11,412] [DEBUG] [axolotl.load_tokenizer:187] [PID:2812] [RANK:0] UNK: 0 / \u001b[39m\n", - "[2023-12-28 15:44:11,413] [INFO] [axolotl.load_tokenized_prepared_datasets:143] [PID:2812] [RANK:0] Loading prepared dataset from disk at tilemachos/GF_new.json/1adc45d2edc1e98ce657814412c6593c...\u001b[39m\n", - "[2023-12-28 15:44:11,415] [INFO] [axolotl.load_tokenized_prepared_datasets:145] [PID:2812] [RANK:0] Prepared dataset loaded from disk...\u001b[39m\n", - "[2023-12-28 15:44:11,432] [DEBUG] [axolotl.load_tokenizer:184] [PID:2814] [RANK:2] EOS: 2 / \u001b[39m\n", - "[2023-12-28 15:44:11,432] [DEBUG] [axolotl.load_tokenizer:185] [PID:2814] [RANK:2] BOS: 1 / \u001b[39m\n", - "[2023-12-28 15:44:11,432] [DEBUG] [axolotl.load_tokenizer:186] [PID:2814] [RANK:2] PAD: 2 / \u001b[39m\n", - "[2023-12-28 15:44:11,432] [DEBUG] [axolotl.load_tokenizer:187] [PID:2814] [RANK:2] UNK: 0 / \u001b[39m\n", - "[2023-12-28 15:44:11,530] [DEBUG] [axolotl.load_tokenizer:184] [PID:2813] [RANK:1] EOS: 2 / \u001b[39m\n", - "[2023-12-28 15:44:11,531] [DEBUG] [axolotl.load_tokenizer:185] [PID:2813] [RANK:1] BOS: 1 / \u001b[39m\n", - "[2023-12-28 15:44:11,531] [DEBUG] [axolotl.load_tokenizer:186] [PID:2813] [RANK:1] PAD: 2 / \u001b[39m\n", - "[2023-12-28 15:44:11,531] [DEBUG] [axolotl.load_tokenizer:187] [PID:2813] [RANK:1] UNK: 0 / \u001b[39m\n", - "[2023-12-28 15:44:12,158] [INFO] [axolotl.load_tokenized_prepared_datasets:143] [PID:2813] [RANK:1] Loading prepared dataset from disk at tilemachos/GF_new.json/1adc45d2edc1e98ce657814412c6593c...\u001b[39m\n", - "[2023-12-28 15:44:12,158] [INFO] [axolotl.load_tokenized_prepared_datasets:143] [PID:2814] [RANK:2] Loading prepared dataset from disk at tilemachos/GF_new.json/1adc45d2edc1e98ce657814412c6593c...\u001b[39m\n", - "[2023-12-28 15:44:12,160] [INFO] [axolotl.load_tokenized_prepared_datasets:145] [PID:2813] [RANK:1] Prepared dataset loaded from disk...\u001b[39m\n", - "[2023-12-28 15:44:12,161] [INFO] [axolotl.load_tokenized_prepared_datasets:145] [PID:2814] [RANK:2] Prepared dataset loaded from disk...\u001b[39m\n", - "[2023-12-28 15:44:12,236] [DEBUG] [axolotl.log:60] [PID:2812] [RANK:0] total_num_tokens: 28120\u001b[39m\n", - "[2023-12-28 15:44:12,238] [DEBUG] [axolotl.log:60] [PID:2812] [RANK:0] `total_supervised_tokens: 7990`\u001b[39m\n", - "[2023-12-28 15:44:12,238] [DEBUG] [axolotl.log:60] [PID:2812] [RANK:0] total_num_steps: 6\u001b[39m\n", - "[2023-12-28 15:44:12,242] [DEBUG] [axolotl.train.log:60] [PID:2812] [RANK:0] loading tokenizer... mistralai/Mistral-7B-v0.1\u001b[39m\n", - "[2023-12-28 15:44:12,518] [DEBUG] [axolotl.load_tokenizer:184] [PID:2812] [RANK:0] EOS: 2 / \u001b[39m\n", - "[2023-12-28 15:44:12,518] [DEBUG] [axolotl.load_tokenizer:185] [PID:2812] [RANK:0] BOS: 1 / \u001b[39m\n", - "[2023-12-28 15:44:12,518] [DEBUG] [axolotl.load_tokenizer:186] [PID:2812] [RANK:0] PAD: 2 / \u001b[39m\n", - "[2023-12-28 15:44:12,518] [DEBUG] [axolotl.load_tokenizer:187] [PID:2812] [RANK:0] UNK: 0 / \u001b[39m\n", - "[2023-12-28 15:44:12,518] [DEBUG] [axolotl.train.log:60] [PID:2812] [RANK:0] loading model and peft_config...\u001b[39m\n", - "[2023-12-28 15:44:12,589] [DEBUG] [axolotl.load_tokenizer:184] [PID:2814] [RANK:2] EOS: 2 / \u001b[39m\n", - "[2023-12-28 15:44:12,589] [DEBUG] [axolotl.load_tokenizer:185] [PID:2814] [RANK:2] BOS: 1 / \u001b[39m\n", - "[2023-12-28 15:44:12,589] [DEBUG] [axolotl.load_tokenizer:186] [PID:2814] [RANK:2] PAD: 2 / \u001b[39m\n", - "[2023-12-28 15:44:12,589] [DEBUG] [axolotl.load_tokenizer:187] [PID:2814] [RANK:2] UNK: 0 / \u001b[39m\n", - "[2023-12-28 15:44:12,599] [DEBUG] [axolotl.load_tokenizer:184] [PID:2813] [RANK:1] EOS: 2 / \u001b[39m\n", - "[2023-12-28 15:44:12,599] [DEBUG] [axolotl.load_tokenizer:185] [PID:2813] [RANK:1] BOS: 1 / \u001b[39m\n", - "[2023-12-28 15:44:12,599] [DEBUG] [axolotl.load_tokenizer:186] [PID:2813] [RANK:1] PAD: 2 / \u001b[39m\n", - "[2023-12-28 15:44:12,599] [DEBUG] [axolotl.load_tokenizer:187] [PID:2813] [RANK:1] UNK: 0 / \u001b[39m\n", - "[2023-12-28 15:44:13,049] [INFO] [partition_parameters.py:348:__exit__] finished initializing model - num_params = 291, num_elems = 7.24B\n", - "Loading checkpoint shards: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 2/2 [00:11<00:00, 5.81s/it]\n", - "Loading checkpoint shards: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 2/2 [00:11<00:00, 5.98s/it]\n", - "[2023-12-28 15:44:25,395] [INFO] [axolotl.load_model:503] [PID:2813] [RANK:1] GPU memory usage after model load: 7.576GB (+0.524GB cache, +0.708GB misc)\u001b[39m\n", - "[2023-12-28 15:44:25,399] [INFO] [axolotl.load_model:526] [PID:2813] [RANK:1] converting PEFT model w/ prepare_model_for_kbit_training\u001b[39m\n", - "[2023-12-28 15:44:25,403] [INFO] [axolotl.load_model:538] [PID:2813] [RANK:1] converting modules to torch.bfloat16 for flash attention\u001b[39m\n", - "trainable params: 3,407,872 || all params: 7,245,139,968 || trainable%: 0.04703666202518836\n", - "[2023-12-28 15:44:25,480] [INFO] [axolotl.load_model:568] [PID:2813] [RANK:1] GPU memory usage after adapters: 7.589GB (+1.501GB cache, +0.708GB misc)\u001b[39m\n", - "[2023-12-28 15:44:25,572] [INFO] [axolotl.load_model:503] [PID:2814] [RANK:2] GPU memory usage after model load: 7.576GB (+0.410GB cache, +0.708GB misc)\u001b[39m\n", - "[2023-12-28 15:44:25,576] [INFO] [axolotl.load_model:526] [PID:2814] [RANK:2] converting PEFT model w/ prepare_model_for_kbit_training\u001b[39m\n", - "[2023-12-28 15:44:25,580] [INFO] [axolotl.load_model:538] [PID:2814] [RANK:2] converting modules to torch.bfloat16 for flash attention\u001b[39m\n", - "trainable params: 3,407,872 || all params: 7,245,139,968 || trainable%: 0.04703666202518836\n", - "[2023-12-28 15:44:25,660] [INFO] [axolotl.load_model:568] [PID:2814] [RANK:2] GPU memory usage after adapters: 7.589GB (+1.388GB cache, +0.708GB misc)\u001b[39m\n", - "Loading checkpoint shards: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 2/2 [00:12<00:00, 6.30s/it]\n", - "[2023-12-28 15:44:26,170] [INFO] [axolotl.load_model:503] [PID:2812] [RANK:0] GPU memory usage after model load: 7.576GB (+0.776GB cache, +0.741GB misc)\u001b[39m\n", - "[2023-12-28 15:44:26,177] [INFO] [axolotl.load_model:526] [PID:2812] [RANK:0] converting PEFT model w/ prepare_model_for_kbit_training\u001b[39m\n", - "[2023-12-28 15:44:26,181] [INFO] [axolotl.load_model:538] [PID:2812] [RANK:0] converting modules to torch.bfloat16 for flash attention\u001b[39m\n", - "trainable params: 3,407,872 || all params: 7,245,139,968 || trainable%: 0.04703666202518836\n", - "[2023-12-28 15:44:26,259] [INFO] [axolotl.load_model:568] [PID:2812] [RANK:0] GPU memory usage after adapters: 7.589GB (+1.753GB cache, +0.741GB misc)\u001b[39m\n", - "[2023-12-28 15:44:26,293] [INFO] [axolotl.train.log:60] [PID:2812] [RANK:0] Pre-saving adapter config to ./out\u001b[39m\n", - "[2023-12-28 15:44:26,296] [INFO] [axolotl.train.log:60] [PID:2812] [RANK:0] Starting trainer...\u001b[39m\n", - "Using /root/.cache/torch_extensions/py310_cu121 as PyTorch extensions root...\n", - "Using /root/.cache/torch_extensions/py310_cu121 as PyTorch extensions root...\n", - "Using /root/.cache/torch_extensions/py310_cu121 as PyTorch extensions root...\n", - "Detected CUDA files, patching ldflags\n", - "Emitting ninja build file /root/.cache/torch_extensions/py310_cu121/fused_adam/build.ninja...\n", - "Building extension module fused_adam...\n", - "Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)\n", - "ninja: no work to do.\n", - "Loading extension module fused_adam...\n", - "Time to load fused_adam op: 0.05891108512878418 seconds\n", - "Loading extension module fused_adam...\n", - "Time to load fused_adam op: 0.10173463821411133 seconds\n", - "Loading extension module fused_adam...\n", - "Time to load fused_adam op: 0.10152459144592285 seconds\n", - "/opt/conda/lib/python3.10/site-packages/deepspeed/ops/adam/fused_adam.py:96: UserWarning: The torch.cuda.*DtypeTensor constructors are no longer recommended. It's best to use methods such as torch.tensor(data, dtype=*, device='cuda') to create tensors. (Triggered internally at /opt/conda/conda-bld/pytorch_1699449201336/work/torch/csrc/tensor/python_tensor.cpp:83.)\n", - " self._dummy_overflow_buf = get_accelerator().IntTensor([0])\n", - "/opt/conda/lib/python3.10/site-packages/deepspeed/ops/adam/fused_adam.py:96: UserWarning: The torch.cuda.*DtypeTensor constructors are no longer recommended. It's best to use methods such as torch.tensor(data, dtype=*, device='cuda') to create tensors. (Triggered internally at /opt/conda/conda-bld/pytorch_1699449201336/work/torch/csrc/tensor/python_tensor.cpp:83.)\n", - " self._dummy_overflow_buf = get_accelerator().IntTensor([0])\n", - "/opt/conda/lib/python3.10/site-packages/deepspeed/ops/adam/fused_adam.py:96: UserWarning: The torch.cuda.*DtypeTensor constructors are no longer recommended. It's best to use methods such as torch.tensor(data, dtype=*, device='cuda') to create tensors. (Triggered internally at /opt/conda/conda-bld/pytorch_1699449201336/work/torch/csrc/tensor/python_tensor.cpp:83.)\n", - " self._dummy_overflow_buf = get_accelerator().IntTensor([0])\n", - "Parameter Offload: Total persistent parameters: 3674112 in 193 params\n", - " 0%| | 0/17 [00:00: Who is the Founder of Apple\""}, {"from": "gpt", "value": "\": The founder of Apple is Steve Jobs\""}]} -{"conversations": [{"from": "Customer", "value": "\": What is the capital of France?\""}, {"from": "gpt", "value": "\": The capital of France is Paris.\""}]} -{"conversations": [{"from": "Customer", "value": "\": How far is the Moon from Earth?\""}, {"from": "gpt", "value": "\": The Moon is approximately 384,400 kilometers from Earth.\""}]} -{"conversations": [{"from": "Customer", "value": "\": What is the tallest mountain in the world?\""}, {"from": "gpt", "value": "\": The tallest mountain in the world is Mount Everest.\""}]} -{"conversations": [{"from": "Customer", "value": "\": Who wrote Romeo and Juliet?\""}, {"from": "gpt", "value": "\": Romeo and Juliet was written by William Shakespeare.\""}]} -{"conversations": [{"from": "Customer", "value": "\": What is the boiling point of water?\""}, {"from": "gpt", "value": "\": The boiling point of water is 100 degrees Celsius.\""}]} -{"conversations": [{"from": "Customer", "value": "\": When was the first man on the moon?\""}, {"from": "gpt", "value": "\": The first man landed on the moon in 1969.\""}]} -{"conversations": [{"from": "Customer", "value": "\": What is the largest ocean?\""}, {"from": "gpt", "value": "\": The largest ocean is the Pacific Ocean.\""}]} -{"conversations": [{"from": "Customer", "value": "\": Who invented the telephone?\""}, {"from": "gpt", "value": "\": The telephone was invented by Alexander Graham Bell.\""}]} -{"conversations": [{"from": "Customer", "value": "\": What is the formula for water?\""}, {"from": "gpt", "value": "\": The chemical formula for water is H2O.\""}]} diff --git a/examples/mistral/config.yml b/examples/mistral/config.yml index e4c73fac9..c909c63e2 100644 --- a/examples/mistral/config.yml +++ b/examples/mistral/config.yml @@ -56,6 +56,3 @@ weight_decay: 0.0 fsdp: fsdp_config: special_tokens: - bos_token: "" - eos_token: "" - unk_token: "" diff --git a/examples/mistral/Mistral-7b-example/config.yml b/examples/mistral/lora.yml similarity index 51% rename from examples/mistral/Mistral-7b-example/config.yml rename to examples/mistral/lora.yml index fd1249462..ac9ac0dd9 100644 --- a/examples/mistral/Mistral-7b-example/config.yml +++ b/examples/mistral/lora.yml @@ -1,4 +1,3 @@ -#Mistral-7b base_model: mistralai/Mistral-7B-v0.1 model_type: MistralForCausalLM tokenizer_type: LlamaTokenizer @@ -8,26 +7,32 @@ load_in_4bit: false strict: false datasets: - - path: tilemachos/Demo-Dataset #Path to json dataset file in huggingface - #for type,conversation arguments read axolotl readme and pick what is suited for your project, I wanted a chatbot and put sharegpt and chatml - type: sharegpt - conversation: chatml -dataset_prepared_path: tilemachos/Demo-Dataset #Path to json dataset file in huggingface -val_set_size: 0.05 -output_dir: ./out + - path: mhenrichsen/alpaca_2k_test + type: alpaca +dataset_prepared_path: last_run_prepared +val_set_size: 0.1 +output_dir: ./lora-out -#using lora for lower cost adapter: lora -lora_r: 8 +lora_model_dir: + +sequence_len: 8192 +sample_packing: true +pad_to_sequence_len: true + +lora_r: 32 lora_alpha: 16 lora_dropout: 0.05 +lora_target_linear: true +lora_fan_in_fan_out: lora_target_modules: + - gate_proj + - down_proj + - up_proj - q_proj - v_proj - -sequence_len: 512 -sample_packing: false -pad_to_sequence_len: true + - k_proj + - o_proj wandb_project: wandb_entity: @@ -35,18 +40,17 @@ wandb_watch: wandb_name: wandb_log_model: -#only 2 epochs because of small dataset -gradient_accumulation_steps: 3 +gradient_accumulation_steps: 4 micro_batch_size: 2 -num_epochs: 2 +num_epochs: 1 optimizer: adamw_bnb_8bit lr_scheduler: cosine learning_rate: 0.0002 train_on_inputs: false group_by_length: false -bf16: true -fp16: false +bf16: auto +fp16: tf32: false gradient_checkpointing: true @@ -57,18 +61,17 @@ logging_steps: 1 xformers_attention: flash_attention: true +loss_watchdog_threshold: 5.0 +loss_watchdog_patience: 3 + warmup_steps: 10 evals_per_epoch: 4 eval_table_size: eval_max_new_tokens: 128 saves_per_epoch: 1 debug: -#default deepspeed, can use more aggresive if needed like zero2, zero3 -deepspeed: deepspeed_configs/zero1.json +deepspeed: weight_decay: 0.0 fsdp: fsdp_config: special_tokens: - bos_token: "" - eos_token: "" - unk_token: "" diff --git a/examples/mistral/qlora.yml b/examples/mistral/qlora.yml index c8ab13b97..6fbbb9618 100644 --- a/examples/mistral/qlora.yml +++ b/examples/mistral/qlora.yml @@ -75,6 +75,3 @@ weight_decay: 0.0 fsdp: fsdp_config: special_tokens: - bos_token: "" - eos_token: "" - unk_token: ""