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Model: aJupyter/EmoLLM_Qwen1_5-0_5B-Chat_full_sft Source: Original Platform
2026-07-12 06:42:07 +08:00
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--- a/README.md
+++ b/README.md
@@ -0,0 +1,226 @@
+# EmoLLM-心理健康大模型
+
+<!-- PROJECT SHIELDS -->
+[![Contributors][contributors-shield]][contributors-url]
+[![Forks][forks-shield]][forks-url]
+[![Issues][issues-shield]][issues-url]
+[![MIT License][license-shield]][license-url]
+[![Stargazers][stars-shield]][stars-url]
+<br />
+<!-- PROJECT LOGO -->
+
+<p align="center">
+  <a href="https://github.com/aJupyter/EmoLLM/">
+    <img src="https://github.com/aJupyter/EmoLLM/raw/main/assets/logo.jpeg" alt="Logo" width="30%">
+  </a>
+
+<h3 align="center">EmoLLM</h3>
+  <p align="center">
+    <br />
+    <a href="https://github.com/aJupyter/EmoLLM"><strong>探索本项目的文档 »</strong></a>
+    <br />
+    <br />
+    <a href="https://github.com/aJupyter/EmoLLM/tree/main/demo">查看Demo</a>
+    ·
+    <a href="https://github.com/aJupyter/EmoLLM/issues">报告Bug</a>
+    ·
+    <a href="https://github.com/aJupyter/EmoLLM/issues">提出新特性</a>
+  </p>
+
+</p>
+
+<!-- 本篇README.md面向开发者 -->
+
+**EmoLLM** 是一个能够支持 **理解用户-支持用户-帮助用户** 心理健康辅导链路的心理健康大模型，由 `LLM`指令微调而来，欢迎大家star~⭐⭐。目前已经开源的 `LLM`微调配置如下：
+
+|         模型          |   类型   |
+| :-------------------: | :------: |
+|   InternLM2_7B_chat   |  qlora   |
+|  InternLM2_1_8B_chat  | 全量微调 |
+|     Qwen_7b_chat      |  qlora   |
+|   Qwen1_5-0_5B-Chat   | 全量微调 |
+|  Baichuan2_13B_chat   |  qlora   |
+|      ChatGLM3_6B      |   lora   |
+| DeepSeek MoE_16B_chat |  qlora   |
+| Mixtral 8x7B_instruct |  qlora   |
+|          ……           |    ……    |
+欢迎大家为本项目做出贡献~
+
+---
+
+心理健康大模型（Mental Health Grand Model）是一个综合性的概念，它旨在全面理解和促进个体、群体乃至整个社会的心理健康状态。这个模型通常包含以下几个关键组成部分：
+
+- 认知因素：涉及个体的思维模式、信念系统、认知偏差以及解决问题的能力。认知因素对心理健康有重要影响，因为它们影响个体如何解释和应对生活中的事件。
+- 情感因素：包括情绪调节、情感表达和情感体验。情感健康是心理健康的重要组成部分，涉及个体如何管理和表达自己的情感，以及如何从负面情绪中恢复。
+- 行为因素：涉及个体的行为模式、习惯和应对策略。这包括应对压力的技巧、社交技能以及自我效能感，即个体对自己能力的信心。
+- 社会环境：包括家庭、工作、社区和文化背景等外部因素，这些因素对个体的心理健康有着直接和间接的影响。
+- 生理健康：身体健康与心理健康紧密相关。良好的身体健康可以促进心理健康，反之亦然。
+- 心理韧性：指个体在面对逆境时的恢复力和适应能力。心理韧性强的人更能够从挑战中恢复，并从中学习和成长。
+- 预防和干预措施：心理健康大模型还包括预防心理问题和促进心理健康的策略，如心理教育、心理咨询、心理治疗和社会支持系统。
+- 评估和诊断工具：为了有效促进心理健康，需要有科学的工具来评估个体的心理状态，以及诊断可能存在的心理问题。
+
+### 最近更新
+- 【2024.2.23】推出基于InternLM2_7B_chat_qlora的 `温柔御姐心理医生艾薇`，[点击获取模型权重](https://openxlab.org.cn/models/detail/ajupyter/EmoLLM_aiwei)，[配置文件](xtuner_config/aiwei-internlm2_chat_7b_qlora.py)，[在线体验链接](https://openxlab.org.cn/apps/detail/ajupyter/EmoLLM_aiwei)
+- 【2024.2.23】更新[若干微调配置](/xtuner_config/)，新增 [data_pro.json](/datasets/data_pro.json)（数量更多、场景更全、更丰富）和 [aiwei.json](/datasets/aiwei.json)（温柔御姐角色扮演专用，带有Emoji表情），即将推出 `温柔御姐心理医生艾薇`
+- 【2024.2.18】 [基于Qwen1_5-0_5B-Chat全量微调版本开源](https://www.modelscope.cn/models/aJupyter/EmoLLM_Qwen1_5-0_5B-Chat_full_sft/summary)，算力有限的道友可以玩起来~
+- 【2024.2.6】 EmoLLM在[**Openxlab** ](https://openxlab.org.cn/models/detail/jujimeizuo/EmoLLM_Model) 平台下载量高达18.7k，欢迎大家体验！
+
+<p align="center"> 
+  <img src="https://github.com/aJupyter/EmoLLM/assets/62385492/7e931682-c54d-4ded-bc67-79130c68d744" alt="模型下载量">
+</p>
+
+<details>
+<summary>查看更多</summary>
+
+- 【2024.2.5】 项目荣获公众号**NLP工程化**推文宣传[推文链接](https://mp.weixin.qq.com/s/78lrRl2tlXEKUfElnkVx4A)，为博主推广一波，欢迎大家关注！！🥳🥳
+
+<p align="center">
+  <img src="https://github.com/aJupyter/EmoLLM/assets/62385492/47868d6a-2e91-4aa9-a630-e594c14295b4" alt="公众号二维码">
+</p>
+
+- 【2024.2.3】 [项目宣传视频](https://www.bilibili.com/video/BV1N7421N76X/)完成 😊
+- 【2024.1.27】 完善数据构建文档、微调指南、部署指南、Readme等相关文档 👏
+- 【2024.1.25】 完成EmoLLM第一版并部署上线 https://openxlab.org.cn/apps/detail/jujimeizuo/EmoLLM 😀
+
+</details>
+
+## 目录
+
+- [EmoLLM-心理健康大模型](#emollm-心理健康大模型)
+  - [最近更新](#最近更新)
+  - [目录](#目录)
+    - [开发前的配置要求](#开发前的配置要求)
+    - [**使用指南**](#使用指南)
+    - [文件目录说明](#文件目录说明)
+    - [数据构建](#数据构建)
+    - [微调指南](#微调指南)
+    - [部署指南](#部署指南)
+    - [使用到的框架](#使用到的框架)
+      - [如何参与本项目](#如何参与本项目)
+    - [版本控制](#版本控制)
+    - [作者（排名不分先后）](#作者排名不分先后)
+    - [版权说明](#版权说明)
+    - [特别鸣谢](#特别鸣谢)
+  - [Star History](#star-history)
+  - [🌟 Contributors](#-contributors)
+
+###### 开发前的配置要求
+
+- 硬件：A100 40G（仅针对InternLM2_7B_chat+qlora微调+deepspeed zero2优化）
+
+###### **使用指南**
+
+1. Clone the repo
+
+```sh
+git clone https://github.com/aJupyter/EmoLLM.git
+```
+
+2. 依次阅读或者选择感兴趣的部分阅读：
+   - [文件目录说明](#文件目录说明)
+   - [数据构建](#数据构建)
+   - [微调指南](#微调指南)
+   - [部署指南](#部署指南)
+   - 查看更多详情
+
+<details>
+<summary>更多详情</summary>
+
+### 文件目录说明
+
+```
+├─assets：图像资源
+├─datasets：数据集
+├─demo：demo脚本
+├─generate_data：生成数据指南
+│  └─xinghuo
+├─scripts：一些可用工具
+└─xtuner_config：微调指南
+    └─images
+```
+
+### 数据构建
+
+请阅读[数据构建指南](generate_data/tutorial.md)查阅
+
+本次微调用到的数据集见[datasets](datasets/data.json)
+
+### 微调指南
+
+详见[微调指南](xtuner_config/README.md)
+
+### 部署指南
+
+详见[部署指南](demo/README.md)
+
+### 使用到的框架
+
+- [Xtuner](https://github.com/InternLM/xtuner)
+- [Transformers](https://github.com/huggingface/transformers)
+- [Pytorch](https://pytorch.org/)
+- …
+
+#### 如何参与本项目
+
+贡献使开源社区成为一个学习、激励和创造的绝佳场所。你所作的任何贡献都是**非常感谢**的。
+
+1. Fork the Project
+2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)
+3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)
+4. Push to the Branch (`git push origin feature/AmazingFeature`)
+5. Open a Pull Request
+
+### 版本控制
+
+该项目使用Git进行版本管理。您可以在repository参看当前可用版本。
+
+</details>
+
+### 作者（排名不分先后）
+
+[aJupyter](https://github.com/aJupyter)@datawhale成员、南开大学在读硕士
+
+[jujimeizuo](https://github.com/jujimeizuo)@江南大学硕士
+
+[Smiling&amp;Weeping](https://github.com/Smiling-Weeping-zhr)@哈尔滨工业大学（威海）在读本科生
+
+[Farewell](https://github.com/8baby8)@
+
+### 版权说明
+
+该项目签署了MIT 授权许可，详情请参阅 [LICENSE](https://github.com/aJupyter/EmoLLM/blob/master/LICENSE)
+
+### 特别鸣谢
+
+- [Sanbu](https://github.com/sanbuphy)
+- [上海人工智能实验室](https://www.shlab.org.cn/)
+- [闻星大佬（小助手）](https://github.com/vansin)
+- [扫地升（公众号宣传）](https://mp.weixin.qq.com/s/78lrRl2tlXEKUfElnkVx4A)
+
+<!-- links -->
+
+<!-- [linkedin-shield]: https://img.shields.io/badge/-LinkedIn-black.svg?style=flat-square&logo=linkedin&colorB=555 -->
+
+<!-- [linkedin-url]: https://linkedin.com/in/aJupyter -->
+
+<!-- 太少了，没必要放 -->
+
+## Star History
+
+[![Star History Chart](https://api.star-history.com/svg?repos=aJupyter/EmoLLM&type=Date)](https://star-history.com/#aJupyter/EmoLLM&Date)
+
+## 🌟 Contributors
+
+[![EmoLLM contributors](https://contrib.rocks/image?repo=aJupyter/EmoLLM&max=50)](https://github.com/aJupyter/EmoLLM/graphs/contributors)
+
+[your-project-path]: aJupyter/EmoLLM
+[contributors-shield]: https://img.shields.io/github/contributors/aJupyter/EmoLLM.svg?style=flat-square
+[contributors-url]: https://github.com/aJupyter/EmoLLM/graphs/contributors
+[forks-shield]: https://img.shields.io/github/forks/aJupyter/EmoLLM.svg?style=flat-square
+[forks-url]: https://github.com/aJupyter/EmoLLM/network/members
+[stars-shield]: https://img.shields.io/github/stars/aJupyter/EmoLLM.svg?style=flat-square
+[stars-url]: https://github.com/aJupyter/EmoLLM/stargazers
+[issues-shield]: https://img.shields.io/github/issues/aJupyter/EmoLLM.svg?style=flat-square
+[issues-url]: https://img.shields.io/github/issues/aJupyter/EmoLLM.svg
+[license-shield]: https://img.shields.io/github/license/aJupyter/EmoLLM.svg?style=flat-square
+[license-url]: https://github.com/aJupyter/EmoLLM/blob/main/LICENSE
--- a/added_tokens.json
+++ b/added_tokens.json
@@ -0,0 +1,5 @@
+{
+  "<|endoftext|>": 151643,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644
+}
--- a/config.json
+++ b/config.json
@@ -0,0 +1,28 @@
+{
+  "_name_or_path": "/root/model/qwen/Qwen1___5-0___5B-Chat",
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "hidden_act": "silu",
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 2816,
+  "max_position_embeddings": 32768,
+  "max_window_layers": 21,
+  "model_type": "qwen2",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "num_key_value_heads": 16,
+  "rms_norm_eps": 1e-06,
+  "rope_theta": 1000000.0,
+  "sliding_window": 32768,
+  "tie_word_embeddings": true,
+  "torch_dtype": "float16",
+  "transformers_version": "4.37.2",
+  "use_cache": false,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}
--- a/configuration.json
+++ b/configuration.json
@@ -0,0 +1 @@
+{"framework":"Pytorch","task":"text-generation"}
--- a/generation_config.json
+++ b/generation_config.json
@@ -0,0 +1,11 @@
+{
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "repetition_penalty": 1.1,
+  "top_p": 0.8,
+  "transformers_version": "4.37.2"
+}
--- a/merges.txt
+++ b/merges.txt
--- a/pytorch_model.bin
+++ b/pytorch_model.bin
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:86352aabe8e3ad49ad65c1c1f70cce39d0639b917292730d10c98c9b43eec2f7
+size 928069010
--- a/special_tokens_map.json
+++ b/special_tokens_map.json
@@ -0,0 +1,20 @@
+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>"
+  ],
+  "eos_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}
--- a/tokenizer.json
+++ b/tokenizer.json
--- a/tokenizer_config.json
+++ b/tokenizer_config.json
@@ -0,0 +1,44 @@
+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|endoftext|>",
+  "errors": "replace",
+  "model_max_length": 32768,
+  "pad_token": "<|endoftext|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}
--- a/vocab.json
+++ b/vocab.json
--- a/xtuner_config.py
+++ b/xtuner_config.py
@@ -0,0 +1,192 @@
+# Copyright (c) OpenMMLab. All rights reserved.
+from datasets import load_dataset
+from mmengine.dataset import DefaultSampler
+from mmengine.hooks import (CheckpointHook, DistSamplerSeedHook, IterTimerHook,
+                            LoggerHook, ParamSchedulerHook)
+from mmengine.optim import AmpOptimWrapper, CosineAnnealingLR, LinearLR
+from torch.optim import AdamW
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+from xtuner.dataset import process_hf_dataset
+from xtuner.dataset.collate_fns import default_collate_fn
+from xtuner.dataset.map_fns import alpaca_map_fn, template_map_fn_factory
+from xtuner.engine.hooks import (DatasetInfoHook, EvaluateChatHook,
+                                 VarlenAttnArgsToMessageHubHook)
+from xtuner.engine.runner import TrainLoop
+from xtuner.model import SupervisedFinetune
+from xtuner.utils import PROMPT_TEMPLATE, SYSTEM_TEMPLATE
+
+#######################################################################
+#                          PART 1  Settings                           #
+#######################################################################
+# Model
+pretrained_model_name_or_path = '/root/model/qwen/Qwen1___5-0___5B-Chat'
+use_varlen_attn = False
+
+# Data
+data_path = './merge.json'
+prompt_template = PROMPT_TEMPLATE.qwen_chat
+max_length = 2048
+pack_to_max_length = True
+
+# Scheduler & Optimizer
+batch_size = 16  # per_device
+accumulative_counts = 4
+dataloader_num_workers = 0
+max_epochs = 3
+optim_type = AdamW
+lr = 2e-5
+betas = (0.9, 0.999)
+weight_decay = 0
+max_norm = 1  # grad clip
+warmup_ratio = 0.03
+
+# Save
+save_steps = 100
+save_total_limit = 2  # Maximum checkpoints to keep (-1 means unlimited)
+
+# Evaluate the generation performance during the training
+evaluation_freq = 100
+SYSTEM = "现在你是一个心理专家，我有一些心理问题，请你用专业的知识帮我解决。"
+evaluation_inputs = [
+    '我压力很大', '生活没意思', "非常容易羡慕别人啊"
+]
+
+#######################################################################
+#                      PART 2  Model & Tokenizer                      #
+#######################################################################
+tokenizer = dict(
+    type=AutoTokenizer.from_pretrained,
+    pretrained_model_name_or_path=pretrained_model_name_or_path,
+    trust_remote_code=True,
+    padding_side='right')
+
+model = dict(
+    type=SupervisedFinetune,
+    use_varlen_attn=use_varlen_attn,
+    llm=dict(
+        type=AutoModelForCausalLM.from_pretrained,
+        pretrained_model_name_or_path=pretrained_model_name_or_path,
+        trust_remote_code=True))
+
+#######################################################################
+#                      PART 3  Dataset & Dataloader                   #
+#######################################################################
+alpaca_en = dict(
+    type=process_hf_dataset,
+    dataset=dict(type=load_dataset, path='json', data_files=dict(train=data_path)),
+    tokenizer=tokenizer,
+    max_length=max_length,
+    dataset_map_fn=None,
+    template_map_fn=dict(
+        type=template_map_fn_factory, template=prompt_template),
+    remove_unused_columns=True,
+    shuffle_before_pack=True,
+    pack_to_max_length=pack_to_max_length,
+    use_varlen_attn=use_varlen_attn)
+
+train_dataloader = dict(
+    batch_size=batch_size,
+    num_workers=dataloader_num_workers,
+    dataset=alpaca_en,
+    sampler=dict(type=DefaultSampler, shuffle=True),
+    collate_fn=dict(type=default_collate_fn, use_varlen_attn=use_varlen_attn))
+
+#######################################################################
+#                    PART 4  Scheduler & Optimizer                    #
+#######################################################################
+# optimizer
+optim_wrapper = dict(
+    type=AmpOptimWrapper,
+    optimizer=dict(
+        type=optim_type, lr=lr, betas=betas, weight_decay=weight_decay),
+    clip_grad=dict(max_norm=max_norm, error_if_nonfinite=False),
+    accumulative_counts=accumulative_counts,
+    loss_scale='dynamic',
+    dtype='float16')
+
+# learning policy
+# More information: https://github.com/open-mmlab/mmengine/blob/main/docs/en/tutorials/param_scheduler.md  # noqa: E501
+param_scheduler = [
+    dict(
+        type=LinearLR,
+        start_factor=1e-5,
+        by_epoch=True,
+        begin=0,
+        end=warmup_ratio * max_epochs,
+        convert_to_iter_based=True),
+    dict(
+        type=CosineAnnealingLR,
+        eta_min=0.0,
+        by_epoch=True,
+        begin=warmup_ratio * max_epochs,
+        end=max_epochs,
+        convert_to_iter_based=True)
+]
+
+# train, val, test setting
+train_cfg = dict(type=TrainLoop, max_epochs=max_epochs)
+
+#######################################################################
+#                           PART 5  Runtime                           #
+#######################################################################
+# Log the dialogue periodically during the training process, optional
+custom_hooks = [
+    dict(type=DatasetInfoHook, tokenizer=tokenizer),
+    dict(
+        type=EvaluateChatHook,
+        tokenizer=tokenizer,
+        every_n_iters=evaluation_freq,
+        evaluation_inputs=evaluation_inputs,
+        system=SYSTEM,
+        prompt_template=prompt_template)
+]
+
+if use_varlen_attn:
+    custom_hooks += [dict(type=VarlenAttnArgsToMessageHubHook)]
+
+# configure default hooks
+default_hooks = dict(
+    # record the time of every iteration.
+    timer=dict(type=IterTimerHook),
+    # print log every 10 iterations.
+    logger=dict(type=LoggerHook, log_metric_by_epoch=False, interval=10),
+    # enable the parameter scheduler.
+    param_scheduler=dict(type=ParamSchedulerHook),
+    # save checkpoint per `save_steps`.
+    checkpoint=dict(
+        type=CheckpointHook,
+        by_epoch=False,
+        interval=save_steps,
+        max_keep_ckpts=save_total_limit),
+    # set sampler seed in distributed evrionment.
+    sampler_seed=dict(type=DistSamplerSeedHook),
+)
+
+# configure environment
+env_cfg = dict(
+    # whether to enable cudnn benchmark
+    cudnn_benchmark=False,
+    # set multi process parameters
+    mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0),
+    # set distributed parameters
+    dist_cfg=dict(backend='nccl'),
+)
+
+# set visualizer
+visualizer = None
+
+# set log level
+log_level = 'INFO'
+
+# load from which checkpoint
+load_from = '/root/Emollm/work_dirs/qwen_0_5_B/iter_255.pth'
+
+# whether to resume training from the loaded checkpoint
+resume = False
+
+# Defaults to use random seed and disable `deterministic`
+randomness = dict(seed=None, deterministic=False)
+
+# set log processor
+log_processor = dict(by_epoch=False)
				`@@ -0,0 +1 @@`
				`{"framework":"Pytorch","task":"text-generation"}`