feat: add internlm2-chat-7b-config

README.md

@@ -39,6 +39,7 @@
 |         模型          |   类型   |
 | :-------------------: | :------: |
 |   InternLM2_7B_chat   |  qlora   |
+|   InternLM2_7B_chat   | 全量微调 |
 |  InternLM2_1_8B_chat  | 全量微调 |
 |     Qwen_7b_chat      |  qlora   |
 |   Qwen1_5-0_5B-Chat   | 全量微调 |
@@ -63,11 +64,15 @@
 - 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
+- 【2024.3.3】 [基于InternLM2-7B-chat全量微调版本开源](https://openxlab.org.cn/models/detail/ajupyter/EmoLLM_internlm2_7b_full)，需要两块100*80G，更新专业评估，详见[evaluate](./evaluate/)，更新基于PaddleOCR的PDF转txt工具脚本，详见[scripts](./scripts/)
 - 【2024.2.29】更新客观评估计算，详见[evaluate](./evaluate/)，更新一系列数据集，详见[datasets](./datasets/)。
 - 【2024.2.27】更新英文readme和一系列数据集（舔狗和单轮对话）
 - 【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~
+
+<summary>查看更多</summary>
+
 - 【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"> 
@@ -75,7 +80,6 @@
 </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！！🥳🥳
 
@@ -247,8 +251,10 @@ git clone https://github.com/SmartFlowAI/EmoLLM.git
 
 
 ## 交流群
+- 如果失效，请移步Issue区
+
 <p align="center">
   <img  width="30%" src="https://github.com/SmartFlowAI/EmoLLM/assets/62385492/55ecd0aa-4832-4269-ad57-4c26f9aa286b" alt="EmoLLM官方交流群">
 </p>
 
-- 如果失效，请移步Issue区
+

README_EN.md

@@ -40,6 +40,7 @@
 |         model          |   type   |
 | :-------------------: | :------: |
 |   InternLM2_7B_chat   |  qlora   |
+|  InternLM2_7B_chat  | full finetuning |
 |  InternLM2_1_8B_chat  | full finetuning |
 |     Qwen_7b_chat      |  qlora   |
 |   Qwen1_5-0_5B-Chat   | full finetuning |
@@ -62,6 +63,7 @@ The Model is aimed at fully understanding and promoting the mental health of ind
 - Prevention and intervention measures: The Mental Health Grand Model also includes strategies for preventing psychological issues and promoting mental health, such as psychological education, counseling, therapy, and social support systems.
 - Assessment and diagnostic tools: Effective promotion of mental health requires scientific tools to assess individuals' psychological states and diagnose potential psychological issues.
 ### Recent Updates
+- 【2024.3.3】 [Based on InternLM2-7B-chat full amount of fine-tuned version of open source](https://openxlab.org.cn/models/detail/ajupyter/EmoLLM_internlm2_7b_full), need two 100*80G, update professional evaluation, see [evaluate](./evaluate/), update PaddleOCR-based PDF to txt tool scripts, see [scripts](./scripts/).
 - 【2024.2.29】 Updated objective assessment calculations, see [evaluate](./evaluate/) for details. A series of datasets have also been updated, see [datasets](./datasets/) for details.
 - 【2024.2.27】 Updated English README and a series of datasets (licking dogs and one-round dialogue)
 - 【2024.2.23】The "Gentle Lady Psychologist Ai Wei" based on InternLM2_7B_chat_qlora was launched. [Click here to obtain the model weights](https://openxlab.org.cn/models/detail/ajupyter/EmoLLM_aiwei), [configuration file](xtuner_config/aiwei-internlm2_chat_7b_qlora.py), [online experience link](https://openxlab.org.cn/apps/detail/ajupyter/EmoLLM-aiwei)
@@ -70,15 +72,16 @@ The Model is aimed at fully understanding and promoting the mental health of ind
 
 - 【2024.2.18】 The full fine-tuned version based on Qwen1_5-0_5B-Chat has been [open-sourced](https://www.modelscope.cn/models/aJupyter/EmoLLM_Qwen1_5-0_5B-Chat_full_sft/summary). Friends with limited computational resources can now dive in and explore it.
 
+
+<details>
+<summary>View More</summary>
+
 - 【2024.2.6】 [Open-sourced based on the Qwen1_5-0_5B-Chat full-scale fine-tuned version](https://www.modelscope.cn/models/aJupyter/EmoLLM_Qwen1_5-0_5B-Chat_full_sft/summary), friends with limited computing power can start experimenting~
 
 <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>View More</summary>
-
 - 【2024.2.5】 The project has been promoted by the official WeChat account NLP Engineering. Here's the [link](https://mp.weixin.qq.com/s/78lrRl2tlXEKUfElnkVx4A) to the article. Welcome everyone to follow!! 🥳🥳
 
 <p align="center">
@@ -249,3 +252,10 @@ The project is licensed under the MIT License. Please refer to the details
 [issues-url]: https://img.shields.io/github/issues/SmartflowAI/EmoLLM.svg
 [license-shield]: https://img.shields.io/github/license/SmartflowAI/EmoLLM.svg?style=flat-square
 [license-url]: https://github.com/SmartflowAI/EmoLLM/blob/main/LICENSE
+
+## Communication group
+- If it fails, go to the Issue section.
+
+<p align="center">
+  <img  width="30%" src="https://github.com/SmartFlowAI/EmoLLM/assets/62385492/55ecd0aa-4832-4269-ad57-4c26f9aa286b" alt="EmoLLM official communication group">
+</p>

datasets/processed/process.py

@@ -0,0 +1,12 @@
+import json
+
+# 打开JSON文件并读取其内容
+with open('/root/Emollm/datasets/multi_turn_dataset_2.json', 'rt', encoding='utf-8') as file:
+    data = json.load(file)
+
+n = 0
+for i in data:
+    i['conversation'][0]['system'] = "你是心理健康助手EmoLLM，由EmoLLM团队打造。你旨在通过专业心理咨询，协助来访者完成心理诊断。请充分利用专业心理学知识与咨询技术，一步步帮助来访者解决心理问题。"
+
+with open('output2.json', 'wt', encoding='utf-8') as file:
+    json.dump(data, file, ensure_ascii=False, indent=4)

xtuner_config/internlm2_chat_7b_full.py

@@ -0,0 +1,222 @@
+# Copyright (c) OpenMMLab. All rights reserved.
+import torch
+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 peft import LoraConfig
+from torch.optim import AdamW
+from transformers import (AutoModelForCausalLM, AutoTokenizer,
+                          BitsAndBytesConfig)
+
+from xtuner.dataset import ConcatDataset, 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
+
+from mmengine.visualization import Visualizer,WandbVisBackend, TensorboardVisBackend
+
+#######################################################################
+#                          PART 1  Settings                           #
+#######################################################################
+# Model
+pretrained_model_name_or_path = '/root/share/model_repos/internlm2-chat-7b'
+# /root/share/model_repos/internlm2-chat-7b
+use_varlen_attn = False
+
+# Data
+data_path1 = './datasets/output.json'
+data_path2 = './datasets/output2.json'
+prompt_template = PROMPT_TEMPLATE.internlm2_chat
+max_length = 4096
+pack_to_max_length = False
+
+# Scheduler & Optimizer
+batch_size = 1 # per_device
+accumulative_counts = 4
+dataloader_num_workers = 1
+max_epochs = 5
+optim_type = AdamW
+lr = 1e-6
+betas = (0.9, 0.999)
+weight_decay = 0.0001
+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 = "你是心理健康助手EmoLLM，由EmoLLM团队打造。你旨在通过专业心理咨询，协助来访者完成心理诊断。请充分利用专业心理学知识与咨询技术，一步步帮助来访者解决心理问题。"
+evaluation_inputs = [
+    '我最近总是感到很焦虑，尤其是在学业上。我有个特别崇拜的同学，他好像在各方面都比我优秀，我总觉得自己怎么努力也追不上他，这让我压力特别大。', '我知道应该理性看待，但就是忍不住会去比较。我甚至晚上会因为这个睡不着觉，总想着怎样才能像他那样出色。'
+]
+
+#######################################################################
+#                      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,
+        torch_dtype=torch.bfloat16,
+     ))
+   
+
+#######################################################################
+#                      PART 3  Dataset & Dataloader                   #
+#######################################################################
+data1 = dict(
+    type=process_hf_dataset,
+    dataset=dict(type=load_dataset, path='json', data_files=dict(train=data_path1)),
+    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)
+
+data2 = dict(
+    type=process_hf_dataset,
+    dataset=dict(type=load_dataset, path='json', data_files=dict(train=data_path2)),
+    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_dataset = dict(
+    type=ConcatDataset, datasets=[data1, data2])
+
+train_dataloader = dict(
+    batch_size=batch_size,
+    num_workers=dataloader_num_workers,
+    dataset=train_dataset,
+    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,  # 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='bfloat16')
+
+# 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 = dict(
+    type=Visualizer, 
+    vis_backends=[dict(type=WandbVisBackend)]
+)
+
+# set log level
+log_level = 'INFO'
+
+# load from which checkpoint
+load_from = '/root/Emollm/work_dirs/internlm2_chat_7b_full/iter_7000.pth'
+
+# whether to resume training from the loaded checkpoint
+resume = True
+
+# Defaults to use random seed and disable `deterministic`
+randomness = dict(seed=None, deterministic=False)
+
+# set log processor
+log_processor = dict(by_epoch=False)