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README_ZH.md

@@ -1,7 +1,7 @@
 [**中文**](./README_ZH.md) | [**English**](./README.md)
 
 <p align="center" width="100%">
-<a href="https://github.com/daiyizheng/TCMChat" target="_blank"><img src="./logo.png" alt="TCMChat" style="width: 25%; min-width: 300px; display: block; margin: auto;"></a>
+<a href="https://github.com/daiyizheng/TCMChat" target="_blank"><img src="logo.png" alt="TCMChat" style="width: 25%; min-width: 300px; display: block; margin: auto;"></a>
 </p>
 
 # TCMChat: Traditional Chinese Medicine Recommendation System based on Large Language Model
@@ -9,33 +9,35 @@
 [![Code License](https://img.shields.io/badge/Code%20License-Apache_2.0-green.svg)](https://github.com/SCIR-HI/Huatuo-Llama-Med-Chinese/blob/main/LICENSE) [![Python 3.10.12](https://img.shields.io/badge/python-3.10.12-blue.svg)](https://www.python.org/downloads/release/python-390/)
 
 ## 新闻
-
+[2024-11-1] 我们在Huggingface上完全开源了模型权重和训练数据集                 
 [2024-5-17] huggingface 开源模型权重
 
+
 ## 应用
 
 ### 安装
-
-```
+```shell
 git clone https://github.com/daiyizheng/TCMChat
 cd TCMChat
 ```
 
-首先安装依赖包，python环境建议3.10+
-
+创建conda 环境
+```shell
+conda create -n baichuan2 python=3.10 -y
 ```
+
+首先安装依赖包，python环境建议3.10+
+``` shell
 pip install -r requirements.txt
 ```
 
 ### 权重下载
-
 - [TCMChat](https://huggingface.co/daiyizheng/TCMChat): 基于baichuan2-7B-Chat的中药、方剂知识问答与推荐。
 
 ### 推理
-
 #### 命令行测试
 
-```
+```shell
 python cli_infer.py \
 --model_name_or_path /your/model/path \
 --model_type  chat
@@ -43,114 +45,115 @@ python cli_infer.py \
 
 #### Web页面测试
 
-```
+```shell
 python gradio_demo.py
 ```
-
 我们提供了一个在线的体验工具：[https://xomics.com.cn/tcmchat](https://xomics.com.cn/tcmchat)
 
 
 ### 重新训练
 #### 数据集下载
 
-- [预训练数据](https://github.com/ZJUFanLab/TCMChat/tree/master/data/pretrain) 
-- [微调数据](https://github.com/ZJUFanLab/TCMChat/tree/master/data/sft)
-- [基准评测数据](https://github.com/ZJUFanLab/TCMChat/tree/master/data/evaluate)
-
-> 注意：目前只提供样例数据，不久将来，我们将完全开源原始数据
+- [预训练数据](https://huggingface.co/datasets/ZJUFanLab/TCMChat-dataset-600k) 
+- [微调数据](https://huggingface.co/datasets/ZJUFanLab/TCMChat-dataset-600k)
+- [基准评测数据](https://github.com/ZJUFanLab/TCMChat/tree/master/evaluation/resources)
 
 
+> 注意： 在执行预训练、微调和推理之前，请修改自己模型、数据等相关数据路径
 #### 预训练
 
 ```shell
-train_type="pretrain"
-train_file="data/pretrain/train"
-validation_file="data/pretrain/test"
-block_size="1024"
-deepspeed_dir="data/resources/deepspeed_zero_stage2_config.yml"
-num_train_epochs="2"
-export WANDB_PROJECT="TCM-${train_type}"
-date_time=$(date +"%Y%m%d%H%M%S")
-run_name="${date_time}_${block_size}"
-model_name_or_path="your/path/Baichuan2-7B-Chat"
-output_dir="output/${train_type}/${date_time}_${block_size}"
-
-
-accelerate launch --config_file ${deepspeed_dir} src/pretraining.py \
---model_name_or_path ${model_name_or_path}  \
---train_file  ${train_file}  \
---validation_file ${validation_file}  \
---preprocessing_num_workers 20  \
---cache_dir ./cache \
---block_size  ${block_size}  \
---seed 42  \
---do_train  \
---do_eval  \
---per_device_train_batch_size  32  \
---per_device_eval_batch_size  32  \
---num_train_epochs ${num_train_epochs}  \
---low_cpu_mem_usage  True \
---torch_dtype bfloat16  \
---bf16  \
---ddp_find_unused_parameters False  \
---gradient_checkpointing True  \
---learning_rate 2e-4 \
---warmup_ratio 0.05 \
---weight_decay 0.01 \
---report_to wandb  \
---run_name ${run_name}  \
---logging_dir  logs \
---logging_strategy steps \
---logging_steps 10 \
---eval_steps 50 \
---evaluation_strategy steps \
---save_steps 100 \
---save_strategy steps \
---save_total_limit 13 \
---output_dir  ${output_dir}  \
---overwrite_output_dir
+## slurm 集群
+sbatch scripts/pretrain/baichuan2_7b_chat.slurm
+##或者
+bash scripts/pretrain/baichuan2_7b_chat.sh
 ```
 
 #### 微调
 ```shell
-train_type="SFT"
-model_max_length="1024"
-date_time=$(date +"%Y%m%d%H%M%S")
-data_path="data/sft/sample_train_baichuan_data.json"
-model_name_or_path="your/path/pretrain"
-deepspeed_dir="data/resources/deepspeed_zero_stage2_confi_baichuan2.json"
-export WANDB_PROJECT="TCM-${train_type}"
-run_name="${train_type}_${date_time}"
-output_dir="output/${train_type}/${date_time}_${model_max_length}"
-
-
-deepspeed --hostfile="" src/fine-tune.py  \
-    --report_to "wandb" \
-    --run_name ${run_name}  \
-    --data_path ${data_path} \
-    --model_name_or_path ${model_name_or_path} \
-    --output_dir ${output_dir} \
-    --model_max_length ${model_max_length} \
-    --num_train_epochs 4 \
-    --per_device_train_batch_size 16 \
-    --gradient_accumulation_steps 1 \
-    --save_strategy epoch \
-    --learning_rate 2e-5 \
-    --lr_scheduler_type constant \
-    --adam_beta1 0.9 \
-    --adam_beta2 0.98 \
-    --adam_epsilon 1e-8 \
-    --max_grad_norm 1.0 \
-    --weight_decay 1e-4 \
-    --warmup_ratio 0.0 \
-    --logging_steps 1 \
-    --gradient_checkpointing True \
-    --deepspeed ${deepspeed_dir} \
-    --bf16 True \
-    --tf32 True
+## slurm 集群
+sbatch scripts/sft/baichuan2_7b_chat.slurm
+##或者
+bash scripts/sft/baichuan2_7b_chat.sh
 ```
-
 ### 训练细节
 
 请参考论文实验部分说明。
 
+### 基准评估
+#### 选择题
+```shell
+python evaluation/choices_evaluate/eval.py   --model_path_or_name /your/model/path --model_name  baichuan2-7b-chat --few_shot -sz herb --dev_file_path evaluation/resources/choice/single/tcm-herb_dev.csv --val_file_path evaluation/resources/choice/single/choice_herb_500.csv --log_dir logs/choices
+```
+
+#### 阅读理解
+```shell
+python infers/baichuan_infer.py \
+--model_name_or_path /your/model/path / \
+--model_type chat \
+--save_path /your/save/data/path \
+--data_path /your/data/path
+##BertScore
+python evaluation/question_rouge_bleu.py/question_bert_score.py
+## BLEU METEOR
+python evaluation/question_rouge_bleu.py/open_question_bleu.py
+## ROUGE-x
+python evaluation/question_rouge_bleu.py/open_question_rouge.py
+
+```
+#### 实体抽取
+```shell
+python infers/baichuan_infer.py \
+--model_name_or_path /your/model/path / \
+--model_type chat \
+--save_path /your/save/data/path \
+--data_path /your/data/path
+
+python evaluation/ner_evaluate/tcm_entity_recognition.py
+
+```
+#### 医案诊断
+```shell
+python infers/baichuan_infer.py \
+--model_name_or_path /your/model/path / \
+--model_type chat \
+--save_path /your/save/data/path \
+--data_path /your/data/path
+
+python evaluation/acc_evaluate/extract_syndrome.py
+
+```
+#### 中药或方剂推荐
+```shell
+python infers/baichuan_infer.py \
+--model_name_or_path /your/model/path / \
+--model_type chat \
+--save_path /your/save/data/path \
+--data_path /your/data/path
+
+python evaluation/recommend_evaluate/mrr_ndcg_p_r.py
+
+```
+#### ADMET预测
+##### 回归任务
+```shell
+python infers/baichuan_infer.py \
+--model_name_or_path /your/model/path / \
+--model_type chat \
+--save_path /your/save/data/path \
+--data_path /your/data/path
+
+python evaluation/admet_evaluate/rmse_mae_mse.py
+
+```
+##### 分类任务
+```shell
+python infers/baichuan_infer.py \
+--model_name_or_path /your/model/path / \
+--model_type chat \
+--save_path /your/save/data/path \
+--data_path /your/data/path
+
+python evaluation/admet_evaluate/acc_recall_f1.py
+
+```