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README.md CHANGED
@@ -1,3 +1,112 @@
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  ---
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- license: mit
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ library_name: peft
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+ license: other
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+ base_model: Qwen/Qwen3-8B
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+ tags:
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+ - base_model:Qwen/Qwen3-8B
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+ - llama-factory
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+ - lora
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+ - transformers
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+ pipeline_tag: text-generation
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+ model-index:
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+ - name: sft100
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+ results: []
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  ---
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+
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+
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+ # GlobalHealthAtlas Public Model
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+
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+ This repository contains the code and resources for the GlobalHealthAtlas Public Model project. The project hosts a fine-tuned question-answering model designed to provide helpful answers to public health–related queries.
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+
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+ ## Overview
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+
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+ The GlobalHealthAtlas Public Model is designed to provide informative, context-aware answers to questions about public health documents and topics. It includes the fine-tuned adapter model, tokenizer files, example prompts, and scripts for running inference in a Q&A or conversational setting.
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+
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+ ## Files and Directories
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+
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+ - **adapter_config.json**: Configuration for the adapter model.
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+ - **adapter_model.safetensors**: Pre-trained adapter model.
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+ - **added_tokens.json**: Tokens added to the tokenizer.
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+ - **all_results.json**: Example outputs and sample Q&A responses from inference and evaluation.
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+ - **merges.txt**: Merges for the tokenizer.
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+ - **README.md**: This file.
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+ - **special_tokens_map.json**: Mapping of special tokens.
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+ - **tokenizer_config.json**: Configuration for the tokenizer.
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+ - **tokenizer.json**: Tokenizer file.
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+ - **train_results.json**: Results from training.
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+ - **trainer_log.jsonl**: Log of the training process.
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+ - **trainer_state.json**: State of the trainer.
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+ - **checkpoint-990/**: Directory containing checkpoint files for the model.
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+
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+ ## Usage
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+
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+ To use the GlobalHealthAtlas Public Model, clone the repository and follow the instructions in the README files. Ensure that all dependencies are installed and configured correctly. Load `adapter_model.safetensors` and the tokenizer, then run the provided inference scripts or your own prompt loop to perform question-answering. This model is intended for research and information purposes and should not be used for clinical diagnosis or other high‑stakes decisions without human review.
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+
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+ ## License
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+
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+ This project is licensed under the MIT License. See the LICENSE file for details.
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+
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+ ## Acknowledgments
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+
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+ We would like to thank the contributors and the community for their support in developing this project.
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+
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+ ## References
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+
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+ For more information, please refer to the related publications and documentation in the Public Health directory.
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+
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+ ## Model description
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+
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+ This model is a fine-tuned version of [/root/Qwen3-8B](https://huggingface.co//root/Qwen3-8B) on the GlobalHealthAtlas dataset.
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+
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+
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+ ## Intended uses & limitations
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+
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+ This model is intended to be used as a question-answering and information retrieval component for the Global Health Atlas project and related public health queries. It is designed to provide helpful, evidence-informed answers but is NOT intended for clinical diagnosis, medical advice, or other high‑stakes decision-making. Users should validate performance on their own data prior to deployment, monitor for potential biases introduced by the fine-tuning data, and review outputs with domain experts when used for operational tasks.
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+
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+ ## Training and evaluation data
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+
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+ The model was fine-tuned on the `GlobalHealthAtlas` dataset to adapt the Qwen/Qwen3-8B base model for question-answering and response generation. Evaluation used held-out splits and standard validation procedures. Detailed evaluation metrics, per-epoch results, and sample outputs are available in `train_results.json` and `all_results.json` in this repository. To reproduce results, use the same data splits and training hyperparameters listed below. For additional context about dataset preparation and task setup, consult the `Public_health/` directory and the Global Health Atlas repository: https://github.com/Jan8217/GlobalHealthAtlas.
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+
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+
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+ This model is a fine-tuned version of [/root/Qwen3-8B](https://huggingface.co//root/Qwen3-8B) on the GlobalHealthAtlas dataset
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 1
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 8
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 2.0
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+
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+ ### Training results
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+
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+ Training completed for 2 epochs using the hyperparameters listed above. Final evaluation metrics (validation loss and task-specific scores) and per-epoch logs are stored in `train_results.json` and the training log is available in `trainer_log.jsonl`. Please refer to those files for exact numeric results and per-example breakdowns.
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.15.1
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+ - Transformers 4.51.3
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
README_zh.md ADDED
@@ -0,0 +1,66 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # GlobalHealthAtlas Public Model(中文说明)
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+
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+ 本仓库包含 GlobalHealthAtlas Public Model 项目的代码与资源,项目包含一个微调的问答模型,用于回答公共卫生相关的问题并提供信息性回复。
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+
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+ ## 概述
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+
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+ 本项目提供用于回答公共卫生文档与主题相关问题的问答模型与配置。仓库包含微调后的模型、分词器配置、示例提示与输出,以及用于推理的脚本。
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+
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+ ## 文件与目录
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+
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+ - **adapter_config.json**:adapter 模型的配置。
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+ - **adapter_model.safetensors**:微调后的 adapter 模型权重。
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+ - **added_tokens.json**:新增词表的映射。
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+ - **all_results.json**:推理的输出示例与问答示例。
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+ - **train_results.json**:训练与验证的指标与明细。
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+ - **trainer_log.jsonl**:训练日志。
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+ - **trainer_state.json**:训练器状态。
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+ - **checkpoint-990/**:模型检查点目录。
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+
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+ ## 使用方法
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+
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+ 克隆仓库后,请参考主仓库(https://github.com/Jan8217/GlobalHealthAtlas)中的使用示例和工具链进行部署与推理。确保安装并配置好相应的依赖环境,然后按需加载 `adapter_model.safetensors` 与分词器文件执行推理(问答)。可以运行仓内提供的推理脚本或使用自己的提示循环进行交互式问答。该模型用于研究与信息查询场景,不应用作临床诊断或其他高风险决策。
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+
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+ ## 模型说明
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+
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+ 该模型是在 Qwen/Qwen3-8B 基础模型上,使用 `GlobalHealthAtlas` 数据集微调得到的:
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+
28
+ This model is a fine-tuned version of [/root/Qwen3-8B](https://huggingface.co//root/Qwen3-8B) on the GlobalHealthAtlas dataset.
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+
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+ **说明**:这是一个用于问答和信息检索的模型(Q&A)。具体使用与任务设置详见: https://github.com/Jan8217/GlobalHealthAtlas 。
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+
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+ ## 使用限制
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+
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+ 该模型适用于自动化评分与排序任务,不适用于临床诊断或高风险决策场景。部署前请在目标数据集上验证模型性能,注意可能存在的偏差,并在需要时由领域专家进行结果复核。
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+
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+ ## 训练与评估数据
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+
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+ 微调使用了 `GlobalHealthAtlas` 数据集;模型被调整用于问答与响应生成的任务。评估采用留出验证集进行,详细指标与示例输出记录在 `train_results.json` 和 `all_results.json` 中。有关数据预处理与任务设置的更多细节,请参阅 `Public_health/` 目录与 Global Health Atlas 项目页面。
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+
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+ ## 训练超参数(概要)
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+
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+ - learning_rate: 5e-05
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+ - train_batch_size: 1
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+ - eval_batch_size: 8
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+ - gradient_accumulation_steps: 8
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+ - num_epochs: 2
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+
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+ ## 训练结果
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+
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+ 训练完成 2 个 epoch。最终评估指标和分阶段日志保存在 `train_results.json`(数值指标)和 `trainer_log.jsonl`(训练日志)。
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+
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+ ## 环境依赖
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+
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+ - PEFT 0.15.1
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+ - Transformers 4.51.3
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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+
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+ ## 许可证
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+
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+ 本项目使用 MIT License(详见 LICENSE 文件)。
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+
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+ ## 致谢
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+
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+ 感谢所有贡献者与社区支持。如需进一步说明或帮助,请在仓库中提 issue。
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+ ---
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+ base_model: /root/autodl-tmp/LLM/Qwen3-8B
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+ library_name: peft
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+ pipeline_tag: text-generation
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+ tags:
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+ - base_model:adapter:/root/autodl-tmp/LLM/Qwen3-8B
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+ - llama-factory
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+ - lora
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+ - transformers
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+ ---
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+
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+ # Model Card for Model ID
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+
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+
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+
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+ ## Model Details
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+
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+ ### Model Description
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+
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+ <!-- Provide a longer summary of what this model is. -->
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+
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+
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+
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+ - **Developed by:** [More Information Needed]
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+ - **Funded by [optional]:** [More Information Needed]
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+ - **Shared by [optional]:** [More Information Needed]
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+ - **Model type:** [More Information Needed]
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+ - **Language(s) (NLP):** [More Information Needed]
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+ - **License:** [More Information Needed]
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+ - **Finetuned from model [optional]:** [More Information Needed]
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+
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+ ### Model Sources [optional]
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+
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+ <!-- Provide the basic links for the model. -->
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+
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+ - **Repository:** [More Information Needed]
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+ - **Paper [optional]:** [More Information Needed]
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+ - **Demo [optional]:** [More Information Needed]
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+
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+ ## Uses
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+
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+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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+
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+ ### Direct Use
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+
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+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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+
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+ [More Information Needed]
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+
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+ ### Downstream Use [optional]
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+
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+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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+
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+ [More Information Needed]
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+
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+ ### Out-of-Scope Use
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+
60
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ## Bias, Risks, and Limitations
65
+
66
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
67
+
68
+ [More Information Needed]
69
+
70
+ ### Recommendations
71
+
72
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
73
+
74
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
75
+
76
+ ## How to Get Started with the Model
77
+
78
+ Use the code below to get started with the model.
79
+
80
+ [More Information Needed]
81
+
82
+ ## Training Details
83
+
84
+ ### Training Data
85
+
86
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
87
+
88
+ [More Information Needed]
89
+
90
+ ### Training Procedure
91
+
92
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
93
+
94
+ #### Preprocessing [optional]
95
+
96
+ [More Information Needed]
97
+
98
+
99
+ #### Training Hyperparameters
100
+
101
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
102
+
103
+ #### Speeds, Sizes, Times [optional]
104
+
105
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
106
+
107
+ [More Information Needed]
108
+
109
+ ## Evaluation
110
+
111
+ <!-- This section describes the evaluation protocols and provides the results. -->
112
+
113
+ ### Testing Data, Factors & Metrics
114
+
115
+ #### Testing Data
116
+
117
+ <!-- This should link to a Dataset Card if possible. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Factors
122
+
123
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
124
+
125
+ [More Information Needed]
126
+
127
+ #### Metrics
128
+
129
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
130
+
131
+ [More Information Needed]
132
+
133
+ ### Results
134
+
135
+ [More Information Needed]
136
+
137
+ #### Summary
138
+
139
+
140
+
141
+ ## Model Examination [optional]
142
+
143
+ <!-- Relevant interpretability work for the model goes here -->
144
+
145
+ [More Information Needed]
146
+
147
+ ## Environmental Impact
148
+
149
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
150
+
151
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
152
+
153
+ - **Hardware Type:** [More Information Needed]
154
+ - **Hours used:** [More Information Needed]
155
+ - **Cloud Provider:** [More Information Needed]
156
+ - **Compute Region:** [More Information Needed]
157
+ - **Carbon Emitted:** [More Information Needed]
158
+
159
+ ## Technical Specifications [optional]
160
+
161
+ ### Model Architecture and Objective
162
+
163
+ [More Information Needed]
164
+
165
+ ### Compute Infrastructure
166
+
167
+ [More Information Needed]
168
+
169
+ #### Hardware
170
+
171
+ [More Information Needed]
172
+
173
+ #### Software
174
+
175
+ [More Information Needed]
176
+
177
+ ## Citation [optional]
178
+
179
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
180
+
181
+ **BibTeX:**
182
+
183
+ [More Information Needed]
184
+
185
+ **APA:**
186
+
187
+ [More Information Needed]
188
+
189
+ ## Glossary [optional]
190
+
191
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
192
+
193
+ [More Information Needed]
194
+
195
+ ## More Information [optional]
196
+
197
+ [More Information Needed]
198
+
199
+ ## Model Card Authors [optional]
200
+
201
+ [More Information Needed]
202
+
203
+ ## Model Card Contact
204
+
205
+ [More Information Needed]
206
+ ### Framework versions
207
+
208
+ - PEFT 0.17.1
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