DCAgent3/medagentbench_rl__24GPU_base_lr5e_6__exp_rpt_pymethods2test_large__GLM_4_7_swescb565060

该数据集是一个包含对话记录和相关元数据的集合，主要用于多任务或多代理场景的分析。数据集特征包括对话（conversations，其中每条对话包含角色和内容）、代理（agent）、模型（model）、模型提供者（model_provider）、日期（date）、任务（task）、剧集（episode）、运行ID（run_id）、试验名称（trial_name）、结果（result）、验证器输出（verifier_output）和跟踪来源（trace_source）。数据集仅包含训练分割，有947个示例，总大小约为34.6 MB。基于特征推断，该数据集可能用于评估或训练AI代理在特定任务中的表现，但具体用途和背景未在README中说明。This dataset is a collection of conversation records and associated metadata, primarily designed for analysis in multi-task or multi-agent scenarios. Its core features include conversations (each conversation contains a speaker role and its corresponding content), agent, model, model_provider, date, task, episode, run_id, trial_name, result, verifier_output, and trace_source. The dataset only contains the training split, with 947 examples in total and an approximate overall size of 34.6 MB. Based on inference from its features, this dataset may be used to evaluate or train the performance of AI Agents on specific tasks, but its specific intended uses and background are not specified in the README.