问题描述

使用问答模型 damo/nlp_structbert_faq-question-answering_chinese-base 进行训练时，参照官方文档代码出现如下错误

** build_dataset error log: 'structbert is not in the custom_datasets registry group faq-question-answering. Please make sure the correct version of ModelScope library is used.'

官方地址

模型地址

使用的数据集格式 如下

调试完整代码

import os
from modelscope.metainfo import Trainers
from modelscope.msdatasets import MsDataset
from modelscope.pipelines import pipeline
from modelscope.trainers import build_trainer
from modelscope.utils.config import Config
from modelscope.utils.hub import read_config
  
train_dataset = MsDataset.load("./qa.csv", split='train').remap_columns({'text': 'text'})
print(train_dataset)
eval_dataset = train_dataset
cfg: Config = read_config("damo/nlp_structbert_faq-question-answering_chinese-base")
cfg.train.train_iters_per_epoch = 30
cfg.evaluation.val_iters_per_epoch = 2
cfg.train.seed = 1234
cfg.train.optimizer.lr = 2e-5
cfg.train.hooks = [{
    'type': 'CheckpointHook',
    'by_epoch': False,
    'interval': 50
}, {
    'type': 'EvaluationHook',
    'by_epoch': False,
    'interval': 50
}, {
    'type': 'TextLoggerHook',
    'by_epoch': False,
    'rounding_digits': 5,
    'interval': 10
}]
cfg_file = os.path.join("./model/temp", 'config.json')
cfg.dump(cfg_file)

trainer = build_trainer(
    Trainers.faq_question_answering_trainer,
    default_args=dict(
        model="damo/nlp_structbert_faq-question-answering_chinese-base",
        work_dir="./model/temp",
        train_dataset=train_dataset,
        eval_dataset=eval_dataset,
        cfg_file=cfg_file))

trainer.train()

evaluate_result = trainer.evaluate()
print(evaluate_result)

完整错误信息

Dataset({
    features: ['text', 'label', 'answer'],
    num_rows: 26
})
2023-06-26 20:32:21,659 - modelscope - INFO - initialize model from ./model/damo/nlp_structbert_faq-question-answering_chinese-base
2023-06-26 20:32:22,949 - modelscope - INFO - faq task build protonet network
2023-06-26 20:32:28,135 - modelscope - INFO - All model checkpoint weights were used when initializing SbertForFaqQuestionAnswering.

2023-06-26 20:32:28,136 - modelscope - INFO - All the weights of SbertForFaqQuestionAnswering were initialized from the model checkpoint If your task is similar to the task the model of the checkpoint was trained on, you can already use SbertForFaqQuestionAnswering for predictions without further training.
2023-06-26 20:32:28,137 - modelscope - WARNING - No train key and type key found in preprocessor domain of configuration.json file.
2023-06-26 20:32:28,138 - modelscope - WARNING - Cannot find available config to build preprocessor at mode train, current config: {'max_seq_length': 50, 'model_dir': './model/damo/nlp_structbert_faq-question-answering_chinese-base'}. trying to build by task and model information.
2023-06-26 20:32:28,172 - modelscope - WARNING - No val key and type key found in preprocessor domain of configuration.json file.
2023-06-26 20:32:28,172 - modelscope - WARNING - Cannot find available config to build preprocessor at mode eval, current config: {'max_seq_length': 50, 'model_dir': './model/damo/nlp_structbert_faq-question-answering_chinese-base'}. trying to build by task and model information.
2023-06-26 20:32:28,185 - modelscope - WARNING - ('CUSTOM_DATASETS', 'faq-question-answering', 'structbert') not found in ast index file
2023-06-26 20:32:28,186 - modelscope - WARNING - ('CUSTOM_DATASETS', 'faq-question-answering', 'structbert') not found in ast index file
2023-06-26 20:32:28,187 - modelscope - INFO - cuda is not available, using cpu instead.
2023-06-26 20:32:28,187 - modelscope - INFO - ==========================Training Config Start==========================
2023-06-26 20:32:28,187 - modelscope - INFO - {
    "framework": "pytorch",
    "task": "faq-question-answering",
    "pipeline": {
        "type": "faq-question-answering"
    },
    "model": {
        "type": "structbert",
        "pooling": "avg",
        "metric": "relation"
    },
    "preprocessor": {
        "max_seq_length": 50,
        "model_dir": "./model/damo/nlp_structbert_faq-question-answering_chinese-base"
    },
    "train": {
        "seed": 1234,
        "hooks": [
            {
                "type": "IterTimerHook"
            }
        ],
        "train_iters_per_epoch": 30,
        "max_epochs": 1,
        "sampler": {
            "n_way": 5,
            "k_shot": 5,
            "r_query": 5,
            "min_labels": 2
        },
        "optimizer": {
            "type": "Adam",
            "lr": 2e-05,
            "options": {
                "grad_clip": {
                    "max_norm": 5.0
                }
            }
        },
        "lr_scheduler": {
            "type": "LinearLR",
            "options": {
                "by_epoch": false
            }
        },
        "dataloader": {
            "workers_per_gpu": 1
        },
        "checkpoint": {
            "period": {
                "by_epoch": false,
                "interval": 50
            }
        },
        "logging": {
            "by_epoch": false,
            "rounding_digits": 5,
            "interval": 10
        },
        "work_dir": "./model/temp"
    },
    "evaluation": {
        "metrics": "seq-cls-metric",
        "val_iters_per_epoch": 2,
        "dataloader": {
            "workers_per_gpu": 1
        },
        "period": {
            "by_epoch": false,
            "interval": 50
        }
    }
}
2023-06-26 20:32:28,188 - modelscope - INFO - ===========================Training Config End===========================
2023-06-26 20:32:28,190 - modelscope - INFO - num. of bad sample ids:5/26
2023-06-26 20:32:28,192 - modelscope - INFO - train: label size:3.0, data size:18,                 domain_size:1
2023-06-26 20:32:28,193 - modelscope - WARNING - ('OPTIMIZER', 'default', 'Adam') not found in ast index file
2023-06-26 20:32:28,194 - modelscope - WARNING - ('LR_SCHEDULER', 'default', 'LinearLR') not found in ast index file
2023-06-26 20:32:28,194 - modelscope - INFO - Stage: before_run:
    (ABOVE_NORMAL) OptimizerHook                      
    (LOW         ) LrSchedulerHook                    
    (LOW         ) CheckpointHook                     
    (VERY_LOW    ) TextLoggerHook                     
 -------------------- 
Stage: before_train_epoch:
    (LOW         ) LrSchedulerHook                    
 -------------------- 
Stage: before_train_iter:
    (ABOVE_NORMAL) OptimizerHook                      
 -------------------- 
Stage: after_train_iter:
    (ABOVE_NORMAL) OptimizerHook                      
    (NORMAL      ) EvaluationHook                     
    (LOW         ) LrSchedulerHook                    
    (LOW         ) CheckpointHook                     
    (VERY_LOW    ) TextLoggerHook                     
 -------------------- 
Stage: after_train_epoch:
    (NORMAL      ) EvaluationHook                     
    (LOW         ) LrSchedulerHook                    
    (LOW         ) CheckpointHook                     
    (VERY_LOW    ) TextLoggerHook                     
 -------------------- 
Stage: after_val_epoch:
    (VERY_LOW    ) TextLoggerHook                     
 -------------------- 
Stage: after_run:
    (LOW         ) CheckpointHook                     
 -------------------- 
2023-06-26 20:32:28,197 - modelscope - INFO - Checkpoints will be saved to ./model/temp
2023-06-26 20:32:28,197 - modelscope - INFO - Text logs will be saved to ./model/temp
** build_dataset error log: 'structbert is not in the custom_datasets registry group faq-question-answering. Please make sure the correct version of ModelScope library is used.'
** build_dataset error log: 'structbert is not in the custom_datasets registry group faq-question-answering. Please make sure the correct version of ModelScope library is used.'