Open wangyuguo1 opened 1 day ago
【train】Epoch: 10/10 Step: 668/670 loss: 0.00103 【train】Epoch: 10/10 Step: 669/670 loss: 0.00121 【train】Epoch: 10/10 Step: 670/670 loss: 0.00136 [eval] precision=0.0341 recall=0.5020 f1_score=0.0639 precision recall f1-score support
风险类别 0.02 0.19 0.03 293 污染来源 0.01 0.40 0.02 241 分析方法 0.02 0.38 0.03 480
区域土壤类型 0.01 0.33 0.02 414 研究区域 0.08 0.50 0.14 225 污染物 0.04 0.59 0.08 2010
micro-f1 0.03 0.50 0.06 3663
if name == 'main': class Args: data_name = "tur" data_dir = 'D:/NER/pytorch_chinese_biaffine_ner-main/pytorch_chinese_biaffine_ner-main/data/{}/'.format(data_name)
train_path = os.path.join(data_dir, "train.json") dev_path = os.path.join(data_dir, "dev.json") test_path = os.path.join(data_dir, "test.json") bert_dir = "D:/NER/pytorch_chinese_biaffine_ner-main/pytorch_chinese_biaffine_ner-main/model_hub/chinese-bert-wwm-ext" save_dir = "D:/NER/pytorch_chinese_biaffine_ner-main/pytorch_chinese_biaffine_ner-main/checkpoints/{}/model.pt".format(data_name) ffnn_size = 256 max_seq_len = 512 train_epoch = 10 train_batch_size = 12 eval_batch_size= 12 eval_step = 100 lr = 3e-5 other_lr = 2e-3 adam_epsilon = 1e-8 warmup_proportion = 0.1 max_grad_norm = 1 weight_decay = 0.01 num_cls = 7#9 bias = True
数据量有多少。
不多1000条,但是我看别的模型识别的还可以基本上f1值也有80多
这类模型可能数据要多一点,然后训练更久一些。
【train】Epoch: 10/10 Step: 668/670 loss: 0.00103 【train】Epoch: 10/10 Step: 669/670 loss: 0.00121 【train】Epoch: 10/10 Step: 670/670 loss: 0.00136 [eval] precision=0.0341 recall=0.5020 f1_score=0.0639 precision recall f1-score support
区域土壤类型 0.01 0.33 0.02 414 研究区域 0.08 0.50 0.14 225 污染物 0.04 0.59 0.08 2010
micro-f1 0.03 0.50 0.06 3663
if name == 'main': class Args: data_name = "tur" data_dir = 'D:/NER/pytorch_chinese_biaffine_ner-main/pytorch_chinese_biaffine_ner-main/data/{}/'.format(data_name)