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@ -188,17 +188,17 @@ class MLModel:
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# 打印训练和验证过程的可视化图片
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plt.close('all')
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fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(15, 5))
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ax1.plot(train_loss_history, label='Train Loss(训练损失)', fontproperties=font_prop)
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ax1.plot(val_loss_history, label='Validation Loss(验证损失)', fontproperties=font_prop)
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ax1.plot(train_loss_history, label='Train Loss(训练损失)')
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ax1.plot(val_loss_history, label='Validation Loss(验证损失)')
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ax1.set_title('Loss(损失)', fontproperties=font_prop)
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ax1.legend()
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ax2.plot(train_acc_history, label='Train Accuracy(训练正确率)', fontproperties=font_prop)
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ax2.plot(val_acc_history, label='Validation Accuracy(验证正确率)', fontproperties=font_prop)
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ax2.plot(train_acc_history, label='Train Accuracy(训练正确率)')
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ax2.plot(val_acc_history, label='Validation Accuracy(验证正确率)')
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ax2.set_title('Accuracy(正确率)', fontproperties=font_prop)
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ax2.legend()
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ax3.plot(val_f1_history, label='Validation F1(验证F1得分)', fontproperties=font_prop)
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ax3.plot(val_precision_history, label='Validation Precision(验证精确率)', fontproperties=font_prop)
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ax3.plot(val_recall_history, label='Validation Recall(验证召回率)', fontproperties=font_prop)
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ax3.plot(val_f1_history, label='Validation F1(验证F1得分)')
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ax3.plot(val_precision_history, label='Validation Precision(验证精确率)')
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ax3.plot(val_recall_history, label='Validation Recall(验证召回率)')
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ax3.set_title('Precision Recall F1-Score (Macro Mean)(宏平均)', fontproperties=font_prop)
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ax3.legend()
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# 保存图片
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