declare-lab
Baseline results=0
Hi, I have tried the bc_LSTM baseline with bimodal in emotion classification, but the F1-score and accuracy of 'fear' and 'disgust' are always zero, so I can't reproduce the result in paper.
The command I use:
python baseline.py -classify emotion -modality bimodal -train
The results:
precision recall f1-score support
0 0.7322 0.7795 0.7551 1256
1 0.4799 0.4662 0.4729 281
2 0.0000 0.0000 0.0000 50
3 0.2781 0.2019 0.2340 208
4 0.4813 0.5448 0.5111 402
5 0.0000 0.0000 0.0000 68
6 0.3832 0.4377 0.4087 345
The emotion labels:
Emotion - {'neutral': 0, 'surprise': 1, 'fear': 2, 'sadness': 3, 'joy': 4, 'disgust': 5, 'anger': 6}.
I know the main strategy is to adjust the class weight. To be hnoest, I'm new to tensorflow. I don't know what codes are needed to add to achieve it. Could you please give me some suggestion?
Best wishes>
Hi, I have tried the bc_LSTM baseline with bimodal in emotion classification, but the F1-score and accuracy of 'fear' and 'disgust' are always zero, so I can't reproduce the result in paper.你好，我在情感分类中尝试了双峰的 bc_LSTM 基线，但“恐惧”和“厌恶”的 F1 分数和准确度始终为零，因此我无法在论文中重现结果。
The command I use: 我使用的命令：
python baseline.py -classify emotion -modality bimodal -trainpython基线.py-分类情感-模态双峰-train
The results: 结果：
precision recall f1-score support 0 0.7322 0.7795 0.7551 1256 1 0.4799 0.4662 0.4729 281 2 0.0000 0.0000 0.0000 50 3 0.2781 0.2019 0.2340 208 4 0.4813 0.5448 0.5111 402 5 0.0000 0.0000 0.0000 68 6 0.3832 0.4377 0.4087 345The emotion labels: 情绪标签：
Emotion - {'neutral': 0, 'surprise': 1, 'fear': 2, 'sadness': 3, 'joy': 4, 'disgust': 5, 'anger': 6}.情绪 - {'中性': 0, '惊讶': 1, '恐惧': 2, '悲伤': 3, '喜悦': 4, '厌恶': 5, '愤怒': 6}。
I know the main strategy is to adjust the class weight. To be hnoest, I'm new to tensorflow. I don't know what codes are needed to add to achieve it. Could you please give me some suggestion?我知道主要策略是调整班级权重。老实说，我是张量流的新手。我不知道需要添加什么代码才能实现。您能给我一些建议吗？
Best wishes> 最美好的祝愿>
Same for me!May I asked If you've solved it?
