Comments (4)
fathouse
commented on August 16, 2024
camera:
batch_size:16
max_test_acc_overall:95.6896551724138
max_f1_overall:63.26241933988123
batch_size:32
max_test_acc_overall:95.0
max_f1_overall:62.65156587737234
car:
batch_size:16
max_test_acc_overall:97.19298245614036
max_f1_overall:64.27432216905902
batch_size:32
max_test_acc_overall:97.19298245614036
max_f1_overall:64.27432216905902
notebook:
batch_size:16
max_test_acc_overall:92.90322580645162
max_f1_overall:61.1015911872705
batch_size:32
max_test_acc_overall:92.25806451612904
max_f1_overall:60.698241560775244
phone:
batch_size:16
max_test_acc_overall:96.63093415007657
max_f1_overall:64.07987611639298
batch_size:32
max_test_acc_overall:96.47779479326188
max_f1_overall:63.91524621082011
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fathouse
commented on August 16, 2024
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yangheng95
commented on August 16, 2024
应该是这里的原因https://github.com/yangheng95/LC-ABSA/blob/7285a57037b9b497c626b742a6a8c269ff3d482d/train_apc.py#L189，我现在没有时间修改，近几天会更新，请耐心等待修复
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fathouse
commented on August 16, 2024
谢谢您，我照着看看
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Related Issues (20)
- some bug in TUTORIALS of Aspect Term Extraction and Sentiment Classification HOT 1
- Attention mask not specified HOT 1
- 请问提取情感三元组是利用哪个算法实现的
- 请问情感三元组的提取是利用哪个算法实现的 HOT 1
- Max length in ASTE HOT 1
- Loading state_dict fails (model trained on linux and copied to windows) HOT 1
- RuntimeError: Error(s) in loading state_dict for APCEnsembler: HOT 1
- IndexError: Target 2 is out of bounds. HOT 3
- Aspect sentiment quadruple extraction
- 模型无法远程下载，如何从本地加载模型？ HOT 1
- 请问哪里可以设置integrated dataset path
- Fail to download checkpoints info from huggingface space, try to download from local HOT 1
- import AspectSentimentTripletExtraction in colab raise error HOT 4
- Fine-tuned ASTE model returns no triplets HOT 2
- The example code: Aspect_Term_Extraction.ipynb in the subfolder of aspect_term_extraction in examples-v2 is not working HOT 4
- PyABSA for German language? HOT 1
- No module named 'pyabsa.functional' HOT 4
- AspectExtractor returns aspects only if pred_sentiments=True in `extract_aspect` method but I don't want sentiments HOT 3
- how to train my own model? HOT 1
- Different performance between model saved as fine-tuned PLM and state_dict HOT 3
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