Comments (3)
airaria
commented on June 7, 2024
我这边12层到12层的效果可以参见
https://textbrewer.readthedocs.io/en/latest/Experiments.html
页面上的T12-nano(英文BERT)和electra-small(中文electra) 相关结果。
使用的match是 examples/matches/matches.py 中的small_hidden_smmd和small_hidden_mse。
最近有篇论文（Improving Task-Agnostic BERT Distillation with Layer Mapping Search）搜索了各种层对应策略，你可以参考下。
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652994331
commented on June 7, 2024
@airaria 感谢您的回复
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sxthunder
commented on June 7, 2024
请问您蒸馏的是什么任务啊？可以交流一下吗？
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Related Issues (20)
- pre-trained student weights HOT 3
- Where to find gs4210.pkl file or how to generate it ? thanks HOT 2
- interpreting intermediate matches HOT 5
- Show the progress bar when training. HOT 3
- Picking right layers HOT 3
- How about the distillation effect of gpt2 ？ HOT 2
- Does it support translation model? HOT 2
- 在VisionTransformer HOT 7
- 关于ner数据的处理 HOT 2
- notebook_examples/msra_ner.ipynb 运行报错 HOT 12
- 不同维度蒸馏有对应的例子吗，从768降到256 HOT 4
- msra_ner.ipynb最后的trainer.evaluate()显示CUDA out of memory，请问训练的显存要求是多大？十分感谢！ HOT 2
- 老师，您好，请问有多任务多教师的蒸馏的demo吗？ HOT 4
- 老师您好，我想问一下，比如roberta蒸馏到tinybert，中间的hidden是通过线性层拉到同样的维度去算mse，那在推理的时候岂不是这些经过梯度更新的线性层毫无作用？那请问这些线性层仅仅就是为了调整维度？ HOT 2
- 蒸馏后的模型进行evaluate，报错AxisError: axis 2 is out of bounds for array of dimension 1 HOT 5
- 可以使用chatgpt蒸馏到bert或者T5吗？ HOT 2
- 麻烦问下，目前支持llama模型吗 HOT 2
- 请问支持BERT-of-Theseus的蒸馏方式吗 HOT 3
- 学生模型权重初始化问题 HOT 2
- TextBrewer/src/textbrewer/distiller_utils.py get_outputs_from_batch fails tocheck dicts properly for maskedLM HOT 4
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