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比如,微调模型的配置如下
--max_steps 3000 \ --save_steps 5\
这样保存的checkpoint就会从5, 10, 15, 20, ..., 3000。这样就保存太多checkpoint了。
我想跳过step小于2000的部分,就是只保存checkpoint从 2000, 2005, 2010, ..., 3000。请问应该如何配置呢?
No response
OS: Ubuntu 20.04 Python: 3.8 Transformers: 4.26.1 PyTorch: 1.12 CUDA Support: True
The text was updated successfully, but these errors were encountered:
(1)可以先训练一个2000的,设置 --max_steps 2000 --save_steps 2000 (2)然后在上面继续训练,设置 --max_steps 3000 --save_steps 5
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感谢回复,这也是个思路。 请问有没有能直接一次训练就能做到的方法?因为有些平台上提交训练没法中断后再接着训练这样操作
(1)可以先训练一个2000的,设置 --max_steps 2000 --save_steps 2000 (2)然后在上面继续训练,设置 --max_steps 3000 --save_steps 5 感谢回复,这也是个思路。 请问有没有能直接一次训练就能做到的方法?因为有些平台上提交训练没法中断后再接着训练这样操作
这个我就不太知道了,抱歉
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Current Behavior
比如,微调模型的配置如下
这样保存的checkpoint就会从5, 10, 15, 20, ..., 3000。这样就保存太多checkpoint了。
我想跳过step小于2000的部分,就是只保存checkpoint从 2000, 2005, 2010, ..., 3000。请问应该如何配置呢?
Expected Behavior
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Steps To Reproduce
Environment
Anything else?
No response
The text was updated successfully, but these errors were encountered: