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Beam search #30
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We don't find a way to apply beam search. We tried to change the argmax to sample for achieving beam search, but the performance dropped. |
What’s the difference between “generate_diffusion” and “generate2_adpt_if”? Are they two different ways to generate text? Because I need two different decoding way to apply a technique of mine based on reinforcement learning (that’s why I asked for beam search, but basically I can try any other decoding way)
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Subject: Re: [buxiangzhiren/DDCap] Beam search (Issue #30)
We don't find a way to apply beam search. We tried to change the argmax to sample to achieve beam search, but the performance dropped.
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The difference is that “generate2_adpt_if”uses the image-free strategy in inference. Maybe you can change the variable "scale" to get different results. But I am not sure that the differences of results from various "scale" are great to support the reinforcement learning. |
Is there a range of possible “scale” parameter that I can try? Experiments set it to 1.06, which one should I set?
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Subject: Re: [buxiangzhiren/DDCap] Beam search (Issue #30)
The difference is that “generate2_adpt_if”uses the image-free strategy in inference. Maybe you can change the variable "scale" to get different results. But I am not sure that the differences of results from various "scale" are great to support the reinforcement learning.
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Thank you very much for your answers, it’s 3 months you’re replying me, now I’m going to try to apply reinforcement learning for my thesis. If you want, I can warn you about results
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Subject: Re: [buxiangzhiren/DDCap] Beam search (Issue #30)
The range was reported in Figure 4 of our paper. For various results, I suggest that you set the range 1~4. [image] <https://user-images.githubusercontent.com/67734862/226416522-79773c5e-a96b-4c27-9d79-2b1dddbcc2e7.png>
The results are reported in validation dataset. When "scale" is 1.06, our model can achieve the best performance in test dataset.
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Hi, is there a way to apply beam search in order to generate text?
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