Comments (3)
Hi, Could you please provide some details about your result reproducing? For example, which result.
from opera.
Hi, Could you please provide some details about your result reproducing? For example, which result.
The image above displays the results from your paper. However, following your instructions to modify transformers-4.31.0, I obtained the following values: CHAIRs=48.6 and CHAIRi=14.2. The parameters used were num_beams=5, max_new_tokens=512, and do_sample=false
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Hi, thanks for your interest!
To reproduce the CHAIR results, you might need to:
- Make sure set the correct
key_position
and the parameters in the generate function, as noted in TL;DR:
opera_decoding=True,
key_position=key_position,
scale_factor=50,
threshold=15,
num_attn_candidates=5,
penalty_weights=1,
- Use our provided codebase and transformers version (4.29.2). Different transformers versions may affects the final results.
- Most crucially, use our provided 500 sample list, given in log/chair_eval_results. Different sample selection greatly influence the CHAIR results.
BTW: We also provide our generated results in log/chair_eval_results. You can directly evaluate them with CHAIR evaluation tool. You can also do the experiments in your own codebase with a new sample selection, but the results may be different with the OPERA results in our paper.
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Related Issues (20)
- Does the method to find `knowledge aggregation pattern` have any relevant papers to reference in NLP domain? HOT 1
- Truncation of generated results HOT 3
- Could you provide the 'model.generate_output' function? HOT 2
- Shikra Version
- CHAIR hallucination evaluation HOT 2
- 关于是否是幻觉句子的问题 HOT 2
- 关于可视化 HOT 2
- 关于复现POPE的结果问题 HOT 14
- 可视化问题 HOT 4
- CUDA error: out of memory HOT 2
- Random 500 samples in MSCOCO HOT 2
- Discrepancy in Random Split Numbers for POPE (#2910 vs #3000) HOT 1
- Issue about visualization HOT 6
- Issue about the visual case provided in the paper HOT 1
- 您好,请问utils.py里面以下代码都为None,是什么导致的 HOT 6
- 请问是否可以在LMDeploy、vLLM等部署框架上使用?
- 热力图相关 HOT 1
- Request for Release of `GPT-4 assisted evaluation` Code HOT 1
- rollback question
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