dataset_path: facebook/PLM-VideoBench
dataset_name: sgqa
task: sgqa_test
test_split: test
output_type: generate_until

doc_to_visual: !function sgqa_utils.plm_sgqa_doc_to_visual
doc_to_text: !function sgqa_utils.plm_sgqa_doc_to_text
doc_to_target: "answer"

generation_kwargs:
  max_new_tokens: 16
  temperature: 0

process_results: !function sgqa_utils.plm_sgqa_process_results

metric_list:
  - metric: plm_sgqa_scores
    aggregation: !function sgqa_utils.plm_sgqa_aggregate_results
    higher_is_better: true

lmms_eval_specific_kwargs:
  default:
    prompt: "The following question is asked by the camera wearer at the end of the video.  Provide a detailed answer even if unsure.  Try to answer in around 20-30 words.  Now answer the following question based on the video content: {question}{answer}"

metadata:
  - version: 0.0
