add longbench

lm_eval/tasks/longbench/passage_count_e.yaml

+
+tag:
+  - longbench_e
+task: longbench_passage_count_e
+dataset_path: THUDM/LongBench
+test_split: test
+dataset_name: passage_count_e
+doc_to_text: 'There are some paragraphs below sourced from Wikipedia. Some of them may be duplicates. Please carefully read these paragraphs and determine how many unique paragraphs there are after removing duplicates. In other words, how many non-repeating paragraphs are there in total?\n\n{{context}}\n\nPlease enter the final count of unique paragraphs after removing duplicates. The output format should only contain the number, such as 1, 2, 3, and so on.\n\nThe final answer is: '
+doc_to_target: '{{answers}}'
+generation_kwargs:
+  max_gen_toks: 32
+  temperature: 1
+  do_sample: False
+metric_list:
+  - metric: !function metrics.count_score
+    aggregation: mean
+    higher_is_better: True
+metadata:
+  version: 1.0

lm_eval/tasks/longbench/passage_retrieval_en.yaml

+
+tag:
+  - longbench
+task: longbench_passage_retrieval_en
+dataset_path: THUDM/LongBench
+test_split: test
+dataset_name: passage_retrieval_en
+doc_to_text: 'Here are 30 paragraphs from Wikipedia, along with an abstract. Please determine which paragraph the abstract is from.\n\n{{context}}\n\nThe following is an abstract.\n\n{{input}}\n\nPlease enter the number of the paragraph that the abstract is from. The answer format must be like "Paragraph 1", "Paragraph 2", etc.\n\nThe answer is: '
+doc_to_target: '{{answers}}'
+generation_kwargs:
+  max_gen_toks: 32
+  temperature: 1
+  do_sample: False
+metric_list:
+  - metric: !function metrics.retrieval_score
+    aggregation: mean
+    higher_is_better: True
+metadata:
+  version: 1.0

lm_eval/tasks/longbench/passage_retrieval_en_e.yaml

+
+tag:
+  - longbench_e
+task: longbench_passage_retrieval_en_e
+dataset_path: THUDM/LongBench
+test_split: test
+dataset_name: passage_retrieval_en_e
+doc_to_text: 'Here are 30 paragraphs from Wikipedia, along with an abstract. Please determine which paragraph the abstract is from.\n\n{{context}}\n\nThe following is an abstract.\n\n{{input}}\n\nPlease enter the number of the paragraph that the abstract is from. The answer format must be like "Paragraph 1", "Paragraph 2", etc.\n\nThe answer is: '
+doc_to_target: '{{answers}}'
+generation_kwargs:
+  max_gen_toks: 32
+  temperature: 1
+  do_sample: False
+metric_list:
+  - metric: !function metrics.retrieval_score
+    aggregation: mean
+    higher_is_better: True
+metadata:
+  version: 1.0

lm_eval/tasks/longbench/passage_retrieval_zh.yaml

+
+tag:
+  - longbench
+task: longbench_passage_retrieval_zh
+dataset_path: THUDM/LongBench
+test_split: test
+dataset_name: passage_retrieval_zh
+doc_to_text: '以下是若干段落文字，以及其中一个段落的摘要。请确定给定的摘要出自哪一段。\n\n{{context}}\n\n下面是一个摘要\n\n{{input}}\n\n请输入摘要所属段落的编号。答案格式必须是"段落1"，"段落2"等格式\n\n答案是：'
+doc_to_target: '{{answers}}'
+generation_kwargs:
+  max_gen_toks: 32
+  temperature: 1
+  do_sample: False
+metric_list:
+  - metric: !function metrics.retrieval_zh_score
+    aggregation: mean
+    higher_is_better: True
+metadata:
+  version: 1.0

lm_eval/tasks/longbench/qasper.yaml

+
+tag:
+  - longbench
+task: longbench_qasper
+dataset_path: THUDM/LongBench
+test_split: test
+dataset_name: qasper
+doc_to_text: 'You are given a scientific article and a question. Answer the question as concisely as you can, using a single phrase or sentence if possible. If the question cannot be answered based on the information in the article, write "unanswerable". If the question is a yes/no question, answer "yes", "no", or "unanswerable". Do not provide any explanation.\n\nArticle: {{context}}\n\n Answer the question based on the above article as concisely as you can, using a single phrase or sentence if possible. If the question cannot be answered based on the information in the article, write "unanswerable". If the question is a yes/no question, answer "yes", "no", or "unanswerable". Do not provide any explanation.\n\nQuestion: {{input}}\n\nAnswer:'
+doc_to_target: '{{answers}}'
+generation_kwargs:
+  max_gen_toks: 128
+  temperature: 1
+  do_sample: False
+metric_list:
+  - metric: !function metrics.qa_f1_score
+    aggregation: mean
+    higher_is_better: True
+metadata:
+  version: 1.0

lm_eval/tasks/longbench/qasper_e.yaml

+
+tag:
+  - longbench_e
+task: longbench_qasper_e
+dataset_path: THUDM/LongBench
+test_split: test
+dataset_name: qasper_e
+doc_to_text: 'You are given a scientific article and a question. Answer the question as concisely as you can, using a single phrase or sentence if possible. If the question cannot be answered based on the information in the article, write "unanswerable". If the question is a yes/no question, answer "yes", "no", or "unanswerable". Do not provide any explanation.\n\nArticle: {{context}}\n\n Answer the question based on the above article as concisely as you can, using a single phrase or sentence if possible. If the question cannot be answered based on the information in the article, write "unanswerable". If the question is a yes/no question, answer "yes", "no", or "unanswerable". Do not provide any explanation.\n\nQuestion: {{input}}\n\nAnswer:'
+doc_to_target: '{{answers}}'
+generation_kwargs:
+  max_gen_toks: 128
+  temperature: 1
+  do_sample: False
+metric_list:
+  - metric: !function metrics.qa_f1_score
+    aggregation: mean
+    higher_is_better: True
+metadata:
+  version: 1.0

lm_eval/tasks/longbench/qmsum.yaml

+
+tag:
+  - longbench
+task: longbench_qmsum
+dataset_path: THUDM/LongBench
+test_split: test
+dataset_name: qmsum
+doc_to_text: 'You are given a meeting transcript and a query containing a question or instruction. Answer the query in one or more sentences.\n\nTranscript:\n{{context}}\n\nNow, answer the query based on the above meeting transcript in one or more sentences.\n\nQuery: {{input}}\nAnswer:'
+doc_to_target: '{{answers}}'
+generation_kwargs:
+  max_gen_toks: 512
+  temperature: 1
+  do_sample: False
+metric_list:
+  - metric: !function metrics.rouge_score
+    aggregation: mean
+    higher_is_better: True
+metadata:
+  version: 1.0

lm_eval/tasks/longbench/repobench-p.yaml

+
+tag:
+  - longbench
+task: longbench_repobench-p
+dataset_path: THUDM/LongBench
+test_split: test
+dataset_name: repobench-p
+doc_to_text: 'Please complete the code given below. \n{{context}}{{input}}Next line of code:\n'
+doc_to_target: '{{answers}}'
+generation_kwargs:
+  max_gen_toks: 64
+  temperature: 1
+  do_sample: False
+metric_list:
+  - metric: !function metrics.code_sim_score
+    aggregation: mean
+    higher_is_better: True
+metadata:
+  version: 1.0

lm_eval/tasks/longbench/repobench-p_e.yaml

+
+tag:
+  - longbench_e
+task: longbench_repobench-p_e
+dataset_path: THUDM/LongBench
+test_split: test
+dataset_name: repobench-p_e
+doc_to_text: 'Please complete the code given below. \n{{context}}{{input}}Next line of code:\n'
+doc_to_target: '{{answers}}'
+generation_kwargs:
+  max_gen_toks: 64
+  temperature: 1
+  do_sample: False
+metric_list:
+  - metric: !function metrics.code_sim_score
+    aggregation: mean
+    higher_is_better: True
+metadata:
+  version: 1.0

lm_eval/tasks/longbench/samsum.yaml

+
+tag:
+  - longbench
+task: longbench_samsum
+dataset_path: THUDM/LongBench
+test_split: test
+dataset_name: samsum
+doc_to_text: 'Summarize the dialogue into a few short sentences. The following are some examples.\n\n{{context}}\n\n{{input}}'
+doc_to_target: '{{answers}}'
+generation_kwargs:
+  max_gen_toks: 128
+  temperature: 1
+  do_sample: False
+metric_list:
+  - metric: !function metrics.rouge_score
+    aggregation: mean
+    higher_is_better: True
+metadata:
+  version: 1.0

lm_eval/tasks/longbench/samsum_e.yaml

+
+tag:
+  - longbench_e
+task: longbench_samsum_e
+dataset_path: THUDM/LongBench
+test_split: test
+dataset_name: samsum_e
+doc_to_text: 'Summarize the dialogue into a few short sentences. The following are some examples.\n\n{{context}}\n\n{{input}}'
+doc_to_target: '{{answers}}'
+generation_kwargs:
+  max_gen_toks: 128
+  temperature: 1
+  do_sample: False
+metric_list:
+  - metric: !function metrics.rouge_score
+    aggregation: mean
+    higher_is_better: True
+metadata:
+  version: 1.0

lm_eval/tasks/longbench/trec.yaml

+
+tag:
+  - longbench
+task: longbench_trec
+dataset_path: THUDM/LongBench
+test_split: test
+dataset_name: trec
+doc_to_text: 'Please determine the type of the question below. Here are some examples of questions.\n\n{{context}}\n{{input}}'
+doc_to_target: '{{answers}}'
+generation_kwargs:
+  max_gen_toks: 64
+  temperature: 1
+  do_sample: False
+metric_list:
+  - metric: !function metrics.classification_score
+    aggregation: mean
+    higher_is_better: True
+metadata:
+  version: 1.0

lm_eval/tasks/longbench/trec_e.yaml

+
+tag:
+  - longbench_e
+task: longbench_trec_e
+dataset_path: THUDM/LongBench
+test_split: test
+dataset_name: trec_e
+doc_to_text: 'Please determine the type of the question below. Here are some examples of questions.\n\n{{context}}\n{{input}}'
+doc_to_target: '{{answers}}'
+generation_kwargs:
+  max_gen_toks: 64
+  temperature: 1
+  do_sample: False
+metric_list:
+  - metric: !function metrics.classification_score
+    aggregation: mean
+    higher_is_better: True
+metadata:
+  version: 1.0

lm_eval/tasks/longbench/triviaqa.yaml

+
+tag:
+  - longbench
+task: longbench_triviaqa
+dataset_path: THUDM/LongBench
+test_split: test
+dataset_name: triviaqa
+doc_to_text: 'Answer the question based on the given passage. Only give me the answer and do not output any other words. The following are some examples.\n\n{{context}}\n\n{{input}}'
+doc_to_target: '{{answers}}'
+generation_kwargs:
+  max_gen_toks: 32
+  temperature: 1
+  do_sample: False
+metric_list:
+  - metric: !function metrics.qa_f1_score
+    aggregation: mean
+    higher_is_better: True
+metadata:
+  version: 1.0

lm_eval/tasks/longbench/triviaqa_e.yaml

+
+tag:
+  - longbench_e
+task: longbench_triviaqa_e
+dataset_path: THUDM/LongBench
+test_split: test
+dataset_name: triviaqa_e
+doc_to_text: 'Answer the question based on the given passage. Only give me the answer and do not output any other words. The following are some examples.\n\n{{context}}\n\n{{input}}'
+doc_to_target: '{{answers}}'
+generation_kwargs:
+  max_gen_toks: 32
+  temperature: 1
+  do_sample: False
+metric_list:
+  - metric: !function metrics.qa_f1_score
+    aggregation: mean
+    higher_is_better: True
+metadata:
+  version: 1.0