Fix LongBench Evaluation (#3273)

* fix: set 'do_sample=False' and use double quotes in 'doc_to_text'

* feat: update versions and README for longbench

* pacify pre-commit

---------
Co-authored-by: Baber <baber@hey.com>

lm_eval/tasks/longbench/passage_count_e.yaml

@@ -5,17 +5,17 @@ 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_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}}'
 process_results: !function metrics.get_count_score
 generation_kwargs:
   max_gen_toks: 32
   temperature: 1
-  do_sample: True
+  do_sample: False
   until: []
 metric_list:
   - metric: "count_score"
     aggregation: mean
     higher_is_better: True
 metadata:
-  version: 3.0
+  version: 4.0

lm_eval/tasks/longbench/passage_retrieval_en.yaml

@@ -5,17 +5,17 @@ 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_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}}'
 process_results: !function metrics.get_retrieval_score
 generation_kwargs:
   max_gen_toks: 32
   temperature: 1
-  do_sample: True
+  do_sample: False
   until: []
 metric_list:
   - metric: "retrieval_score"
     aggregation: mean
     higher_is_better: True
 metadata:
-  version: 3.0
+  version: 4.0

lm_eval/tasks/longbench/passage_retrieval_en_e.yaml

@@ -5,17 +5,17 @@ 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_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}}'
 process_results: !function metrics.get_retrieval_score
 generation_kwargs:
   max_gen_toks: 32
   temperature: 1
-  do_sample: True
+  do_sample: False
   until: []
 metric_list:
   - metric: "retrieval_score"
     aggregation: mean
     higher_is_better: True
 metadata:
-  version: 3.0
+  version: 4.0

lm_eval/tasks/longbench/passage_retrieval_zh.yaml

@@ -5,17 +5,17 @@ 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_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}}'
 process_results: !function metrics.get_retrieval_zh_score
 generation_kwargs:
   max_gen_toks: 32
   temperature: 1
-  do_sample: True
+  do_sample: False
   until: []
 metric_list:
   - metric: "retrieval_zh_score"
     aggregation: mean
     higher_is_better: True
 metadata:
-  version: 3.0
+  version: 4.0

lm_eval/tasks/longbench/qasper.yaml

@@ -5,17 +5,17 @@ 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_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}}'
 process_results: !function metrics.get_qa_f1_score
 generation_kwargs:
   max_gen_toks: 128
   temperature: 1
-  do_sample: True
+  do_sample: False
   until: []
 metric_list:
   - metric: "qa_f1_score"
     aggregation: mean
     higher_is_better: True
 metadata:
-  version: 3.0
+  version: 4.0

lm_eval/tasks/longbench/qasper_e.yaml

@@ -5,17 +5,17 @@ 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_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}}'
 process_results: !function metrics.get_qa_f1_score
 generation_kwargs:
   max_gen_toks: 128
   temperature: 1
-  do_sample: True
+  do_sample: False
   until: []
 metric_list:
   - metric: "qa_f1_score"
     aggregation: mean
     higher_is_better: True
 metadata:
-  version: 3.0
+  version: 4.0

lm_eval/tasks/longbench/qmsum.yaml

@@ -5,17 +5,17 @@ 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_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}}'
 process_results: !function metrics.get_rouge_score
 generation_kwargs:
   max_gen_toks: 512
   temperature: 1
-  do_sample: True
+  do_sample: False
   until: []
 metric_list:
   - metric: "rouge_score"
     aggregation: mean
     higher_is_better: True
 metadata:
-  version: 3.0
+  version: 4.0

lm_eval/tasks/longbench/repobench-p.yaml

@@ -5,17 +5,17 @@ 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_text: "Please complete the code given below. \n{{context}}{{input}}Next line of code:\n"
 doc_to_target: '{{answers}}'
 process_results: !function metrics.get_code_sim_score
 generation_kwargs:
   max_gen_toks: 64
   temperature: 1
-  do_sample: True
+  do_sample: False
   until: []
 metric_list:
   - metric: "code_sim_score"
     aggregation: mean
     higher_is_better: True
 metadata:
-  version: 3.0
+  version: 4.0

lm_eval/tasks/longbench/repobench-p_e.yaml

@@ -5,17 +5,17 @@ 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_text: "Please complete the code given below. \n{{context}}{{input}}Next line of code:\n"
 doc_to_target: '{{answers}}'
 process_results: !function metrics.get_code_sim_score
 generation_kwargs:
   max_gen_toks: 64
   temperature: 1
-  do_sample: True
+  do_sample: False
   until: []
 metric_list:
   - metric: "code_sim_score"
     aggregation: mean
     higher_is_better: True
 metadata:
-  version: 3.0
+  version: 4.0

lm_eval/tasks/longbench/samsum.yaml

@@ -5,17 +5,17 @@ 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_text: "Summarize the dialogue into a few short sentences. The following are some examples.\n\n{{context}}\n\n{{input}}"
 doc_to_target: '{{answers}}'
 process_results: !function metrics.get_rouge_score
 generation_kwargs:
   max_gen_toks: 128
   temperature: 1
-  do_sample: True
+  do_sample: False
   until: ["\n"]
 metric_list:
   - metric: "rouge_score"
     aggregation: mean
     higher_is_better: True
 metadata:
-  version: 3.0
+  version: 4.0

lm_eval/tasks/longbench/samsum_e.yaml

@@ -5,17 +5,17 @@ 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_text: "Summarize the dialogue into a few short sentences. The following are some examples.\n\n{{context}}\n\n{{input}}"
 doc_to_target: '{{answers}}'
 process_results: !function metrics.get_rouge_score
 generation_kwargs:
   max_gen_toks: 128
   temperature: 1
-  do_sample: True
+  do_sample: False
   until: ["\n"]
 metric_list:
   - metric: "rouge_score"
     aggregation: mean
     higher_is_better: True
 metadata:
-  version: 3.0
+  version: 4.0

lm_eval/tasks/longbench/trec.yaml

@@ -5,17 +5,17 @@ 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_text: "Please determine the type of the question below. Here are some examples of questions.\n\n{{context}}\n{{input}}"
 doc_to_target: '{{answers}}'
 process_results: !function metrics.get_classification_score
 generation_kwargs:
   max_gen_toks: 64
   temperature: 1
-  do_sample: True
+  do_sample: False
   until: ["\n"]
 metric_list:
   - metric: "classification_score"
     aggregation: mean
     higher_is_better: True
 metadata:
-  version: 3.0
+  version: 4.0

lm_eval/tasks/longbench/trec_e.yaml

@@ -5,17 +5,17 @@ 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_text: "Please determine the type of the question below. Here are some examples of questions.\n\n{{context}}\n{{input}}"
 doc_to_target: '{{answers}}'
 process_results: !function metrics.get_classification_score
 generation_kwargs:
   max_gen_toks: 64
   temperature: 1
-  do_sample: True
+  do_sample: False
   until: ["\n"]
 metric_list:
   - metric: "classification_score"
     aggregation: mean
     higher_is_better: True
 metadata:
-  version: 3.0
+  version: 4.0

lm_eval/tasks/longbench/triviaqa.yaml

@@ -5,17 +5,17 @@ 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_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}}'
 process_results: !function metrics.get_qa_f1_score
 generation_kwargs:
   max_gen_toks: 32
   temperature: 1
-  do_sample: True
+  do_sample: False
   until: ["\n"]
 metric_list:
   - metric: "qa_f1_score"
     aggregation: mean
     higher_is_better: True
 metadata:
-  version: 3.0
+  version: 4.0

lm_eval/tasks/longbench/triviaqa_e.yaml

@@ -5,17 +5,17 @@ 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_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}}'
 process_results: !function metrics.get_qa_f1_score
 generation_kwargs:
   max_gen_toks: 32
   temperature: 1
-  do_sample: True
+  do_sample: False
   until: ["\n"]
 metric_list:
   - metric: "qa_f1_score"
     aggregation: mean
     higher_is_better: True
 metadata:
-  version: 3.0
+  version: 4.0

lm_eval/tasks/longbench/vcsum.yaml

@@ -5,17 +5,17 @@ task: longbench_vcsum
 dataset_path: THUDM/LongBench
 test_split: test
 dataset_name: vcsum
-doc_to_text: '下面有一段会议记录，请你阅读后，写一段总结，总结会议的内容。\n会议记录：\n{{context}}\n\n会议总结：'
+doc_to_text: "下面有一段会议记录，请你阅读后，写一段总结，总结会议的内容。\n会议记录：\n{{context}}\n\n会议总结："
 doc_to_target: '{{answers}}'
 process_results: !function metrics.get_rouge_zh_score
 generation_kwargs:
   max_gen_toks: 512
   temperature: 1
-  do_sample: True
+  do_sample: False
   until: []
 metric_list:
   - metric: "rouge_zh_score"
     aggregation: mean
     higher_is_better: True
 metadata:
-  version: 3.0
+  version: 4.0