Dataset Viewer
Auto-converted to Parquet Duplicate
input
dict
prediction
dict
reasoning
stringclasses
9 values
messages
dict
correct
bool
2 classes
{ "full_text": "Many people have car where they live. The thing they don't know is that when you use a car alot of thing can happen like you can get in accidet or the smoke that the car has is bad to breath on if someone is walk but in VAUBAN,Germany they dont have that proble because 70 percent of vauban's families ...
{ "score": "4" }
Thinking Process: 1. **Analyze the Request:** * Input: `full_text` containing a student essay. * Task: Assign a holistic score from 1 to 6 based on a provided rubric. * Output Format: JSON object `{"score": N}`, but looking at the initial system prompt instructions, there's a conflict. * S...
{ "messages": [ { "content": "Your input fields are:\n1. `full_text` (str): Essay text to score.\nYour output fields are:\n1. `score` (Literal['1', '2', '3', '4', '5', '6']): Holistic essay score on a 1-6 scale.\nAll interactions will be structured in the following way, with the appropriate values filled in...
false
{ "full_text": "I am a scientist at NASA that is discussing the \"face\" on mars. I will be explaining how the \"face\" is a land form. By sharing my information about this isue i will tell you just that.\n\nFirst off, how could it be a martions drawing. There is no plant life on mars as of rite now that we know of, ...
{ "score": "4" }
Thinking Process: 1. **Analyze the Request:** * Input: A single student essay (`<full_text>` containing the essay). * Task: Assign a holistic score (1-6) based on a specific rubric. * Output Format: XML tag `<score>{"label": N}`. Wait, looking closer at the prompt instructions: * "Output f...
{ "messages": [ { "content": "Your input fields are:\n1. `full_text` (str): Essay text to score.\nYour output fields are:\n1. `score` (Literal['1', '2', '3', '4', '5', '6']): Holistic essay score on a 1-6 scale.\nAll interactions will be structured in the following way, with the appropriate values filled in...
false
{ "full_text": "People always wish they had the same technology that they have seen in movies, or the best new piece of technology that is all over social media. However, nobody seems to think of the risks that these kinds of new technologies may have. Cars have been around for many decades, and now manufacturers are...
{ "score": "3" }
Thinking Process: 1. **Analyze the Request:** * Input: A string `full_text` containing an essay. * Output: A JSON object with a single key `"score"`. * Score values: '1', '2', '3', '4', '5', '6' (as a string literal in JSON, but the instruction says `Literal['1', '2', '3', '4', '5', '6']` and later ...
{ "messages": [ { "content": "Your input fields are:\n1. `full_text` (str): Essay text to score.\nYour output fields are:\n1. `score` (Literal['1', '2', '3', '4', '5', '6']): Holistic essay score on a 1-6 scale.\nAll interactions will be structured in the following way, with the appropriate values filled in...
false
{ "full_text": "We all heard about Venus, the planet without almost oxygen with earthquakes, erupting volcanoes and temperatures average over 800 degrees Fahrenheit but what if scientist project the futur into this planet ? Through this article, the author uses evidences appealing to reason and concession to make us ...
null
null
null
false
{"full_text":"Dear, State Senator\n\nThis is a letter to argue in favor of keeping the Electoral Col(...TRUNCATED)
{ "score": "3" }
"Thinking Process:\n\n1. **Analyze the Request:**\n * Input: A student essay (letter format) a(...TRUNCATED)
{"messages":[{"content":"Your input fields are:\n1. `full_text` (str): Essay text to score.\nYour ou(...TRUNCATED)
true
{"full_text":"If I were to choose between keeping the electoral college or abolishing it, I would ch(...TRUNCATED)
{ "score": "4" }
"The user wants me to score an AES2 essay based on a specific rubric. I need to output just the scor(...TRUNCATED)
{"messages":[{"content":"Your input fields are:\n1. `full_text` (str): Essay text to score.\nYour ou(...TRUNCATED)
true
{"full_text":"The posibilty of a face reconizing computer would be very helpful for children or even(...TRUNCATED)
{ "score": "4" }
"Thinking Process:\n\n1. **Analyze the Request:**\n * Input: A JSON-like object with a `full_t(...TRUNCATED)
{"messages":[{"content":"Your input fields are:\n1. `full_text` (str): Essay text to score.\nYour ou(...TRUNCATED)
false
{"full_text":"What is the Seagoing Cowboys progam?\n\nIt was to help many countries that had been sc(...TRUNCATED)
{ "score": "4" }
"Thinking Process:\n\n1. **Analyze the Request:**\n * Input: A JSON-like structure with a `ful(...TRUNCATED)
{"messages":[{"content":"Your input fields are:\n1. `full_text` (str): Essay text to score.\nYour ou(...TRUNCATED)
false
{"full_text":"The challenge of exploring Venus\n\nThis storie is about the challeng of exploring Ven(...TRUNCATED)
{ "score": "3" }
"Thinking Process:\n\n1. **Analyze the Request:**\n * Input: `full_text` (an essay text).\n (...TRUNCATED)
{"messages":[{"content":"Your input fields are:\n1. `full_text` (str): Essay text to score.\nYour ou(...TRUNCATED)
false
{"full_text":"There are many reasons why you should join seagoing cowboys program. You would be help(...TRUNCATED)
{ "score": "3" }
"Thinking Process:\n\n1. **Analyze the Request:**\n * Input: A student essay text (`full_text`(...TRUNCATED)
{"messages":[{"content":"Your input fields are:\n1. `full_text` (str): Essay text to score.\nYour ou(...TRUNCATED)
true

qwen3.5-4b-v2-instructions-smoke

  • Repo: tytodd/qwen3.5-4b-v2-instructions-smoke
  • Model: Qwen/Qwen3.5-4B
  • Config: /tmp/v2-instructions-smoke.yaml
benchmark train val ood all
chatbot_arena_conversations 50.00% 30.00% 40.00%
hh_rlhf 60.00% 70.00% 65.00%
ultrafeedback 20.00% 20.00% 20.00%
projudgebench 100.00% 100.00% 100.00%
reward_bench_2 80.00% 90.00% 85.00%
aes2_essay_scoring 30.00% 10.00% 20.00%
halueval_qa 80.00% 90.00% 85.00%
halueval_dialogue 70.00% 70.00% 70.00%
or_bench_80k 10.00% 30.00% 20.00%
or_bench_hard_1k 60.00% 60.00% 60.00%
toxigen_data 90.00% 100.00% 95.00%
civil_comments 80.00% 90.00% 85.00%
boardgame_qa 100.00% 100.00% 100.00%
go_emotions 0.00% 0.00% 0.00%
mfrc 0.00% 60.00% 30.00%
tweet_eval_emotion 70.00% 90.00% 80.00%
yelp 20.00% 20.00% 20.00%
tweet_eval_sentiment 70.00% 70.00% 70.00%
mmlu 30.00% 100.00% 65.00%
spartqa_mchoice 90.00% 80.00% 85.00%
anli_r1 90.00% 80.00% 85.00%
anli_r2 80.00% 40.00% 60.00%
anli_r3 50.00% 100.00% 75.00%
snli 80.00% 90.00% 85.00%
sem_eval_2010_task_8 70.00% 70.00% 70.00%
smollm_corpus 60.00% 60.00% 60.00%
medical_abstracts 30.00% 50.00% 40.00%
lex_glue_case_hold 60.00% 80.00% 70.00%
lex_glue_ledgar 70.00% 80.00% 75.00%
dbpedia_easy 100.00% 70.00% 85.00%
dbpedia_medium 60.00% 70.00% 65.00%
dbpedia_hard 60.00% 90.00% 75.00%
colbert_humor_detection 80.00% 80.00% 80.00%
tweet_eval_irony 60.00% 60.00% 60.00%
tweet_eval_hate 70.00% 70.00% 70.00%
tweet_eval_offensive 70.00% 90.00% 80.00%
customer_support_tickets_en 50.00% 60.00% 55.00%
customer_support_tickets_gorkem 0.00% 0.00% 0.00%
argument_quality_ranking 20.00% 20.00%
rod101_essay_scoring 30.00% 30.00%
or_bench_toxic 50.00% 50.00%
judge_bench 60.00% 60.00%
musr_team_allocation 60.00% 60.00%
musr_object_placements 40.00% 40.00%
musr_murder_mysteries 70.00% 70.00%
halueval_summarization 70.00% 70.00%
code_judge_bench 80.00% 80.00%
mmlu_pro 90.00% 90.00%
gpqa_diamond 90.00% 90.00%
arc_challenge 100.00% 100.00%
mt_bench_human_judgments 90.00% 90.00%
all 59.21% 66.32% 65.38% 63.15%
Downloads last month
192