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% |
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