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upload E1b (sft_thinking)

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.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
@@ -0,0 +1,60 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: apache-2.0
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+ base_model: Qwen/Qwen3-VL-2B-Thinking
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+ library_name: transformers
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+ tags:
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+ - vision-language
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+ - new-yorker
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+ - humor
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+ - rlhf
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+ - sft-thinking
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+ datasets:
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+ - yguooo/newyorker_caption_ranking
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+ language:
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+ - en
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+ ---
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+
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+ # humor-r1 — SFT, with thinking (Qwen3-VL-2B-Thinking + LoRA, merged) (E1b)
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+
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+ LoRA-adapted Qwen3-VL-2B-Thinking supervised fine-tuned on (image, synthetic thinking, chosen caption) triples, then merged. Output format: `{thinking}</think>\n\n<caption>X</caption>`.
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+
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+ ## Training data
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+
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+ - 271 New Yorker contests, top-rated caption per contest
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+ (`yguooo/newyorker_caption_ranking`).
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+ - The 60k Bradley-Terry preference pairs underlying the reward model
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+ (separate split).
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+ - We deliberately do NOT use the dataset's GPT-4o-generated
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+ Scene/Twist/Location/Entities descriptions in the prompt, since they
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+ hand-feed scene content to a vision-language model that can already
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+ see the image; this makes the policy and reward model usable on any
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+ single-panel cartoon, not just the curated subset.
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+
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+ ## How it fits the project
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+
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+ Part of a 2x2 ablation over training method (SFT, GRPO) and output
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+ format (no thinking, thinking) for humor caption generation. See
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+ `HumorR1/rm-qwen25vl-3b-nodesc` for the reward model used to train (and
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+ score) this policy.
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+
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+ ## Inference
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+
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+ Backbone: `Qwen/Qwen3-VL-2B-Thinking`.
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+ This repo is a merged full model; load with `transformers.AutoModelForCausalLM.from_pretrained`.
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+
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+ ```python
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+ from PIL import Image
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+ from transformers import AutoProcessor
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+ from vllm import LLM, SamplingParams
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+
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+
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+ processor = AutoProcessor.from_pretrained("Qwen/Qwen3-VL-2B-Thinking", trust_remote_code=True)
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+ llm = LLM(model="Qwen/Qwen3-VL-2B-Thinking", trust_remote_code=True, dtype="bfloat16",
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+ max_model_len=4096)
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+
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+ # Caption format: <caption>X</caption>; thinking variant prefixes <think>...</think>.
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+ ```
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+
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+ ## Reward model used during training
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+
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+ - `HumorR1/rm-qwen25vl-3b-nodesc` (held-out pairwise accuracy 0.6635).
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+ {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}
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+ {%- endif %}
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+ {%- endfor %}
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+ {%- for tool in tools %}
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+ {{- "\n" }}
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+ {{- tool | tojson }}
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+ {%- endfor %}
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+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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+ {%- else %}
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+ {%- if messages[0].role == 'system' %}
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+ {{- '<|im_start|>system\n' + render_content(messages[0].content, false) + '<|im_end|>\n' }}
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+ {%- endif %}
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+ {%- endif %}
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+ {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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+ {%- for message in messages[::-1] %}
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+ {%- set index = (messages|length - 1) - loop.index0 %}
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+ {%- if ns.multi_step_tool and message.role == "user" %}
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+ {%- set content = render_content(message.content, false) %}
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+ {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
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+ {%- set ns.multi_step_tool = false %}
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+ {%- set ns.last_query_index = index %}
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+ {%- endif %}
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+ {%- endif %}
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+ {%- endfor %}
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+ {%- for message in messages %}
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+ {%- set content = render_content(message.content, True) %}
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+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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+ {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
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+ {%- elif message.role == "assistant" %}
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+ {%- set reasoning_content = '' %}
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+ {%- if message.reasoning_content is string %}
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+ {%- set reasoning_content = message.reasoning_content %}
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+ {%- set content = content.split('</think>')[-1].lstrip('\n') %}
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+ {%- else %}
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+ {{- '<|im_start|>' + message.role + '\n' + content }}
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+ {%- if tool_call.arguments is string %}
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+ {%- if add_generation_prompt %}
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+ {{- '<|im_start|>assistant\n<think>\n' }}
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