From 439e83e703e3472e20bfd781f6a8360716605893 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Thu, 23 Jul 2026 13:24:13 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: lldois/v28_v26_no_template_product_world_lr12e6_ep022 Source: Original Platform --- .gitattributes | 36 + README.md | 58 + all_results.json | 8 + chat_template.jinja | 89 + config.json | 63 + experiment_recipe.json | 65 + generation_config.json | 12 + model.safetensors | 3 + ...801589.ubuntu-System-Product-Name.776848.0 | 3 + tokenizer.json | 3 + tokenizer_config.json | 16 + train.log | 2282 +++++++++++++++++ train_results.json | 8 + trainer_log.jsonl | 11 + trainer_state.json | 113 + training_args.bin | 3 + training_loss.png | Bin 0 -> 48922 bytes 17 files changed, 2773 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 all_results.json create mode 100644 chat_template.jinja create mode 100644 config.json create mode 100644 experiment_recipe.json create mode 100644 generation_config.json create mode 100644 model.safetensors create mode 100644 runs/Jul12_04-26-29_ubuntu-System-Product-Name/events.out.tfevents.1783801589.ubuntu-System-Product-Name.776848.0 create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json create mode 100644 train.log create mode 100644 train_results.json create mode 100644 trainer_log.jsonl create mode 100644 trainer_state.json create mode 100644 training_args.bin create mode 100644 training_loss.png diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..52373fe --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..c3e2363 --- /dev/null +++ b/README.md @@ -0,0 +1,58 @@ +--- +library_name: transformers +license: other +base_model: lldois/v26_v21_product_rec_rebalance_lr22e6_ep032 +tags: +- llama-factory +- full +- generated_from_trainer +model-index: +- name: v28_v26_no_template_product_world_lr12e6_ep022 + results: [] +--- + + + +# v28_v26_no_template_product_world_lr12e6_ep022 + +This model is a fine-tuned version of [lldois/v26_v21_product_rec_rebalance_lr22e6_ep032](https://huggingface.co/lldois/v26_v21_product_rec_rebalance_lr22e6_ep032) on the exp_v26_no_template_product_world dataset. + +## Model description + +More information needed + +## Intended uses & limitations + +More information needed + +## Training and evaluation data + +More information needed + +## Training procedure + +### Training hyperparameters + +The following hyperparameters were used during training: +- learning_rate: 1.2e-06 +- train_batch_size: 1 +- eval_batch_size: 8 +- seed: 202607281 +- gradient_accumulation_steps: 4 +- total_train_batch_size: 4 +- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments +- lr_scheduler_type: cosine +- lr_scheduler_warmup_steps: 0.02 +- num_epochs: 0.22 + +### Training results + + + +### Framework versions + +- Transformers 5.6.0 +- Pytorch 2.7.1+cu126 +- Datasets 4.0.0 +- Tokenizers 0.22.2 diff --git a/all_results.json b/all_results.json new file mode 100644 index 0000000..8a2261f --- /dev/null +++ b/all_results.json @@ -0,0 +1,8 @@ +{ + "epoch": 0.22123893805309736, + "total_flos": 2.3544070748841984e+16, + "train_loss": 1.5697357273101806, + "train_runtime": 430.9822, + "train_samples_per_second": 0.461, + "train_steps_per_second": 0.116 +} \ No newline at end of file diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..01be9b3 --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1,89 @@ +{%- if tools %} + {{- '<|im_start|>system\n' }} + {%- if messages[0].role == 'system' %} + {{- messages[0].content + '\n\n' }} + {%- endif %} + {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within XML tags:\n" }} + {%- for tool in tools %} + {{- "\n" }} + {{- tool | tojson }} + {%- endfor %} + {{- "\n\n\nFor each function call, return a json object with function name and arguments within XML tags:\n\n{\"name\": , \"arguments\": }\n<|im_end|>\n" }} +{%- else %} + {%- if messages[0].role == 'system' %} + {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }} + {%- endif %} +{%- endif %} +{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %} +{%- for message in messages[::-1] %} + {%- set index = (messages|length - 1) - loop.index0 %} + {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('') and message.content.endswith('')) %} + {%- set ns.multi_step_tool = false %} + {%- set ns.last_query_index = index %} + {%- endif %} +{%- endfor %} +{%- for message in messages %} + {%- if message.content is string %} + {%- set content = message.content %} + {%- else %} + {%- set content = '' %} + {%- endif %} + {%- if (message.role == "user") or (message.role == "system" and not loop.first) %} + {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }} + {%- elif message.role == "assistant" %} + {%- set reasoning_content = '' %} + {%- if message.reasoning_content is string %} + {%- set reasoning_content = message.reasoning_content %} + {%- else %} + {%- if '' in content %} + {%- set reasoning_content = content.split('')[0].rstrip('\n').split('')[-1].lstrip('\n') %} + {%- set content = content.split('')[-1].lstrip('\n') %} + {%- endif %} + {%- endif %} + {%- if loop.index0 > ns.last_query_index %} + {%- if loop.last or (not loop.last and reasoning_content) %} + {{- '<|im_start|>' + message.role + '\n\n' + reasoning_content.strip('\n') + '\n\n\n' + content.lstrip('\n') }} + {%- else %} + {{- '<|im_start|>' + message.role + '\n' + content }} + {%- endif %} + {%- else %} + {{- '<|im_start|>' + message.role + '\n' + content }} + {%- endif %} + {%- if message.tool_calls %} + {%- for tool_call in message.tool_calls %} + {%- if (loop.first and content) or (not loop.first) %} + {{- '\n' }} + {%- endif %} + {%- if tool_call.function %} + {%- set tool_call = tool_call.function %} + {%- endif %} + {{- '\n{"name": "' }} + {{- tool_call.name }} + {{- '", "arguments": ' }} + {%- if tool_call.arguments is string %} + {{- tool_call.arguments }} + {%- else %} + {{- tool_call.arguments | tojson }} + {%- endif %} + {{- '}\n' }} + {%- endfor %} + {%- endif %} + {{- '<|im_end|>\n' }} + {%- elif message.role == "tool" %} + {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %} + {{- '<|im_start|>user' }} + {%- endif %} + {{- '\n\n' }} + {{- content }} + {{- '\n' }} + {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %} + {{- '<|im_end|>\n' }} + {%- endif %} + {%- endif %} +{%- endfor %} +{%- if add_generation_prompt %} + {{- '<|im_start|>assistant\n' }} + {%- if enable_thinking is defined and enable_thinking is false %} + {{- '\n\n\n\n' }} + {%- endif %} +{%- endif %} \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000..c4eb20b --- /dev/null +++ b/config.json @@ -0,0 +1,63 @@ +{ + "architectures": [ + "Qwen3ForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": null, + "dtype": "bfloat16", + "eos_token_id": 151645, + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": 3072, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 40960, + "max_window_layers": 28, + "model_type": "qwen3", + "num_attention_heads": 16, + "num_hidden_layers": 28, + "num_key_value_heads": 8, + "pad_token_id": 151643, + "rms_norm_eps": 1e-06, + "rope_parameters": { + "rope_theta": 1000000, + "rope_type": "default" + }, + "sliding_window": null, + "tie_word_embeddings": false, + "transformers_version": "5.6.0", + "use_cache": false, + "use_sliding_window": false, + "vocab_size": 176253 +} diff --git a/experiment_recipe.json b/experiment_recipe.json new file mode 100644 index 0000000..9bc3ef6 --- /dev/null +++ b/experiment_recipe.json @@ -0,0 +1,65 @@ +{ + "created_at": "2026-07-12 04:25:55", + "run": { + "name": "v28_v26_no_template_product_world_lr12e6_ep022", + "dataset": "v26_no_template_product_world", + "model_path": "/home/ll/llm4rec/experiments/outputs/v26_v21_product_rec_rebalance_lr22e6_ep032", + "lr": "1.2e-6", + "epochs": 0.22, + "warmup": 0.02, + "scheduler": "cosine", + "seed": 202607281, + "note": "v26 continuation. Remove repeated synthetic short-think templates, keep low-update CoT/no-think route supervision, add mild product/video rec replay plus item and user guards. Goal: keep v26 speed/user1/rec1 while recovering rec2/world.", + "config": "/home/ll/llm4rec/experiments/configs/v28_v26_no_template_product_world_lr12e6_ep022.yaml" + }, + "dataset_manifest": { + "name": "v26_no_template_product_world", + "path": "/home/ll/llm4rec/experiments/data/v26_no_template_product_world.jsonl", + "records": 21886, + "groups": { + "item": 8397, + "rec": 10689, + "user": 2800 + }, + "variants": { + "item_short_think": 2792, + "item_compact_cot": 2800, + "rec_cot_pattern_clean": 4000, + "user_extra_no_think_logic": 483, + "rec_no_think_direct_final": 6689, + "item_no_think_direct_final": 2805, + "user_strict_array": 1269, + "user_strict_logic": 1048 + }, + "sha256": "e3ca534de9f823184f2688db713a110fcaf10f98e17a534183e096a6bca88d18", + "seed": 202607111 + }, + "dataset_recipe": "v26 continuation: drop repeated synthetic short-think templates, keep cleaned original CoT and route-specific no-think final answers, add mild product/video repair, item replay, and user JSON guard.", + "cot_policy": "Preserve /think reasoning supervision and do not use v7_final_only as a CoT training base. For /no_think prompts, train pure final answers without generated tags. This is route-specific behavior, not global CoT removal.", + "raw_counts": { + "rec": 19204, + "item": 10384, + "user": 2892 + }, + "eval_observations": { + "v07": "best local score so far: total=0.8978, eval_time≈47.3min; fast final outputs likely help.", + "v15": "best CoT-preserving score so far: total=0.8778, eval_time≈70.1min; logs show repeated tokens, JSON shell errors, prompt leakage, and verbose /no_think outputs.", + "v19": "best CoT-native continuation so far: total=0.8855, eval_time≈48.1min; user1 and rec4 improved but world dropped.", + "v20": "v7 final-only continuation with CoT restore failed as a CoT route: total=0.8527, item fell to 0.1840; do not use v7 as future CoT base.", + "v22": "scratch official-base 3 epoch clean CoT underperformed: total=0.8217; item/world preserved but user and rec2 are weak.", + "v23": "scratch official-base 5 epoch low-LR guard failed badly: total=0.6990; item/user collapse suggests long scratch SFT is not viable with current data mix.", + "v24": "v15 light repair is best among v22-v24 but still only total=0.8364; user2 improves but rec/world do not recover.", + "v25": "v19 product-heavy repair did not beat v19: total=0.8793. Logs show heavy repeated product tokens and repeated short-think phrases; avoid this over-sampling pattern.", + "v26": "best latest batch and fastest eval: total=0.8804, eval_time≈45.7min, best user1/rec1. It is useful as a base, but rec2/world dropped.", + "v27": "v12 product/ad repair kept user2/world relatively better but was slow and template-heavy: total=0.8563, eval_time≈70.6min. Do not continue this exact direction.", + "v16": "CoT pattern rewrite failed: total=0.7912; logs show malformed user JSON and fragmented recommendation reasoning.", + "v18": "low-LR mixed replay from v12 failed: total=0.8340; item/world dropped and rec outputs mixed text/itemic/think tags." + }, + "script": "/home/ll/llm4rec/experiments/run_experiments.py", + "script_sha256": "7375c7a06ae5221c98bc2135819e0999d80e2b2098543ac9a5c56c352bd693d3", + "deadline": "none", + "reproduce": { + "prepare_command": "EXPERIMENT_PREPARE_ONLY=1 python3 experiments/run_experiments.py", + "train_command": "CUDA_VISIBLE_DEVICES= bash -lc 'source /home/ll/llm4rec/demo/LLaMA-Factory/.venv/bin/activate && llamafactory-cli train /home/ll/llm4rec/experiments/configs/v28_v26_no_template_product_world_lr12e6_ep022.yaml'" + } +} \ No newline at end of file diff --git a/generation_config.json b/generation_config.json new file mode 100644 index 0000000..cf5bf49 --- /dev/null +++ b/generation_config.json @@ -0,0 +1,12 @@ +{ + "do_sample": true, + "eos_token_id": [ + 151645, + 151643 + ], + "pad_token_id": 151643, + "temperature": 0.6, + "top_k": 20, + "top_p": 0.95, + "transformers_version": "5.6.0" +} diff --git a/model.safetensors b/model.safetensors new file mode 100644 index 0000000..779d869 --- /dev/null +++ b/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:05cb7d56f868f19bf3298e29c6b903cc9698d8962afb1be3c04423ccb2a28c25 +size 1602902832 diff --git a/runs/Jul12_04-26-29_ubuntu-System-Product-Name/events.out.tfevents.1783801589.ubuntu-System-Product-Name.776848.0 b/runs/Jul12_04-26-29_ubuntu-System-Product-Name/events.out.tfevents.1783801589.ubuntu-System-Product-Name.776848.0 new file mode 100644 index 0000000..757613e --- /dev/null +++ b/runs/Jul12_04-26-29_ubuntu-System-Product-Name/events.out.tfevents.1783801589.ubuntu-System-Product-Name.776848.0 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0d971c752da4a5fbe1b2123ef2a6a95c3e2f5beacc67e94e89240f160b8e628c +size 8396 diff --git a/tokenizer.json b/tokenizer.json new file mode 100644 index 0000000..8aee134 --- /dev/null +++ b/tokenizer.json @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:cd4d15f596979aecbc11ba12668cb21c9fb8452ce1235cd9d7878cc950170421 +size 16016554 diff --git a/tokenizer_config.json b/tokenizer_config.json new file mode 100644 index 0000000..35d445f --- /dev/null +++ b/tokenizer_config.json @@ -0,0 +1,16 @@ +{ + "add_prefix_space": false, + "backend": "tokenizers", + "bos_token": null, + "clean_up_tokenization_spaces": false, + "eos_token": "<|im_end|>", + "errors": "replace", + "is_local": true, + "local_files_only": false, + "model_max_length": 131072, + "pad_token": "<|endoftext|>", + "padding_side": "right", + "split_special_tokens": false, + "tokenizer_class": "Qwen2Tokenizer", + "unk_token": null +} diff --git a/train.log b/train.log new file mode 100644 index 0000000..4424ce2 --- /dev/null +++ b/train.log @@ -0,0 +1,2282 @@ +/home/ll/llm4rec/demo/LLaMA-Factory/.venv/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. + import pkg_resources +[transformers] warmup_ratio is deprecated and will be removed in v5.2. Use `warmup_steps` instead. +[transformers] `logging_dir` is deprecated and will be removed in v5.2. Please set `TENSORBOARD_LOGGING_DIR` instead. +[INFO|2026-07-12 04:25:58] llamafactory.hparams.parser:523 >> Process rank: 0, world size: 1, device: cuda:0, distributed training: False, compute dtype: torch.bfloat16 +[INFO|configuration_utils.py:769] 2026-07-12 04:25:58,575 >> loading configuration file /home/ll/llm4rec/experiments/outputs/v26_v21_product_rec_rebalance_lr22e6_ep032/config.json +[INFO|configuration_utils.py:847] 2026-07-12 04:25:58,578 >> Model config Qwen3Config { + "architectures": [ + "Qwen3ForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": null, + "dtype": "bfloat16", + "eos_token_id": 151645, + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": 3072, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 40960, + "max_window_layers": 28, + "model_type": "qwen3", + "num_attention_heads": 16, + "num_hidden_layers": 28, + "num_key_value_heads": 8, + "pad_token_id": 151643, + "rms_norm_eps": 1e-06, + "rope_parameters": { + "rope_theta": 1000000, + "rope_type": "default" + }, + "sliding_window": null, + "tie_word_embeddings": false, + "transformers_version": "5.6.0", + "use_cache": false, + "use_sliding_window": false, + "vocab_size": 176253 +} + +[INFO|configuration_utils.py:769] 2026-07-12 04:25:59,263 >> loading configuration file /home/ll/llm4rec/experiments/outputs/v26_v21_product_rec_rebalance_lr22e6_ep032/config.json +[INFO|configuration_utils.py:847] 2026-07-12 04:25:59,264 >> Model config Qwen3Config { + "architectures": [ + "Qwen3ForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": null, + "dtype": "bfloat16", + "eos_token_id": 151645, + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": 3072, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 40960, + "max_window_layers": 28, + "model_type": "qwen3", + "num_attention_heads": 16, + "num_hidden_layers": 28, + "num_key_value_heads": 8, + "pad_token_id": 151643, + "rms_norm_eps": 1e-06, + "rope_parameters": { + "rope_theta": 1000000, + "rope_type": "default" + }, + "sliding_window": null, + "tie_word_embeddings": false, + "transformers_version": "5.6.0", + "use_cache": false, + "use_sliding_window": false, + "vocab_size": 176253 +} + +[INFO|configuration_utils.py:769] 2026-07-12 04:25:59,264 >> loading configuration file /home/ll/llm4rec/experiments/outputs/v26_v21_product_rec_rebalance_lr22e6_ep032/config.json +[INFO|configuration_utils.py:847] 2026-07-12 04:25:59,264 >> Model config Qwen3Config { + "architectures": [ + "Qwen3ForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": null, + "dtype": "bfloat16", + "eos_token_id": 151645, + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": 3072, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 40960, + "max_window_layers": 28, + "model_type": "qwen3", + "num_attention_heads": 16, + "num_hidden_layers": 28, + "num_key_value_heads": 8, + "pad_token_id": 151643, + "rms_norm_eps": 1e-06, + "rope_parameters": { + "rope_theta": 1000000, + "rope_type": "default" + }, + "sliding_window": null, + "tie_word_embeddings": false, + "transformers_version": "5.6.0", + "use_cache": false, + "use_sliding_window": false, + "vocab_size": 176253 +} + +[INFO|2026-07-12 04:25:59] llamafactory.data.loader:144 >> Loading dataset /home/ll/llm4rec/experiments/data/v26_no_template_product_world.jsonl... +Setting num_proc from 16 back to 1 for the train split to disable multiprocessing as it only contains one shard. + Generating train split: 0 examples [00:00, ? examples/s] Generating train split: 11849 examples [00:00, 107394.96 examples/s] Generating train split: 21886 examples [00:00, 113861.68 examples/s] + Converting format of dataset (num_proc=16): 0%| | 0/21886 [00:00user +【用户交互历史】： +【2025-03-23】 + --:-- [直播-打赏] <|living_begin|> +【2025-05-10】 + --:-- [直播-打赏] <|living_begin|> +【2025-06-23】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-25】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-06-26】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-07-03】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-07-11】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-13】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-04】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-07】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-08-15】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-17】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-18】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-27】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-09-03】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-05】 + --:-- [直播-首次打赏] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-09-24】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-02】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-19】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-11-06】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-11】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-20】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-06】 + --:-- [商品-购买] <|prod_begin|> +【2025-12-12】 + 06:09 [广告-深度转化] <|ad_begin|> + 18:04 [广告-深度转化] <|ad_begin|> +【2025-12-13】 + 15:21 [广告-深度转化] <|ad_begin|> + 17:08 [广告-深度转化] <|ad_begin|> +【2025-12-15】 + 10:05 [广告-深度转化] <|ad_begin|> + 11:24 [广告-深度转化] <|ad_begin|> +【2025-12-16】 + 01:36 [广告-深度转化] <|ad_begin|> + 15:34 [广告-深度转化] <|ad_begin|> +【2025-12-18】 + 01:51 [广告-深度转化] <|ad_begin|> + 17:25 [广告-深度转化] <|ad_begin|> +【2025-12-19】 + 04:04 [广告-深度转化] <|ad_begin|> + 04:44 [广告-深度转化] <|ad_begin|> + 13:59 [广告-深度转化] <|ad_begin|> + 14:20 [广告-深度转化] <|ad_begin|> +【2025-12-21】 + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + 11:06 [广告-深度转化] <|ad_begin|> + 11:49 [广告-深度转化] <|ad_begin|> +【2025-12-22】 + --:-- [商品-加购] <|prod_begin|> +【2025-12-23】 + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + 05:12 [广告-深度转化] <|ad_begin|> +【2025-12-24】 + 09:20 [广告-深度转化] <|ad_begin|> + 10:18 [广告-深度转化] <|ad_begin|> + 11:20 [广告-深度转化] <|ad_begin|> +【2025-12-25】 + 01:24 [广告-深度转化] <|ad_begin|> + 02:02 [广告-深度转化] <|ad_begin|> + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + 09:56 [广告-深度转化] <|ad_begin|> + 10:56 [广告-深度转化] <|ad_begin|> + 17:36 [广告-深度转化] <|ad_begin|> +【2025-12-26】 + 04:36 [广告-深度转化] <|ad_begin|> + 15:15 [广告-深度转化] <|ad_begin|> + 15:15 [广告-点击] <|ad_begin|> + 15:33 [广告-深度转化] <|ad_begin|> + 15:33 [广告-点击] <|ad_begin|> +【2025-12-27】 + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + 06:51 [广告-深度转化] <|ad_begin|> + 06:51 [广告-点击] <|ad_begin|> + 06:52 [广告-点击] <|ad_begin|> + 07:39 [广告-深度转化] <|ad_begin|> + 07:39 [广告-点击] <|ad_begin|> + 08:59 [广告-深度转化] <|ad_begin|> + 08:59 [广告-点击] <|ad_begin|> + 10:10 [广告-深度转化] <|ad_begin|> + 10:10 [广告-点击] <|ad_begin|> + 14:17 [广告-深度转化] <|ad_begin|> + 14:17 [广告-点击] <|ad_begin|> + 14:25 [广告-深度转化] <|ad_begin|> + 14:25 [广告-点击] <|ad_begin|> + 14:42 [广告-深度转化] <|ad_begin|> + 14:42 [广告-点击] <|ad_begin|> +【2025-12-28】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 07:07 [广告-深度转化] <|ad_begin|> + 07:07 [广告-点击] <|ad_begin|> + 12:28 [广告-深度转化] <|ad_begin|> + 12:28 [广告-点击] <|ad_begin|> + 15:35 [广告-深度转化] <|ad_begin|> + 15:35 [广告-点击] <|ad_begin|> + 15:49 [广告-深度转化] <|ad_begin|> + 15:49 [广告-点击] <|ad_begin|> + 17:50 [广告-点击] <|ad_begin|> +【2025-12-29】 + 02:11 [广告-点击] <|ad_begin|> + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + 03:14 [广告-深度转化] <|ad_begin|> + 03:14 [广告-点击] <|ad_begin|> + 04:19 [广告-点击] <|ad_begin|> + 05:49 [广告-深度转化] <|ad_begin|> + 05:49 [广告-点击] <|ad_begin|> + 06:38 [广告-深度转化] <|ad_begin|> + 06:38 [广告-点击] <|ad_begin|> + 09:56 [广告-深度转化] <|ad_begin|> + 09:56 [广告-点击] <|ad_begin|> +【2025-12-30】 + 01:10 [广告-深度转化] <|ad_begin|> + 01:10 [广告-点击] <|ad_begin|> + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + 04:47 [广告-深度转化] <|ad_begin|> + 04:47 [广告-点击] <|ad_begin|> + 09:23 [广告-点击] <|ad_begin|> + 10:11 [广告-深度转化] <|ad_begin|> + 10:11 [广告-点击] <|ad_begin|> +【2025-12-31】 + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + 03:06 [广告-深度转化] <|ad_begin|> + 03:06 [广告-点击] <|ad_begin|> + 03:11 [广告-点击] <|ad_begin|> + 10:04 [广告-深度转化] <|ad_begin|> + 10:04 [广告-点击] <|ad_begin|> + 10:56 [广告-深度转化] <|ad_begin|> + 10:56 [广告-点击] <|ad_begin|> + 12:18 [广告-深度转化] <|ad_begin|> + 12:18 [广告-点击] <|ad_begin|> + 13:37 [广告-深度转化] <|ad_begin|> + 13:37 [广告-点击] <|ad_begin|> +【2026-01-01】 + 01:37 [广告-点击] <|ad_begin|> + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + 05:00 [广告-深度转化] <|ad_begin|> + 05:00 [广告-点击] <|ad_begin|> +【2026-01-02】 + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + 07:53 [广告-深度转化] <|ad_begin|> + 07:53 [广告-点击] <|ad_begin|> + 09:09 [广告-深度转化] <|ad_begin|> + 09:09 [广告-点击] <|ad_begin|> + 10:22 [广告-深度转化] <|ad_begin|> + 10:22 [广告-点击] <|ad_begin|> + 11:13 [广告-深度转化] <|ad_begin|> + 11:13 [广告-点击] <|ad_begin|> +【2026-01-04】 + 05:16 [广告-点击] <|ad_begin|> +【2026-01-05】 + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-加购] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-06】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-07】 + 15:20 [广告-点击] <|ad_begin|> +【2026-01-08】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-10】 + --:-- [商品-购买] <|prod_begin|> + 07:32 [广告-深度转化] <|ad_begin|> + 07:32 [广告-点击] <|ad_begin|> + 10:40 [广告-点击] <|ad_begin|> + 10:47 [广告-点击] <|ad_begin|> +【2026-01-12】 + 08:32 [广告-点击] <|ad_begin|> + 11:05 [广告-点击] <|ad_begin|> +【2026-01-13】 + 01:52 [广告-点击] <|ad_begin|> +【2026-01-15】 + 02:51 [广告-深度转化] <|ad_begin|> + 02:51 [广告-点击] <|ad_begin|> + 03:22 [广告-深度转化] <|ad_begin|> + 03:22 [广告-点击] <|ad_begin|> + 03:39 [广告-深度转化] <|ad_begin|> + 03:39 [广告-点击] <|ad_begin|> +【2026-01-16】 + 01:49 [广告-深度转化] <|ad_begin|> + 01:49 [广告-点击] <|ad_begin|> + --:-- [商品-加购] <|prod_begin|> +【2026-01-17】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 16:31 [广告-点击] <|ad_begin|> +【2026-01-22】 + 00:40 [广告-点击] <|ad_begin|> +【2026-01-23】 + 00:18 [广告-点击] <|ad_begin|> + 05:33 [视频-评论/点赞/长播] <|video_begin|> + 05:33 [视频-关注/长播] <|video_begin|> +【2026-01-24】 + --:-- [商品-购买] <|prod_begin|> + 03:54 [视频-评论/点赞/长播] <|video_begin|> +【2026-01-25】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 11:37 [视频-评论/点赞/长播] <|video_begin|> + 12:43 [视频-评论/点赞/长播] <|video_begin|> +【2026-01-26】 + --:-- [商品-购买] <|prod_begin|> + 12:43 [视频-评论/点赞/长播] <|video_begin|> + 12:43 [视频-评论/点赞/长播] <|video_begin|> + 14:01 [视频-评论/点赞/长播] <|video_begin|> +【2026-01-27】 + --:-- [商品-购买] <|prod_begin|> + 02:46 [视频-评论/点赞/长播] <|video_begin|> + 03:38 [视频-评论/点赞/长播] <|video_begin|> + 03:39 [广告-深度转化] <|ad_begin|> + 03:39 [广告-点击] <|ad_begin|> + 11:34 [广告-深度转化] <|ad_begin|> + 11:34 [广告-点击] <|ad_begin|> + 11:37 [视频-评论/长播] <|video_begin|> + 12:09 [广告-点击] <|ad_begin|> + 16:06 [广告-点击] <|ad_begin|> + 16:09 [广告-点击] <|ad_begin|> + 23:45 [广告-点击] <|ad_begin|> + 23:49 [广告-深度转化] <|ad_begin|> + 23:49 [广告-点击] <|ad_begin|> +【2026-01-28】 + 06:47 [广告-深度转化] <|ad_begin|> + 06:47 [广告-点击] <|ad_begin|> + 07:06 [广告-点击] <|ad_begin|> + 10:30 [视频-评论/点赞/长播] <|video_begin|> + 23:30 [视频-点赞/长播] <|video_begin|> + 23:30 [视频-点赞/长播] <|video_begin|> + 23:40 [广告-深度转化] <|ad_begin|> + 23:40 [广告-点击] <|ad_begin|> +【2026-01-29】 + 01:44 [视频-点赞/长播] <|video_begin|> + 02:13 [视频-评论/点赞/长播] <|video_begin|> + 03:03 [视频-长播] <|video_begin|> + 03:03 [视频-评论/点赞/长播] <|video_begin|> + 03:15 [视频-点赞/长播] <|video_begin|> + 03:26 [视频-点赞/长播] <|video_begin|> + 14:42 [视频-长播] <|video_begin|> + 14:42 [视频-长播] <|video_begin|> + 14:42 [视频-点赞/长播] <|video_begin|> + 23:24 [视频-长播] <|video_begin|> + 23:24 [视频-点赞/长播] <|video_begin|> + 23:44 [广告-点击] <|ad_begin|> +【2026-01-30】 + 00:14 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 02:30 [视频-点赞/长播] <|video_begin|> + 07:19 [视频-点赞/长播] <|video_begin|> + 07:34 [视频-点赞/长播] <|video_begin|> + 13:15 [视频-点赞/长播] <|video_begin|> + 13:15 [视频-评论/点赞/长播] <|video_begin|> +【2026-01-31】 + 00:34 [视频-点赞/长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 03:16 [视频-长播] <|video_begin|> + 03:16 [视频-长播] <|video_begin|> + 03:16 [视频-长播] <|video_begin|> + 03:16 [视频-长播] <|video_begin|> + 03:16 [视频-长播] <|video_begin|> + 03:16 [广告-点击] <|ad_begin|> + 03:41 [视频-长播] <|video_begin|> + 03:41 [视频-长播] <|video_begin|> + 04:25 [视频-长播] <|video_begin|> + 04:25 [视频-长播] <|video_begin|> + 05:24 [视频-长播] <|video_begin|> + 05:24 [视频-点赞/长播] <|video_begin|> + 05:43 [视频-长播] <|video_begin|> + 05:43 [视频-点赞/长播] <|video_begin|> + 05:43 [视频-评论/点赞/长播] <|video_begin|> + 05:57 [视频-长播] <|video_begin|> + 05:57 [视频-长播] <|video_begin|> + 05:57 [视频-评论/长播] <|video_begin|> + 06:10 [视频-点赞/长播] <|video_begin|> + 06:10 [视频-评论/长播] <|video_begin|> + 06:51 [视频-长播] <|video_begin|> + 14:02 [视频-长播] <|video_begin|> + 14:02 [视频-长播] <|video_begin|> + 14:02 [视频-点赞/长播] <|video_begin|> + 14:02 [视频-点赞/长播] <|video_begin|> + 14:02 [视频-点赞/长播] <|video_begin|> + 15:06 [广告-深度转化] <|ad_begin|> + 15:06 [广告-点击] <|ad_begin|> + 23:49 [广告-深度转化] <|ad_begin|> + 23:49 [广告-点击] <|ad_begin|> +【2026-02-01】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 05:30 [视频-长播] <|video_begin|> + 05:30 [视频-点赞/长播] <|video_begin|> + 06:04 [视频-长播] <|video_begin|> + 06:42 [视频-长播] <|video_begin|> + 06:42 [视频-点赞/长播] <|video_begin|> + 07:17 [视频-点赞/长播] <|video_begin|> + 07:41 [视频-点赞/长播] <|video_begin|> + 07:59 [视频-点赞/长播] <|video_begin|> + 08:04 [视频-长播] <|video_begin|> + 23:33 [视频-长播] <|video_begin|> + 23:33 [视频-长播] <|video_begin|> + 23:33 [视频-点赞/长播] <|video_begin|> + 23:47 [视频-长播] <|video_begin|> + 23:47 [视频-点赞/长播] <|video_begin|> +【2026-02-02】 + 01:42 [视频-点赞/长播] <|video_begin|> + 01:42 [视频-点赞/长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 02:51 [视频-点赞/长播] <|video_begin|> + 02:51 [视频-点赞/长播] <|video_begin|> + 03:04 [视频-长播] <|video_begin|> + 03:04 [视频-点赞/长播] <|video_begin|> + 03:04 [视频-点赞/长播] <|video_begin|> + 03:18 [视频-长播] <|video_begin|> + 04:19 [视频-点赞/长播] <|video_begin|> + 04:43 [视频-长播] <|video_begin|> + 04:43 [视频-长播] <|video_begin|> + 05:10 [视频-点赞/长播] <|video_begin|> +【2026-02-03】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 03:13 [视频-长播] <|video_begin|> + 03:13 [视频-长播] <|video_begin|> + 03:35 [视频-长播] <|video_begin|> + 03:35 [视频-长播] <|video_begin|> + 05:22 [视频-长播] <|video_begin|> + 09:58 [视频-长播] <|video_begin|> + 09:58 [视频-点赞/长播] <|video_begin|> + 10:13 [视频-长播] <|video_begin|> + 10:13 [视频-长播] <|video_begin|> + 10:56 [广告-深度转化] <|ad_begin|> + 10:56 [广告-点击] <|ad_begin|> + 11:27 [视频-长播] <|video_begin|> + 11:46 [视频-点赞/长播] <|video_begin|> +【2026-02-04】 + 01:42 [视频-长播] <|video_begin|> + 01:42 [视频-点赞/长播] <|video_begin|> + 01:42 [视频-点赞/长播] <|video_begin|> + 01:42 [视频-评论/点赞/长播] <|video_begin|> + 02:01 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 02:36 [视频-点赞/长播] <|video_begin|> + 02:36 [视频-点赞/长播] <|video_begin|> + 02:36 [视频-点赞/长播] <|video_begin|> + 10:22 [视频-长播] <|video_begin|> + 10:22 [视频-长播] <|video_begin|> + 12:47 [视频-长播] <|video_begin|> + 12:47 [视频-点赞/长播] <|video_begin|> + 13:10 [视频-长播] <|video_begin|> + 13:10 [视频-长播] <|video_begin|> + 13:10 [视频-长播] <|video_begin|> + 13:10 [视频-长播] <|video_begin|> + 13:10 [视频-长播] <|video_begin|> + 13:10 [视频-点赞/长播] <|video_begin|> + 13:10 [视频-点赞/长播] <|video_begin|> + 13:10 [视频-点赞/长播] <|video_begin|> +【2026-02-05】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 03:20 [视频-点赞/长播] <|video_begin|> + 03:20 [视频-点赞/长播] <|video_begin|> + 03:20 [视频-点赞/长播] <|video_begin|> + 03:34 [视频-点赞/长播] <|video_begin|> + 03:34 [视频-评论/点赞/长播] <|video_begin|> + 04:50 [视频-点赞/长播] <|video_begin|> + 05:13 [广告-深度转化] <|ad_begin|> + 05:13 [广告-点击] <|ad_begin|> + 05:31 [视频-长播] <|video_begin|> + 05:31 [视频-点赞/长播] <|video_begin|> + +角色任务：你是极端严苛的用户行为数据挖掘与数据格式化专家，请结合上述用户交互历史，面向给定主题，全面提取出所有具备关联性的历史交互数据。 + +主题：从被动接收到主动探索的Lolita风格穿搭兴趣构建 + +输出格式要求：请仅输出包含 SID 的 JSON 数组，严禁输出任何额外的解释、说明或 Markdown 标记。 + +强约束：最终答案必须是一个可被 json.loads 解析的 JSON，不能包含 Markdown、解释、重复键或 JSON 外额外字符。/no_think<|im_end|> +<|im_start|>assistant +["<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|video_begin|>","<|prod_begin|>"]<|im_end|> +<|im_start|>user +【用户交互历史】： +【2023-12-24】 + --:-- [商品-购买] <|prod_begin|> +【2024-08-10】 + --:-- [商品-购买] <|prod_begin|> +【2024-12-31】 + --:-- [商品-购买] <|prod_begin|> +【2025-01-05】 + --:-- [商品-购买] <|prod_begin|> +【2025-01-13】 + --:-- [直播-关注] <|living_begin|> +【2025-01-14】 + --:-- [直播-关注] <|living_begin|> +【2025-01-17】 + --:-- [直播-关注] <|living_begin|> +【2025-01-20】 + --:-- [直播-关注] <|living_begin|> +【2025-01-25】 + --:-- [直播-关注] <|living_begin|> +【2025-02-03】 + --:-- [直播-关注] <|living_begin|> +【2025-02-06】 + --:-- [直播-关注] <|living_begin|> +【2025-02-07】 + --:-- [商品-购买] <|prod_begin|> +【2025-02-08】 + --:-- [商品-购买] <|prod_begin|> +【2025-02-21】 + --:-- [商品-购买] <|prod_begin|> +【2025-02-23】 + --:-- [直播-关注] <|living_begin|> +【2025-02-25】 + --:-- [直播-关注] <|living_begin|> +【2025-03-22】 + --:-- [直播-关注] <|living_begin|> +【2025-04-04】 + --:-- [商品-购买] <|prod_begin|> +【2025-04-18】 + --:-- [直播-关注] <|living_begin|> +【2025-04-19】 + --:-- [商品-购买] <|prod_begin|> +【2025-05-02】 + --:-- [商品-点击] <|prod_begin|> +【2025-05-03】 + --:-- [商品-点击] <|prod_begin|> +【2025-05-06】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-05-07】 + --:-- [商品-点击] <|prod_begin|> +【2025-05-10】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-05-13】 + --:-- [商品-点击] <|prod_begin|> +【2025-05-16】 + --:-- [商品-点击] <|prod_begin|> +【2025-05-18】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-06-05】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-06-11】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-06-18】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-06-19】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-07-01】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-07-08】 + --:-- [商品-点击] <|prod_begin|> +【2025-07-27】 + --:-- [商品-点击] <|prod_begin|> +【2025-08-04】 + --:-- [直播-关注] <|living_begin|> +【2025-08-07】 + --:-- [商品-点击] <|prod_begin|> +【2025-08-16】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-08-21】 + --:-- [直播-关注] <|living_begin|> +【2025-08-25】 + --:-- [商品-点击] <|prod_begin|> +【2025-08-27】 + --:-- [商品-点击] <|prod_begin|> +【2025-08-30】 + --:-- [商品-点击] <|prod_begin|> +【2025-09-07】 + --:-- [商品-点击] <|prod_begin|> +【2025-09-25】 + --:-- [直播-关注] <|living_begin|> +【2025-10-14】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-10-16】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-10-24】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-10-31】 + --:-- [商品-点击] <|prod_begin|> +【2025-11-02】 + --:-- [商品-点击] <|prod_begin|> +【2025-11-12】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-12-06】 + --:-- [直播-关注] <|living_begin|> +【2025-12-10】 + 02:34 [广告-点击] <|ad_begin|> +【2025-12-11】 + --:-- [直播-关注] <|living_begin|> +【2025-12-12】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 11:34 [广告-点击] <|ad_begin|> +【2025-12-16】 + 13:24 [广告-点击] <|ad_begin|> +【2025-12-18】 + 05:57 [广告-点击] <|ad_begin|> +【2025-12-19】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-26】 + 04:35 [广告-点击] <|ad_begin|> +【2025-12-29】 + 13:24 [广告-点击] <|ad_begin|> + 13:27 [广告-点击] <|ad_begin|> +【2025-12-30】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + 05:39 [广告-点击] <|ad_begin|> +【2025-12-31】 + 02:28 [广告-点击] <|ad_begin|> + 02:49 [广告-深度转化] <|ad_begin|> + 02:49 [广告-点击] <|ad_begin|> +【2026-01-01】 + 13:03 [广告-点击] <|ad_begin|> + 13:13 [广告-点击] <|ad_begin|> + 13:37 [广告-深度转化] <|ad_begin|> + 13:37 [广告-点击] <|ad_begin|> +【2026-01-05】 + --:-- [直播-关注] <|living_begin|> + 04:22 [广告-点击] <|ad_begin|> +【2026-01-06】 + 06:33 [广告-深度转化] <|ad_begin|> + 06:33 [广告-点击] <|ad_begin|> +【2026-01-08】 + 22:47 [广告-点击] <|ad_begin|> +【2026-01-09】 + --:-- [直播-关注] <|living_begin|> +【2026-01-10】 + 07:52 [广告-点击] <|ad_begin|> +【2026-01-12】 + 00:36 [广告-点击] <|ad_begin|> +【2026-01-13】 + 14:09 [广告-点击] <|ad_begin|> +【2026-01-14】 + 22:00 [广告-深度转化] <|ad_begin|> + 22:00 [广告-点击] <|ad_begin|> +【2026-01-16】 + 23:04 [广告-点击] <|ad_begin|> +【2026-01-17】 + 03:16 [广告-点击] <|ad_begin|> + 04:09 [广告-点击] <|ad_begin|> + 04:21 [广告-点击] <|ad_begin|> +【2026-01-18】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + 03:54 [广告-点击] <|ad_begin|> + 14:27 [广告-点击] <|ad_begin|> +【2026-01-19】 + 08:04 [广告-点击] <|ad_begin|> + 10:53 [广告-深度转化] <|ad_begin|> + 10:53 [广告-点击] <|ad_begin|> +【2026-01-20】 + --:-- [商品-点击] <|prod_begin|> + 07:01 [广告-点击] <|ad_begin|> + 07:27 [广告-点击] <|ad_begin|> +【2026-01-21】 + --:-- [直播-关注] <|living_begin|> + 02:39 [广告-点击] <|ad_begin|> + 03:07 [广告-点击] <|ad_begin|> + 22:54 [广告-点击] <|ad_begin|> +【2026-01-22】 + --:-- [商品-点击] <|prod_begin|> + 03:56 [视频-关注/点赞/长播] <|video_begin|> + 03:56 [视频-关注/点赞/长播] <|video_begin|> + 05:47 [视频-关注/点赞/长播] <|video_begin|> + 22:43 [视频-关注/点赞/长播] <|video_begin|> + 22:53 [广告-深度转化] <|ad_begin|> + 22:53 [广告-点击] <|ad_begin|> + 22:54 [广告-点击] <|ad_begin|> + 22:58 [广告-点击] <|ad_begin|> + 23:26 [广告-点击] <|ad_begin|> +【2026-01-23】 + 03:13 [视频-关注/点赞/长播] <|video_begin|> + 06:13 [广告-点击] <|ad_begin|> + 06:16 [广告-点击] <|ad_begin|> + 07:06 [广告-点击] <|ad_begin|> + 23:04 [视频-关注/长播] <|video_begin|> +【2026-01-24】 + --:-- [商品-点击] <|prod_begin|> + 02:50 [广告-深度转化] <|ad_begin|> + 02:50 [广告-点击] <|ad_begin|> +【2026-01-25】 + 01:49 [广告-点击] <|ad_begin|> + 02:06 [视频-关注/点赞/长播] <|video_begin|> + 02:19 [视频-点赞/长播] <|video_begin|> + 02:19 [视频-关注/点赞/长播] <|video_begin|> + 02:34 [视频-点赞/长播] <|video_begin|> + 02:34 [视频-关注/长播] <|video_begin|> + 02:38 [视频-点赞/长播] <|video_begin|> + 02:45 [视频-点赞/长播] <|video_begin|> + 02:51 [视频-关注/点赞/长播] <|video_begin|> + 02:51 [视频-关注/点赞/长播] <|video_begin|> + 02:51 [视频-关注/点赞/长播] <|video_begin|> + 03:13 [视频-点赞/长播] <|video_begin|> + 03:13 [视频-关注/点赞/长播] <|video_begin|> + 03:36 [视频-点赞/长播] <|video_begin|> + 03:36 [视频-点赞/长播] <|video_begin|> + 03:48 [视频-关注/点赞/长播] <|video_begin|> + 04:15 [广告-点击] <|ad_begin|> + 22:44 [视频-点赞/长播] <|video_begin|> +【2026-01-26】 + 03:58 [广告-深度转化] <|ad_begin|> + 03:58 [广告-点击] <|ad_begin|> + 03:59 [视频-关注/点赞/长播] <|video_begin|> + 14:36 [视频-点赞/长播] <|video_begin|> + 22:50 [视频-点赞/长播] <|video_begin|> + 23:31 [视频-点赞/长播] <|video_begin|> + 23:31 [视频-关注/点赞/长播] <|video_begin|> + 23:41 [视频-关注/点赞/长播] <|video_begin|> +【2026-01-27】 + 03:55 [视频-点赞/长播] <|video_begin|> + 03:55 [视频-点赞/长播] <|video_begin|> + 03:55 [视频-关注/点赞/长播] <|video_begin|> + 04:09 [广告-点击] <|ad_begin|> + 04:10 [视频-点赞/长播] <|video_begin|> + 04:18 [视频-点赞/长播] <|video_begin|> + 04:18 [视频-点赞/长播] <|video_begin|> + 08:20 [视频-关注/点赞/长播] <|video_begin|> + 08:34 [视频-点赞/长播] <|video_begin|> + 08:34 [视频-点赞/长播] <|video_begin|> + 12:56 [视频-点赞/长播] <|video_begin|> + 12:56 [视频-点赞/长播] <|video_begin|> + 12:56 [视频-关注/长播] <|video_begin|> + 13:20 [视频-点赞/长播] <|video_begin|> +【2026-01-28】 + 04:09 [广告-点击] <|ad_begin|> + 04:12 [视频-点赞/长播] <|video_begin|> + 04:12 [视频-关注/点赞/长播] <|video_begin|> + 04:12 [视频-关注/点赞/长播] <|video_begin|> + 04:29 [广告-点击] <|ad_begin|> + 06:56 [视频-点赞/长播] <|video_begin|> + 06:58 [视频-关注/长播] <|video_begin|> + 07:00 [视频-点赞/长播] <|video_begin|> + 07:06 [视频-点赞/长播] <|video_begin|> + 07:13 [广告-深度转化] <|ad_begin|> + 07:13 [广告-点击] <|ad_begin|> +【2026-01-29】 + --:-- [直播-关注] <|living_begin|> + 03:23 [视频-关注/点赞/长播] <|video_begin|> + 03:56 [广告-点击] <|ad_begin|> + 04:48 [视频-点赞/长播] <|video_begin|> + 05:17 [视频-点赞/长播] <|video_begin|> + 05:20 [广告-点击] <|ad_begin|> + 05:21 [广告-点击] <|ad_begin|> + 05:26 [广告-点击] <|ad_begin|> + 05:28 [视频-关注/点赞/长播] <|video_begin|> + 05:28 [视频-关注/点赞/长播] <|video_begin|> + 05:28 [视频-关注/点赞/长播] <|video_begin|> + 05:32 [视频-点赞/长播] <|video_begin|> + 13:40 [视频-点赞/长播] <|video_begin|> + 13:55 [视频-关注/点赞/长播] <|video_begin|> + 14:04 [视频-点赞/长播] <|video_begin|> + 14:18 [广告-点击] <|ad_begin|> + 23:02 [视频-点赞/长播] <|video_begin|> + 23:14 [广告-点击] <|ad_begin|> +【2026-01-30】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-02-01】 + 03:35 [视频-点赞/长播] <|video_begin|> + 03:47 [视频-点赞/长播] <|video_begin|> + 03:47 [视频-点赞/长播] <|video_begin|> + 03:59 [视频-关注/点赞/长播] <|video_begin|> + 03:59 [视频-关注/长播] <|video_begin|> + 04:04 [视频-点赞/长播] <|video_begin|> + 04:27 [视频-关注/点赞/长播] <|video_begin|> + 04:39 [视频-点赞/长播] <|video_begin|> + 22:49 [视频-关注/点赞/长播] <|video_begin|> + 22:52 [广告-点击] <|ad_begin|> +【2026-02-02】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + 01:56 [视频-点赞/长播] <|video_begin|> + 01:56 [视频-关注/点赞/长播] <|video_begin|> + 06:09 [广告-点击] <|ad_begin|> + 06:26 [视频-点赞/长播] <|video_begin|> + 07:25 [视频-点赞/长播] <|video_begin|> + 23:28 [广告-点击] <|ad_begin|> +【2026-02-03】 + 06:15 [视频-点赞/长播] <|video_begin|> + 06:26 [视频-点赞/长播] <|video_begin|> + 06:30 [视频-转发/长播] <|video_begin|> + 07:05 [视频-长播] <|video_begin|> + 07:05 [视频-长播] <|video_begin|> + 22:38 [视频-长播] <|video_begin|> + 22:38 [视频-点赞/长播] <|video_begin|> + 22:44 [视频-长播] <|video_begin|> + 22:44 [视频-长播] <|video_begin|> + 22:47 [视频-长播] <|video_begin|> + 22:47 [视频-长播] <|video_begin|> + 22:50 [视频-长播] <|video_begin|> + 22:50 [视频-点赞/长播] <|video_begin|> + 22:52 [视频-长播] <|video_begin|> + 22:52 [视频-长播] <|video_begin|> + 22:52 [视频-长播] <|video_begin|> + 22:53 [视频-长播] <|video_begin|> + 22:56 [视频-长播] <|video_begin|> + 23:28 [视频-长播] <|video_begin|> + 23:28 [视频-长播] <|video_begin|> + 23:29 [视频-长播] <|video_begin|> + 23:29 [视频-长播] <|video_begin|> + 23:31 [视频-点赞/长播] <|video_begin|> +【2026-02-04】 + 01:52 [视频-长播] <|video_begin|> + 02:14 [视频-长播] <|video_begin|> + 02:14 [视频-点赞/长播] <|video_begin|> + 02:21 [视频-点赞/长播] <|video_begin|> + 05:35 [视频-长播] <|video_begin|> + 05:35 [视频-点赞/长播] <|video_begin|> + 05:35 [视频-关注/点赞/长播] <|video_begin|> + 05:35 [视频-关注/点赞/长播] <|video_begin|> + 05:41 [视频-长播] <|video_begin|> + 05:43 [视频-长播] <|video_begin|> + 05:43 [视频-长播] <|video_begin|> + 06:39 [视频-长播] <|video_begin|> + 06:39 [视频-长播] <|video_begin|> + 06:39 [视频-长播] <|video_begin|> + 06:39 [视频-长播] <|video_begin|> + 06:44 [视频-长播] <|video_begin|> + 06:44 [视频-长播] <|video_begin|> + 06:44 [视频-长播] <|video_begin|> + 06:44 [视频-点赞/长播] <|video_begin|> + 06:49 [视频-长播] <|video_begin|> + 06:49 [视频-长播] <|video_begin|> + 06:59 [视频-点赞/长播] <|video_begin|> + 07:22 [视频-长播] <|video_begin|> + 07:30 [视频-长播] <|video_begin|> + 08:19 [视频-长播] <|video_begin|> + 08:19 [视频-长播] <|video_begin|> + 22:52 [视频-长播] <|video_begin|> +【2026-02-05】 + 02:33 [视频-点赞/长播] <|video_begin|> + 02:36 [视频-长播] <|video_begin|> + 02:36 [视频-长播] <|video_begin|> + 02:38 [视频-长播] <|video_begin|> + 02:43 [视频-长播] <|video_begin|> + 02:43 [视频-长播] <|video_begin|> + 02:45 [视频-长播] <|video_begin|> + 02:50 [视频-长播] <|video_begin|> + 02:51 [广告-点击] <|ad_begin|> + 02:51 [视频-长播] <|video_begin|> + 02:53 [视频-长播] <|video_begin|> + 02:53 [视频-长播] <|video_begin|> + 03:39 [视频-长播] <|video_begin|> + 04:00 [视频-长播] <|video_begin|> + 04:00 [视频-关注/点赞/长播] <|video_begin|> + 04:10 [视频-长播] <|video_begin|> + 04:31 [视频-关注/点赞/长播] <|video_begin|> + 04:42 [广告-点击] <|ad_begin|> + 04:44 [广告-深度转化] <|ad_begin|> + 04:44 [广告-点击] <|ad_begin|> +角色任务：你是一名极端严苛的用户行为数据挖掘专家，同时具备数据格式化能力，请根据以上用户交互历史，针对指定主题提取具有行为递进逻辑及内在关联的交互行为逻辑链。 +交互行为类型（固定格式严禁更改）： 商品-点击、商品-购买、搜索-搜索、直播-关注、直播-首次打赏、视频-浏览、视频-长播、广告-点击、广告-深度转化 +核心提取逻辑 (递进性准则)： +按时间顺序提取 5 步以内的行为链，要求后项交互B必须是前项交互A的场景需求协同补充、副作用诱因或兴趣细化升级——即 B 必须是因为 A 才产生的延伸需求，严禁提取任何品类平级、内容重复或仅因天气/促销产生的凑单并列行为。 +1.场景驱动协同：交互 B 与交互 A 必须处于同一生活场景和主题类目下，并具备极强的需求补完关系。 +2.兴趣因果递进：交互 B 需要体现为交互 A 之后衍生出的副作用需求或新需求，或者 A 是促使 B 出现的诱因。 +3.需求深度细化：在同一主题类目下，交互 B 的需求必须比交互 A 更具体、更细化，但不包括重复出现的购买、点击、搜索等行为，避免节点内容重复。 +请围绕以下主题提取行为逻辑链： +主题：从泛化滋补到聚焦成分的认知深化 + +输出格式：请以 JSON 对象形式返回，结构如下： +{ + "logic_chain": { + "name": "从泛化滋补到聚焦成分的认知深化", + "events": [ + { + "date": "YYYY-MM-DD", + "action": "[交互行为类型] 交互内容"（严格对应Timeline中交互条目，不允许省略）, + "logic": "逻辑说明" + } + ] + } +} + +强约束：最终答案必须是一个可被 json.loads 解析的 JSON，不能包含 Markdown、解释、重复键或 JSON 外额外字符。/no_think<|im_end|> +<|im_start|>assistant +{"logic_chain":{"name":"从泛化滋补到聚焦成分的认知深化","events":[{"date":"2025-04-19","action":"[商品-购买] <|prod_begin|>","logic":"初始阶段：购买复合成分的保健品（如人参、灵芝等），需求停留在“缓解疲劳”、“护肝”等宽泛的功能层面。"},{"date":"2026-01-25","action":"[视频-关注/点赞/长播] <|video_begin|>","logic":"认知跃迁：从被动购买成品，转变为主动学习特定核心成分（鹿鞭丸）的专业知识，包括“鉴别方法”、“食用方式”、“注意事项”。这标志着用户兴趣从宽泛的功能诉求，聚焦到了对某一具体成分的深度研究和品质甄别上，产生了显著的认知增量。"},{"date":"2026-02-04","action":"[视频-长播] <|video_begin|>","logic":"认知巩固与深化：在首次学习后，继续观看同类科普视频，进一步了解鹿鞭丸的“具体成分构成”（鹿茸、鹿尾、鹿津等）和更详细的“食用方法”。这表明用户正在构建关于该成分的系统知识体系，从“如何辨别”深化到“为何有效”的层面。"}]}}<|im_end|> +<|im_start|>user +【用户交互历史】： +【2023-10-22】 + --:-- [商品-购买] <|prod_begin|> +【2023-10-28】 + --:-- [商品-购买] <|prod_begin|> +【2023-11-02】 + --:-- [商品-购买] <|prod_begin|> +【2024-06-08】 + --:-- [商品-购买] <|prod_begin|> +【2024-10-04】 + --:-- [商品-购买] <|prod_begin|> +【2025-01-16】 + --:-- [直播-关注] <|living_begin|> +【2025-01-18】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-01-20】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-02-01】 + --:-- [商品-购买] <|prod_begin|> +【2025-02-05】 + --:-- [直播-关注] <|living_begin|> +【2025-02-13】 + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2025-03-02】 + --:-- [直播-关注] <|living_begin|> +【2025-04-04】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-04-06】 + --:-- [商品-购买] <|prod_begin|> +【2025-04-20】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-05-11】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-05-15】 + --:-- [直播-关注] <|living_begin|> +【2025-05-25】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-06-02】 + --:-- [直播-关注] <|living_begin|> +【2025-06-15】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-06-19】 + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-06-22】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2025-06-29】 + --:-- [直播-打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2025-07-01】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> +【2025-07-04】 + --:-- [直播-打赏] <|living_begin|> +【2025-07-05】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-07-06】 + --:-- [直播-关注] <|living_begin|> +【2025-07-10】 + --:-- [直播-打赏] <|living_begin|> +【2025-07-11】 + --:-- [直播-打赏] <|living_begin|> +【2025-07-18】 + --:-- [直播-关注] <|living_begin|> +【2025-07-20】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-07-22】 + --:-- [直播-关注] <|living_begin|> +【2025-07-23】 + --:-- [直播-关注] <|living_begin|> +【2025-07-24】 + --:-- [直播-关注] <|living_begin|> +【2025-07-28】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-07-29】 + --:-- [直播-关注] <|living_begin|> +【2025-07-31】 + --:-- [直播-关注] <|living_begin|> +【2025-08-14】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-17】 + --:-- [直播-关注] <|living_begin|> +【2025-08-22】 + --:-- [直播-关注] <|living_begin|> +【2025-08-23】 + --:-- [直播-关注] <|living_begin|> +【2025-08-29】 + --:-- [直播-关注] <|living_begin|> +【2025-09-07】 + --:-- [直播-关注] <|living_begin|> +【2025-09-10】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-09-18】 + --:-- [直播-关注] <|living_begin|> +【2025-09-21】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-02】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-03】 + --:-- [直播-关注] <|living_begin|> +【2025-10-14】 + --:-- [直播-关注/首次打赏] <|living_begin|> + --:-- [直播-首次打赏] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-22】 + --:-- [直播-关注] <|living_begin|> +【2025-10-26】 + --:-- [商品-点击] <|prod_begin|> +【2025-10-27】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-11-02】 + --:-- [商品-点击] <|prod_begin|> +【2025-11-03】 + --:-- [商品-点击] <|prod_begin|> +【2025-11-04】 + --:-- [商品-点击] <|prod_begin|> +【2025-11-06】 + --:-- [商品-点击] <|prod_begin|> +【2025-11-09】 + --:-- [商品-点击] <|prod_begin|> +【2025-11-10】 + --:-- [商品-点击] <|prod_begin|> +【2025-11-11】 + --:-- [商品-点击] <|prod_begin|> +【2025-11-15】 + --:-- [直播-关注] <|living_begin|> +【2025-11-23】 + --:-- [商品-点击] <|prod_begin|> +【2025-11-28】 + --:-- [商品-点击] <|prod_begin|> +【2025-11-30】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-10】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-11】 + 11:37 [广告-点击] <|ad_begin|> + 23:08 [广告-点击] <|ad_begin|> +【2025-12-13】 + 01:21 [广告-点击] <|ad_begin|> +【2025-12-14】 + 00:20 [广告-点击] <|ad_begin|> + 10:41 [广告-点击] <|ad_begin|> + 10:42 [广告-深度转化] <|ad_begin|> + 10:42 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-16】 + 01:08 [广告-点击] <|ad_begin|> + 13:06 [广告-点击] <|ad_begin|> +【2025-12-18】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-19】 + 10:38 [广告-点击] <|ad_begin|> + 17:10 [广告-点击] <|ad_begin|> + 23:51 [广告-点击] <|ad_begin|> +【2025-12-20】 + 02:46 [广告-点击] <|ad_begin|> + 11:38 [广告-点击] <|ad_begin|> +【2025-12-21】 + 00:59 [广告-深度转化] <|ad_begin|> + 00:59 [广告-点击] <|ad_begin|> + 09:01 [广告-点击] <|ad_begin|> +【2025-12-22】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-23】 + 11:24 [广告-点击] <|ad_begin|> + 12:39 [广告-点击] <|ad_begin|> + 12:44 [广告-点击] <|ad_begin|> + 12:45 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-24】 + 03:23 [广告-点击] <|ad_begin|> + 13:09 [广告-点击] <|ad_begin|> +【2025-12-25】 + 13:29 [广告-深度转化] <|ad_begin|> + 13:29 [广告-点击] <|ad_begin|> +【2025-12-27】 + --:-- [直播-关注/首次打赏] <|living_begin|> + 07:53 [广告-点击] <|ad_begin|> +【2025-12-28】 + --:-- [直播-关注/首次打赏] <|living_begin|> + 08:26 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-30】 + 23:23 [广告-点击] <|ad_begin|> +【2025-12-31】 + 20:44 [广告-点击] <|ad_begin|> +【2026-01-01】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + 07:10 [广告-点击] <|ad_begin|> +【2026-01-02】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-03】 + 01:04 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-05】 + 14:59 [广告-点击] <|ad_begin|> + 14:59 [广告-点击] <|ad_begin|> + 14:59 [广告-点击] <|ad_begin|> + 14:59 [广告-点击] <|ad_begin|> + 14:59 [广告-点击] <|ad_begin|> + 14:59 [广告-点击] <|ad_begin|> + 15:00 [广告-点击] <|ad_begin|> + 15:00 [广告-点击] <|ad_begin|> + 17:11 [广告-点击] <|ad_begin|> +【2026-01-06】 + 02:27 [广告-点击] <|ad_begin|> + 11:22 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 19:09 [广告-点击] <|ad_begin|> +【2026-01-07】 + 11:17 [广告-点击] <|ad_begin|> +【2026-01-09】 + 08:01 [广告-点击] <|ad_begin|> + 08:02 [广告-点击] <|ad_begin|> +【2026-01-10】 + 03:31 [广告-点击] <|ad_begin|> + 10:26 [广告-点击] <|ad_begin|> + 11:01 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-11】 + 04:51 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-12】 + --:-- [直播-关注] <|living_begin|> +【2026-01-13】 + --:-- [直播-关注] <|living_begin|> +【2026-01-15】 + --:-- [直播-打赏] <|living_begin|> + 23:08 [广告-点击] <|ad_begin|> +【2026-01-17】 + --:-- [直播-关注] <|living_begin|> + 05:31 [广告-点击] <|ad_begin|> +【2026-01-18】 + 03:03 [广告-点击] <|ad_begin|> + 04:14 [广告-深度转化] <|ad_begin|> + 04:14 [广告-点击] <|ad_begin|> + 13:19 [广告-点击] <|ad_begin|> + 13:21 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-19】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-20】 + --:-- [直播-关注] <|living_begin|> +【2026-01-21】 + 02:14 [广告-点击] <|ad_begin|> + 02:14 [广告-点击] <|ad_begin|> + 04:17 [广告-点击] <|ad_begin|> + 04:40 [广告-深度转化] <|ad_begin|> + 04:40 [广告-点击] <|ad_begin|> + 11:26 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-22】 + 09:53 [广告-点击] <|ad_begin|> + 15:20 [视频-评论/长播] <|video_begin|> + 23:10 [视频-转发/长播] <|video_begin|> +【2026-01-23】 + 07:04 [视频-评论/长播] <|video_begin|> + 08:16 [视频-转发/长播] <|video_begin|> + 11:12 [视频-转发/长播] <|video_begin|> + 13:42 [视频-收藏/长播] <|video_begin|> + 15:59 [视频-评论/长播] <|video_begin|> +【2026-01-24】 + --:-- [直播-首次打赏] <|living_begin|> + 11:54 [视频-评论/长播] <|video_begin|> + 12:00 [视频-评论/长播] <|video_begin|> +【2026-01-25】 + 08:17 [视频-评论/长播] <|video_begin|> + 08:25 [广告-点击] <|ad_begin|> + 08:26 [广告-点击] <|ad_begin|> + 08:33 [视频-收藏/长播] <|video_begin|> + 08:48 [广告-点击] <|ad_begin|> + 08:50 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-26】 + 08:31 [视频-关注/长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-27】 + 04:45 [视频-收藏/长播] <|video_begin|> + 06:07 [视频-评论/长播] <|video_begin|> + 06:14 [视频-收藏/长播] <|video_begin|> + 07:00 [广告-点击] <|ad_begin|> + 16:42 [视频-评论/长播] <|video_begin|> +【2026-01-28】 + 16:32 [视频-点赞/长播] <|video_begin|> + 16:50 [视频-点赞/长播] <|video_begin|> + 17:11 [视频-转发/长播] <|video_begin|> + 18:27 [视频-评论/长播] <|video_begin|> +【2026-01-29】 + 06:20 [视频-评论/长播] <|video_begin|> + 07:25 [广告-点击] <|ad_begin|> + 07:53 [视频-点赞/长播] <|video_begin|> + 07:53 [视频-点赞/长播] <|video_begin|> + 08:03 [视频-评论/长播] <|video_begin|> + 16:11 [广告-点击] <|ad_begin|> + 16:24 [视频-评论/长播] <|video_begin|> + 16:37 [广告-点击] <|ad_begin|> +【2026-01-30】 + 06:46 [视频-评论/长播] <|video_begin|> + 07:01 [广告-点击] <|ad_begin|> + 07:07 [视频-评论/长播] <|video_begin|> + 07:58 [视频-评论/长播] <|video_begin|> + 07:58 [视频-评论/点赞/长播] <|video_begin|> + 11:45 [视频-评论/长播] <|video_begin|> + 15:16 [视频-点赞/长播] <|video_begin|> +【2026-01-31】 + 04:01 [视频-收藏/长播] <|video_begin|> +【2026-02-01】 + --:-- [直播-关注] <|living_begin|> + 14:49 [广告-点击] <|ad_begin|> +【2026-02-02】 + 06:35 [视频-长播] <|video_begin|> + 06:47 [视频-长播] <|video_begin|> + 06:49 [视频-长播] <|video_begin|> + 06:49 [视频-长播] <|video_begin|> + 07:06 [视频-长播] <|video_begin|> + 07:06 [视频-长播] <|video_begin|> + 07:06 [视频-评论/长播] <|video_begin|> + 07:13 [视频-长播] <|video_begin|> + 07:14 [视频-长播] <|video_begin|> + 07:14 [视频-长播] <|video_begin|> + 07:14 [视频-长播] <|video_begin|> + 07:20 [视频-长播] <|video_begin|> + 07:29 [视频-长播] <|video_begin|> + 07:35 [视频-长播] <|video_begin|> + 07:53 [视频-长播] <|video_begin|> + 07:53 [视频-长播] <|video_begin|> + 14:04 [视频-点赞/长播] <|video_begin|> + 14:51 [视频-长播] <|video_begin|> + 14:51 [视频-长播] <|video_begin|> + 14:51 [视频-长播] <|video_begin|> + 15:16 [视频-长播] <|video_begin|> + 16:59 [视频-长播] <|video_begin|> + 16:59 [视频-长播] <|video_begin|> + 17:04 [视频-长播] <|video_begin|> + 17:05 [视频-长播] <|video_begin|> +【2026-02-03】 + 09:08 [视频-长播] <|video_begin|> + 09:10 [视频-评论/长播] <|video_begin|> + 10:12 [视频-收藏/长播] <|video_begin|> + 10:19 [视频-长播] <|video_begin|> + 10:19 [视频-长播] <|video_begin|> + 10:19 [视频-长播] <|video_begin|> + 10:27 [视频-长播] <|video_begin|> + 10:30 [视频-长播] <|video_begin|> + 10:46 [视频-转发/长播] <|video_begin|> + 17:45 [视频-长播] <|video_begin|> + 17:45 [视频-评论/长播] <|video_begin|> + 17:51 [视频-评论/长播] <|video_begin|> + 17:56 [视频-评论/长播] <|video_begin|> + 18:01 [视频-长播] <|video_begin|> + 18:08 [视频-长播] <|video_begin|> + 18:19 [视频-长播] <|video_begin|> + 18:19 [视频-评论/长播] <|video_begin|> + 18:22 [视频-长播] <|video_begin|> + 18:26 [视频-长播] <|video_begin|> + 18:26 [视频-长播] <|video_begin|> +【2026-02-04】 + 17:28 [视频-长播] <|video_begin|> + 17:28 [视频-长播] <|video_begin|> + 17:28 [视频-长播] <|video_begin|> + 17:30 [视频-长播] <|video_begin|> + 17:44 [视频-长播] <|video_begin|> + 17:49 [视频-长播] <|video_begin|> + 17:49 [视频-评论/长播] <|video_begin|> + 17:53 [视频-长播] <|video_begin|> + 18:30 [广告-点击] <|ad_begin|> +【2026-02-05】 + 05:21 [视频-长播] <|video_begin|> + 05:21 [视频-评论/长播] <|video_begin|> + 05:21 [视频-评论/长播] <|video_begin|> + 05:29 [视频-长播] <|video_begin|> + 05:35 [视频-长播] <|video_begin|> + 12:27 [视频-长播] <|video_begin|> + 12:27 [视频-长播] <|video_begin|> + 12:27 [视频-长播] <|video_begin|> + 12:27 [视频-长播] <|video_begin|> + 12:27 [视频-评论/长播] <|video_begin|> +角色任务：你需要扮演极端严苛的用户行为数据挖掘专家以及数据格式化专家，基于以上用户交互历史，针对给定主题识别并提取具有递进逻辑和内在联系的交互行为逻辑链。 +交互行为类型（固定格式严禁更改）： 视频-浏览、视频-长播、搜索-搜索、商品-点击、商品-购买、直播-关注、直播-首次打赏、广告-点击、广告-深度转化 +核心逻辑要求（递进性准则）： +请按时间顺序提取 5 步以内的行为链，且后项交互B必须构成前项交互A在场景需求上的协同补充、副作用诱因或兴趣细化升级——即 B 必须源于 A 所延伸出的需求，严禁提取任何品类平级、内容重复或仅由天气/促销触发的并列凑单行为。 +1.场景驱动协同：交互 B 与交互 A 必须同属一个生活场景及主题类目，并呈现极强的需求补完性。 +2.兴趣因果递进：交互 B 必须由交互 A 引发的副作用或新需求而产生，或者 A 本身就是 B 的诱因。 +3.需求深度细化：在同一主题类目中，交互 B 相比交互 A 应体现出更具体、更详细的需求层次，但不得包含多次重复的购买、点击、搜索等行为，以避免重复节点内容。 +请针对下列主题提取行为逻辑链： +主题：从泛化游戏兴趣到特定玩法（三角洲行动）的深度探索与技能学习 + +输出格式：请以 JSON 对象形式返回，结构如下： +{ + "logic_chain": { + "name": "从泛化游戏兴趣到特定玩法（三角洲行动）的深度探索与技能学习", + "events": [ + { + "date": "YYYY-MM-DD", + "action": "[交互行为类型] 交互内容"（严格对应Timeline中交互条目，不允许省略）, + "logic": "逻辑说明" + } + ] + } +} + +强约束：最终答案必须是一个可被 json.loads 解析的 JSON，不能包含 Markdown、解释、重复键或 JSON 外额外字符。/no_think<|im_end|> +<|im_start|>assistant +{"logic_chain":{"name":"从泛化游戏兴趣到特定玩法（三角洲行动）的深度探索与技能学习","events":[{"date":"2025-12-21","action":"[广告-点击] <|ad_begin|>","logic":"兴趣萌芽：用户处于游戏兴趣的广泛探索期，被动点击各类游戏广告，对角色、升级等玩法有泛化兴趣。"},{"date":"2026-01-22","action":"[视频-转发/长播] <|video_begin|>","logic":"兴趣聚焦：首次出现对特定游戏《三角洲行动》的主动深度互动（转发），关注点从泛化的游戏概念转向具体的“装备策略”和“操作技巧”。"},{"date":"2026-01-28","action":"[视频-点赞/长播] <|video_begin|>","logic":"认知深化：兴趣点进一步收敛到游戏内的具体装备（M14步枪）和核心玩法（个性化改装），开始主动学习如何通过“配件调整”来“提升精度稳定性”，体现了从玩家到研究者的认知跃迁。"},{"date":"2026-01-30","action":"[视频-评论/长播] <|video_begin|>","logic":"技能精通与闭环：用户已不满足于通用攻略，开始研究更具体的“成本控制”、“配件平衡”等高阶改装策略，并进行评论互动，标志着其在该游戏领域的知识体系已趋于完善和闭环。"}]}}<|im_end|> +<|im_start|>user +【用户交互历史】： +【2025-03-21】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-04-08】 + --:-- [直播-关注] <|living_begin|> +【2025-04-09】 + --:-- [直播-关注] <|living_begin|> +【2025-04-10】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-04-11】 + --:-- [商品-购买] <|prod_begin|> +【2025-04-14】 + --:-- [直播-关注] <|living_begin|> +【2025-05-06】 + --:-- [直播-关注] <|living_begin|> +【2025-05-10】 + --:-- [直播-关注] <|living_begin|> +【2025-05-17】 + --:-- [商品-购买] <|prod_begin|> +【2025-05-18】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-05-19】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-05-21】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-06-02】 + --:-- [直播-关注] <|living_begin|> +【2025-06-12】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-17】 + --:-- [直播-关注] <|living_begin|> +【2025-07-05】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-25】 + --:-- [直播-关注] <|living_begin|> +【2025-07-26】 + --:-- [直播-关注] <|living_begin|> +【2025-07-27】 + --:-- [商品-购买] <|prod_begin|> +【2025-07-28】 + --:-- [商品-购买] <|prod_begin|> +【2025-08-05】 + --:-- [直播-关注] <|living_begin|> +【2025-08-10】 + --:-- [直播-关注/首次打赏] <|living_begin|> +【2025-08-15】 + --:-- [直播-关注] <|living_begin|> +【2025-08-22】 + --:-- [直播-关注] <|living_begin|> +【2025-08-27】 + --:-- [直播-关注] <|living_begin|> +【2025-08-29】 + --:-- [直播-关注] <|living_begin|> +【2025-09-08】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-12】 + --:-- [直播-关注] <|living_begin|> +【2025-09-14】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-09-26】 + --:-- [直播-关注] <|living_begin|> +【2025-09-28】 + --:-- [直播-关注] <|living_begin|> +【2025-09-30】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-01】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-10-06】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-08】 + --:-- [商品-购买] <|prod_begin|> +【2025-10-10】 + --:-- [直播-关注] <|living_begin|> +【2025-10-12】 + --:-- [直播-关注] <|living_begin|> +【2025-10-20】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-10-22】 + --:-- [直播-关注] <|living_begin|> +【2025-10-26】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-10-29】 + --:-- [直播-关注] <|living_begin|> +【2025-10-31】 + --:-- [直播-关注] <|living_begin|> +【2025-11-07】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-14】 + --:-- [直播-关注] <|living_begin|> +【2025-11-17】 + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-11-18】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-20】 + --:-- [商品-购买] <|prod_begin|> +【2025-11-23】 + --:-- [直播-关注] <|living_begin|> +【2025-11-24】 + --:-- [直播-关注] <|living_begin|> +【2025-11-25】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-11-26】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-12-01】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-12-04】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-05】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-08】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> +【2025-12-14】 + --:-- [直播-首次打赏] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-21】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-23】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-24】 + --:-- [直播-关注] <|living_begin|> +【2025-12-25】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-26】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2025-12-27】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2025-12-30】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-31】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-04】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> +【2026-01-10】 + 02:00 [广告-深度转化] <|ad_begin|> + 08:29 [广告-深度转化] <|ad_begin|> + 11:00 [广告-深度转化] <|ad_begin|> + 13:30 [广告-深度转化] <|ad_begin|> + 15:08 [广告-深度转化] <|ad_begin|> +【2026-01-12】 + 02:22 [广告-深度转化] <|ad_begin|> + 05:52 [广告-深度转化] <|ad_begin|> + 08:27 [广告-深度转化] <|ad_begin|> + 14:27 [广告-深度转化] <|ad_begin|> +【2026-01-13】 + --:-- [直播-关注] <|living_begin|> + 16:57 [广告-深度转化] <|ad_begin|> + 17:16 [广告-深度转化] <|ad_begin|> +【2026-01-14】 + 13:26 [广告-深度转化] <|ad_begin|> + 13:47 [广告-深度转化] <|ad_begin|> + 14:32 [广告-深度转化] <|ad_begin|> + 14:39 [广告-深度转化] <|ad_begin|> + 15:26 [广告-深度转化] <|ad_begin|> +【2026-01-15】 + 08:23 [广告-深度转化] <|ad_begin|> + 11:02 [广告-深度转化] <|ad_begin|> +【2026-01-16】 + 03:17 [广告-深度转化] <|ad_begin|> + 06:11 [广告-深度转化] <|ad_begin|> + 11:09 [广告-深度转化] <|ad_begin|> + 11:18 [广告-深度转化] <|ad_begin|> + 14:11 [广告-深度转化] <|ad_begin|> + 15:55 [广告-深度转化] <|ad_begin|> + 16:45 [广告-深度转化] <|ad_begin|> + 17:10 [广告-深度转化] <|ad_begin|> + 17:10 [广告-点击] <|ad_begin|> + 20:20 [广告-点击] <|ad_begin|> +【2026-01-17】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 03:32 [广告-深度转化] <|ad_begin|> + 03:32 [广告-点击] <|ad_begin|> + 07:28 [广告-深度转化] <|ad_begin|> + 07:28 [广告-点击] <|ad_begin|> + 07:55 [广告-深度转化] <|ad_begin|> + 07:55 [广告-点击] <|ad_begin|> + 11:59 [广告-深度转化] <|ad_begin|> + 11:59 [广告-点击] <|ad_begin|> +【2026-01-18】 + 00:18 [广告-深度转化] <|ad_begin|> + 00:18 [广告-点击] <|ad_begin|> +【2026-01-19】 + 02:56 [广告-点击] <|ad_begin|> + 05:36 [广告-深度转化] <|ad_begin|> + 05:36 [广告-点击] <|ad_begin|> + 14:33 [广告-深度转化] <|ad_begin|> + 14:33 [广告-点击] <|ad_begin|> +【2026-01-20】 + --:-- [直播-关注] <|living_begin|> + 16:03 [广告-深度转化] <|ad_begin|> + 16:03 [广告-点击] <|ad_begin|> +【2026-01-21】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 07:21 [广告-深度转化] <|ad_begin|> + 07:21 [广告-点击] <|ad_begin|> + 09:21 [广告-深度转化] <|ad_begin|> + 09:21 [广告-点击] <|ad_begin|> + 14:09 [广告-点击] <|ad_begin|> + 16:16 [广告-深度转化] <|ad_begin|> + 16:16 [广告-点击] <|ad_begin|> +【2026-01-22】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 06:29 [广告-点击] <|ad_begin|> + 11:59 [广告-深度转化] <|ad_begin|> + 11:59 [广告-点击] <|ad_begin|> +【2026-01-23】 + --:-- [直播-关注] <|living_begin|> + 02:52 [视频-长播] <|video_begin|> + 12:28 [广告-点击] <|ad_begin|> + 13:00 [广告-深度转化] <|ad_begin|> + 13:00 [广告-点击] <|ad_begin|> +【2026-01-24】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + 11:10 [广告-点击] <|ad_begin|> + 13:16 [广告-深度转化] <|ad_begin|> + 13:16 [广告-点击] <|ad_begin|> + 13:57 [广告-深度转化] <|ad_begin|> + 13:57 [广告-点击] <|ad_begin|> +【2026-01-25】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + 04:45 [广告-深度转化] <|ad_begin|> + 04:45 [广告-点击] <|ad_begin|> + 13:33 [广告-点击] <|ad_begin|> + 15:54 [广告-点击] <|ad_begin|> + 15:59 [广告-深度转化] <|ad_begin|> + 15:59 [广告-点击] <|ad_begin|> + 22:03 [广告-点击] <|ad_begin|> +【2026-01-26】 + --:-- [直播-关注] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + 04:39 [视频-长播] <|video_begin|> + 04:39 [视频-长播] <|video_begin|> + 04:39 [视频-长播] <|video_begin|> + 04:49 [广告-深度转化] <|ad_begin|> + 04:49 [广告-点击] <|ad_begin|> + 11:19 [广告-点击] <|ad_begin|> + 11:38 [广告-点击] <|ad_begin|> + 13:03 [广告-点击] <|ad_begin|> + 13:13 [广告-深度转化] <|ad_begin|> + 13:13 [广告-点击] <|ad_begin|> +【2026-01-27】 + 02:00 [广告-深度转化] <|ad_begin|> + 02:00 [广告-点击] <|ad_begin|> + 15:03 [广告-深度转化] <|ad_begin|> + 15:03 [广告-点击] <|ad_begin|> + 16:09 [视频-长播] <|video_begin|> +【2026-01-28】 + 00:10 [广告-点击] <|ad_begin|> + 02:15 [视频-长播] <|video_begin|> + 02:15 [视频-长播] <|video_begin|> + 02:15 [视频-关注/长播] <|video_begin|> + 02:18 [视频-长播] <|video_begin|> + 02:18 [视频-长播] <|video_begin|> + 02:28 [视频-长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-购买] <|prod_begin|> + 02:31 [广告-点击] <|ad_begin|> + 13:43 [广告-点击] <|ad_begin|> + 20:56 [广告-点击] <|ad_begin|> +【2026-01-29】 + 11:14 [广告-深度转化] <|ad_begin|> + 11:14 [广告-点击] <|ad_begin|> + 11:40 [广告-点击] <|ad_begin|> + 13:39 [广告-点击] <|ad_begin|> +【2026-01-30】 + --:-- [直播-关注] <|living_begin|> + --:-- [直播-关注] <|living_begin|> + --:-- [商品-点击] <|prod_begin|> + 05:54 [视频-长播] <|video_begin|> + 10:00 [广告-点击] <|ad_begin|> + 12:26 [广告-点击] <|ad_begin|> + 13:45 [广告-深度转化] <|ad_begin|> + 13:45 [广告-点击] <|ad_begin|> + 15:40 [广告-深度转化] <|ad_begin|> + 15:40 [广告-点击] <|ad_begin|> +【2026-01-31】 + 07:55 [广告-深度转化] <|ad_begin|> + 07:55 [广告-点击] <|ad_begin|> + 18:27 [广告-点击] <|ad_begin|> +【2026-02-01】 + 11:44 [视频-长播] <|video_begin|> + 13:31 [广告-深度转化] <|ad_begin|> + 13:31 [广告-点击] <|ad_begin|> + 13:55 [广告-深度转化] <|ad_begin|> + 13:55 [广告-点击] <|ad_begin|> + 14:50 [广告-深度转化] <|ad_begin|> + 14:50 [广告-点击] <|ad_begin|> + 15:25 [广告-深度转化] <|ad_begin|> + 15:25 [广告-点击] <|ad_begin|> + 22:18 [广告-深度转化] <|ad_begin|> + 22:18 [广告-点击] <|ad_begin|> +【2026-02-02】 + --:-- [直播-关注] <|living_begin|> + 03:27 [广告-点击] <|ad_begin|> + 07:21 [广告-深度转化] <|ad_begin|> + 07:21 [广告-点击] <|ad_begin|> + 12:07 [广告-深度转化] <|ad_begin|> + 12:07 [广告-点击] <|ad_begin|> + 13:50 [广告-深度转化] <|ad_begin|> + 13:50 [广告-点击] <|ad_begin|> +【2026-02-03】 + 11:03 [广告-深度转化] <|ad_begin|> + 11:03 [广告-点击] <|ad_begin|> + 12:56 [广告-深度转化] <|ad_begin|> + 12:56 [广告-点击] <|ad_begin|> + 13:22 [广告-深度转化] <|ad_begin|> + 13:22 [广告-点击] <|ad_begin|> + 15:57 [广告-深度转化] <|ad_begin|> + 15:57 [广告-点击] <|ad_begin|> +【2026-02-04】 + 00:11 [视频-长播] <|video_begin|> + 12:00 [广告-深度转化] <|ad_begin|> + 12:00 [广告-点击] <|ad_begin|> + 15:11 [广告-深度转化] <|ad_begin|> + 15:11 [广告-点击] <|ad_begin|> + 15:27 [广告-点击] <|ad_begin|> + 16:04 [广告-点击] <|ad_begin|> + 16:23 [视频-长播] <|video_begin|> + 16:23 [视频-长播] <|video_begin|> + 16:23 [视频-长播] <|video_begin|> + 16:46 [广告-深度转化] <|ad_begin|> + 16:46 [广告-点击] <|ad_begin|> +【2026-02-05】 + 03:14 [广告-点击] <|ad_begin|> + 11:49 [广告-深度转化] <|ad_begin|> + 11:49 [广告-点击] <|ad_begin|> + 12:05 [广告-深度转化] <|ad_begin|> + 12:05 [广告-点击] <|ad_begin|> + 13:32 [广告-深度转化] <|ad_begin|> + 13:32 [广告-点击] <|ad_begin|> + 14:49 [广告-深度转化] <|ad_begin|> + 14:49 [广告-点击] <|ad_begin|> +角色任务：你是一名极端严苛的用户行为数据挖掘专家和数据格式化专家，请基于以上用户交互历史，围绕指定主题提取具备行为递进关系与内在关联的交互行为逻辑链。 +交互行为类型（固定格式严禁更改）： 视频-浏览、视频-长播、搜索-搜索、商品-点击、商品-购买、直播-关注、直播-首次打赏、广告-点击、广告-深度转化 +核心判定逻辑（递进性准则）： +按时间顺序提取 5 步以内的行为链，要求后项交互B必须是前项交互A的场景需求协同补充、副作用诱因或兴趣细化升级——即 B 必须是因为 A 才产生的延伸需求，严禁提取任何品类平级、内容重复或仅因天气/促销产生的凑单并列行为。 +1.场景驱动协同：交互 B 相对于交互 A，必须在同一生活场景与主题类目下形成强需求补完关系。 +2.兴趣因果递进：交互 B 是因为 交互 A 产生的副作用或新需求，或者 A 是 B 的诱因。 +3.需求深度细化：在同一主题类目下,交互 B 的需求比 交互 A 更具体详细, 但不包括多次重复的购买、点击、搜索等行为，避免重复节点内容。 +请面向以下主题提取行为逻辑链： +主题：从被动观看视频到主动购买关联产品的兴趣转化 + +输出格式：请以 JSON 对象形式返回，结构如下： +{ + "logic_chain": { + "name": "从被动观看视频到主动购买关联产品的兴趣转化", + "events": [ + { + "date": "YYYY-MM-DD", + "action": "[交互行为类型] 交互内容"（严格对应Timeline中交互条目，不允许省略）, + "logic": "逻辑说明" + } + ] + } +} + +强约束：最终答案必须是一个可被 json.loads 解析的 JSON，不能包含 Markdown、解释、重复键或 JSON 外额外字符。/think<|im_end|> +<|im_start|>assistant + +按时间顺序筛选关键交互，抽取兴趣变化和行为转化链路，最终只返回合法 JSON。 + +{"logic_chain":{"name":"从被动观看视频到主动购买关联产品的兴趣转化","events":[{"date":"2026-01-28","action":"[视频-长播] <|video_begin|>","logic":"兴趣触发：被动接收到一个关于“太阳能扎带灯”的具体产品介绍视频，了解了其功能、特性（环保、便捷）和应用场景（庭院）。"},{"date":"2026-01-28","action":"[商品-点击] <|prod_begin|>","logic":"行为深化与验证：在观看视频后极短时间内，用户从被动观看转为主动点击商品，关键词“太阳能”、“庭院”、“围栏”、“扎带灯”与视频内容高度匹配，表明兴趣已被成功激发并进入产品筛选阶段。"},{"date":"2026-01-28","action":"[商品-购买] <|prod_begin|>","logic":"决策闭环：在点击验证后，用户迅速完成了购买行为，形成了“观看视频获取认知 -> 点击商品进行比对 -> 购买商品完成转化”的完整、紧凑且逻辑清晰的行为链。"}]}}<|im_end|> +<|im_start|>user +【用户交互历史】： +【2024-11-29】 + --:-- [商品-购买] <|prod_begin|> +【2024-11-30】 + --:-- [商品-购买] <|prod_begin|> +【2024-12-21】 + --:-- [商品-购买] <|prod_begin|> +【2024-12-23】 + --:-- [商品-购买] <|prod_begin|> +【2025-05-13】 + --:-- [直播-关注] <|living_begin|> +【2025-06-12】 + --:-- [商品-购买] <|prod_begin|> +【2025-06-19】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-16】 + --:-- [商品-购买] <|prod_begin|> +【2025-09-25】 + --:-- [直播-首次打赏] <|living_begin|> +【2025-11-14】 + --:-- [直播-关注] <|living_begin|> +【2025-12-08】 + 11:34 [广告-点击] <|ad_begin|> +【2025-12-24】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-25】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-27】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-28】 + --:-- [商品-点击] <|prod_begin|> +【2025-12-29】 + 06:08 [广告-点击] <|ad_begin|> +【2026-01-04】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-06】 + 01:01 [广告-点击] <|ad_begin|> +【2026-01-07】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-08】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-09】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-10】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-11】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-12】 + 00:37 [广告-点击] <|ad_begin|> + 00:48 [广告-深度转化] <|ad_begin|> + 00:48 [广告-点击] <|ad_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-16】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-17】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-20】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-21】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-22】 + 12:31 [视频-转发/长播] <|video_begin|> +【2026-01-23】 + 00:14 [视频-转发/长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-24】 + 01:23 [视频-转发/长播] <|video_begin|> + 01:30 [广告-点击] <|ad_begin|> + 02:11 [视频-转发/长播] <|video_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-25】 + 05:52 [视频-收藏/长播] <|video_begin|> + 06:31 [视频-浏览] <|video_begin|> +【2026-01-26】 + --:-- [商品-点击] <|prod_begin|> +【2026-01-27】 + --:-- [商品-点击] <|prod_begin|> + --:-- [商品-点击] <|prod_begin|> +【2026-01-28】 + 07:00 [视频-转发/长播] <|video_begin|> +【2026-01-29】 + 08:27 [视频-浏览] <|video_begin|> +【2026-01-30】 + 14:44 [视频-浏览] <|video_begin|> +【2026-02-04】 + 05:33 [视频-收藏/长播] <|video_begin|> + 07:21 [视频-浏览] <|video_begin|> + 14:38 [视频-收藏/长播] <|video_begin|> +【2026-02-05】 + 09:04 [视频-长播] <|video_begin|> + 09:04 [视频-长播] <|video_begin|> + 09:04 [视频-长播] <|video_begin|> + 09:04 [视频-长播] <|video_begin|> + 09:05 [视频-长播] <|video_begin|> + 09:07 [视频-长播] <|video_begin|> + 09:07 [视频-长播] <|video_begin|> + 09:07 [视频-长播] <|video_begin|> + 09:08 [视频-长播] <|video_begin|> + 09:08 [视频-长播] <|video_begin|> + 09:08 [视频-长播] <|video_begin|> + 09:09 [视频-长播] <|video_begin|> + 09:09 [视频-长播] <|video_begin|> + 09:09 [视频-长播] <|video_begin|> + 09:12 [视频-长播] <|video_begin|> + 09:12 [视频-长播] <|video_begin|> + 09:12 [视频-长播] <|video_begin|> + 09:12 [视频-长播] <|video_begin|> + 09:12 [视频-长播] <|video_begin|> + 09:13 [视频-长播] <|video_begin|> + 09:13 [视频-长播] <|video_begin|> + 09:24 [视频-长播] <|video_begin|> + 09:28 [视频-长播] <|video_begin|> + 09:28 [视频-长播] <|video_begin|> + 09:28 [视频-长播] <|video_begin|> + 09:30 [视频-长播] <|video_begin|> + 09:30 [视频-长播] <|video_begin|> + 09:30 [视频-长播] <|video_begin|> + 09:36 [视频-长播] <|video_begin|> + 09:36 [视频-长播] <|video_begin|> + 09:36 [视频-长播] <|video_begin|> + 09:36 [视频-长播] <|video_begin|> + 09:36 [视频-长播] <|video_begin|> + 09:36 [视频-长播] <|video_begin|> + 09:36 [视频-长播] <|video_begin|> + 09:38 [视频-长播] <|video_begin|> + 09:38 [视频-长播] <|video_begin|> + 09:38 [视频-长播] <|video_begin|> + 09:38 [视频-长播] <|video_begin|> + 09:49 [视频-长播] <|video_begin|> + 09:49 [视频-长播] <|video_begin|> + 09:49 [视频-长播] <|video_begin|> + 09:49 [视频-长播] <|video_begin|> + 09:51 [视频-长播] <|video_begin|> + 09:51 [视频-长播] <|video_begin|> + 09:53 [视频-长播] <|video_begin|> + 09:53 [视频-长播] <|video_begin|> + 09:53 [视频-长播] <|video_begin|> + 09:56 [视频-长播] <|video_begin|> + 14:40 [视频-长播] <|video_begin|> + +角色任务：你需要以极端严苛的用户行为数据挖掘专家及数据格式化专家的身份，基于以上交互历史，针对给定主题筛选并提取出全部相关的历史交互行为。 + +主题：从被动接收广告到主动探索解决方案的健康焦虑演化 + +输出格式要求：请务必仅返回一个包含 SID 的 JSON 数组，不要附带任何额外的文字解释或冗余内容。 + +强约束：最终答案必须是一个可被 json.loads 解析的 JSON，不能包含 Markdown、解释、重复键或 JSON 外额外字符。/no_think<|im_end|> +<|im_start|>assistant +["<|ad_begin|>","<|video_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>"]<|im_end|> +<|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|><|endoftext|> +label_ids: +[-100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, -100, 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loading configuration file /home/ll/llm4rec/experiments/outputs/v26_v21_product_rec_rebalance_lr22e6_ep032/config.json +[INFO|configuration_utils.py:847] 2026-07-12 04:26:28,212 >> Model config Qwen3Config { + "architectures": [ + "Qwen3ForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": null, + "dtype": "bfloat16", + "eos_token_id": 151645, + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 1024, + "initializer_range": 0.02, + "intermediate_size": 3072, + "layer_types": [ + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention", + "full_attention" + ], + "max_position_embeddings": 40960, + "max_window_layers": 28, + "model_type": "qwen3", + "num_attention_heads": 16, + "num_hidden_layers": 28, + "num_key_value_heads": 8, + "pad_token_id": 151643, + "rms_norm_eps": 1e-06, + "rope_parameters": { + "rope_theta": 1000000, + "rope_type": "default" + }, + "sliding_window": null, + "tie_word_embeddings": false, + "transformers_version": "5.6.0", + "use_cache": false, + "use_sliding_window": false, + "vocab_size": 176253 +} + + +labels: +["<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|video_begin|>","<|video_begin|>","<|video_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|video_begin|>","<|prod_begin|>"]<|im_end|> +{"logic_chain":{"name":"从泛化滋补到聚焦成分的认知深化","events":[{"date":"2025-04-19","action":"[商品-购买] <|prod_begin|>","logic":"初始阶段：购买复合成分的保健品（如人参、灵芝等），需求停留在“缓解疲劳”、“护肝”等宽泛的功能层面。"},{"date":"2026-01-25","action":"[视频-关注/点赞/长播] <|video_begin|>","logic":"认知跃迁：从被动购买成品，转变为主动学习特定核心成分（鹿鞭丸）的专业知识，包括“鉴别方法”、“食用方式”、“注意事项”。这标志着用户兴趣从宽泛的功能诉求，聚焦到了对某一具体成分的深度研究和品质甄别上，产生了显著的认知增量。"},{"date":"2026-02-04","action":"[视频-长播] <|video_begin|>","logic":"认知巩固与深化：在首次学习后，继续观看同类科普视频，进一步了解鹿鞭丸的“具体成分构成”（鹿茸、鹿尾、鹿津等）和更详细的“食用方法”。这表明用户正在构建关于该成分的系统知识体系，从“如何辨别”深化到“为何有效”的层面。"}]}}<|im_end|> +{"logic_chain":{"name":"从泛化游戏兴趣到特定玩法（三角洲行动）的深度探索与技能学习","events":[{"date":"2025-12-21","action":"[广告-点击] <|ad_begin|>","logic":"兴趣萌芽：用户处于游戏兴趣的广泛探索期，被动点击各类游戏广告，对角色、升级等玩法有泛化兴趣。"},{"date":"2026-01-22","action":"[视频-转发/长播] <|video_begin|>","logic":"兴趣聚焦：首次出现对特定游戏《三角洲行动》的主动深度互动（转发），关注点从泛化的游戏概念转向具体的“装备策略”和“操作技巧”。"},{"date":"2026-01-28","action":"[视频-点赞/长播] <|video_begin|>","logic":"认知深化：兴趣点进一步收敛到游戏内的具体装备（M14步枪）和核心玩法（个性化改装），开始主动学习如何通过“配件调整”来“提升精度稳定性”，体现了从玩家到研究者的认知跃迁。"},{"date":"2026-01-30","action":"[视频-评论/长播] <|video_begin|>","logic":"技能精通与闭环：用户已不满足于通用攻略，开始研究更具体的“成本控制”、“配件平衡”等高阶改装策略，并进行评论互动，标志着其在该游戏领域的知识体系已趋于完善和闭环。"}]}}<|im_end|> + +按时间顺序筛选关键交互，抽取兴趣变化和行为转化链路，最终只返回合法 JSON。 + +{"logic_chain":{"name":"从被动观看视频到主动购买关联产品的兴趣转化","events":[{"date":"2026-01-28","action":"[视频-长播] <|video_begin|>","logic":"兴趣触发：被动接收到一个关于“太阳能扎带灯”的具体产品介绍视频，了解了其功能、特性（环保、便捷）和应用场景（庭院）。"},{"date":"2026-01-28","action":"[商品-点击] <|prod_begin|>","logic":"行为深化与验证：在观看视频后极短时间内，用户从被动观看转为主动点击商品，关键词“太阳能”、“庭院”、“围栏”、“扎带灯”与视频内容高度匹配，表明兴趣已被成功激发并进入产品筛选阶段。"},{"date":"2026-01-28","action":"[商品-购买] <|prod_begin|>","logic":"决策闭环：在点击验证后，用户迅速完成了购买行为，形成了“观看视频获取认知 -> 点击商品进行比对 -> 购买商品完成转化”的完整、紧凑且逻辑清晰的行为链。"}]}}<|im_end|> +["<|ad_begin|>","<|video_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>","<|prod_begin|>"]<|im_end|> + +[INFO|2026-07-12 04:26:28] llamafactory.model.model_utils.kv_cache:144 >> KV cache is disabled during training. +[INFO|2026-07-12 04:26:28] llamafactory.model.model_utils.liger_kernel:144 >> Liger kernel has been applied to the model. +[INFO|modeling_utils.py:748] 2026-07-12 04:26:28,765 >> loading weights file /home/ll/llm4rec/experiments/outputs/v26_v21_product_rec_rebalance_lr22e6_ep032/model.safetensors +[INFO|modeling_utils.py:821] 2026-07-12 04:26:28,765 >> Will use dtype=torch.bfloat16 as defined in model's config object +[INFO|configuration_utils.py:1027] 2026-07-12 04:26:28,827 >> Generate config GenerationConfig { + "eos_token_id": 151645, + "output_attentions": false, + "output_hidden_states": false, + "pad_token_id": 151643, + "use_cache": false +} + + Loading weights: 0%| | 0/311 [00:00> loading configuration file /home/ll/llm4rec/experiments/outputs/v26_v21_product_rec_rebalance_lr22e6_ep032/generation_config.json +[INFO|configuration_utils.py:1027] 2026-07-12 04:26:29,197 >> Generate config GenerationConfig { + "do_sample": true, + "eos_token_id": [ + 151645, + 151643 + ], + "pad_token_id": 151643, + "temperature": 0.6, + "top_k": 20, + "top_p": 0.95 +} + +[INFO|dynamic_module_utils.py:406] 2026-07-12 04:26:29,197 >> Could not locate the custom_generate/generate.py inside /home/ll/llm4rec/experiments/outputs/v26_v21_product_rec_rebalance_lr22e6_ep032. +[INFO|2026-07-12 04:26:29] llamafactory.model.model_utils.checkpointing:144 >> Gradient checkpointing enabled. +[INFO|2026-07-12 04:26:29] llamafactory.model.model_utils.attention:144 >> Using FlashAttention-2 for faster training and inference. +[INFO|2026-07-12 04:26:29] llamafactory.model.adapter:144 >> Pure bf16 / BAdam detected, remaining trainable params in half precision. +[INFO|2026-07-12 04:26:29] llamafactory.model.adapter:144 >> Fine-tuning method: Full +[INFO|2026-07-12 04:26:29] llamafactory.model.loader:144 >> trainable params: 801,433,600 || all params: 801,433,600 || trainable%: 100.0000 +[INFO|trainer.py:1469] 2026-07-12 04:26:29,362 >> ***** Running training ***** +[INFO|trainer.py:1470] 2026-07-12 04:26:29,362 >> Num examples = 904 +[INFO|trainer.py:1471] 2026-07-12 04:26:29,362 >> Num Epochs = 1 +[INFO|trainer.py:1472] 2026-07-12 04:26:29,362 >> Num update steps per epoch = 226 +[INFO|trainer.py:1473] 2026-07-12 04:26:29,362 >> Instantaneous batch size per device = 1 +[INFO|trainer.py:1476] 2026-07-12 04:26:29,362 >> Total train batch size (w. parallel, distributed & accumulation) = 4 +[INFO|trainer.py:1477] 2026-07-12 04:26:29,362 >> Gradient Accumulation steps = 4 +[INFO|trainer.py:1478] 2026-07-12 04:26:29,362 >> Total optimization steps = 50 +[INFO|trainer.py:1479] 2026-07-12 04:26:29,362 >> Number of trainable parameters = 801,433,600 + 0%| | 0/50 [00:00> 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Do not forget to share your model on huggingface.co/models =) + + + 100%|██████████| 50/50 [07:10<00:00, 8.31s/it] 100%|██████████| 50/50 [07:10<00:00, 8.62s/it] +[INFO|trainer.py:3815] 2026-07-12 04:33:40,345 >> Saving model checkpoint to /home/ll/llm4rec/experiments/outputs/v28_v26_no_template_product_world_lr12e6_ep022 +[INFO|configuration_utils.py:533] 2026-07-12 04:33:40,347 >> Configuration saved in /home/ll/llm4rec/experiments/outputs/v28_v26_no_template_product_world_lr12e6_ep022/config.json +[INFO|configuration_utils.py:816] 2026-07-12 04:33:40,347 >> Configuration saved in /home/ll/llm4rec/experiments/outputs/v28_v26_no_template_product_world_lr12e6_ep022/generation_config.json +{'loss': '1.658', 'grad_norm': '15.94', 'learning_rate': '1.189e-06', 'epoch': '0.02212'} +{'loss': '1.527', 'grad_norm': '11.69', 'learning_rate': '1.123e-06', 'epoch': '0.04425'} +{'loss': '1.501', 'grad_norm': '9.562', 'learning_rate': '1.003e-06', 'epoch': '0.06637'} +{'loss': '1.495', 'grad_norm': '10.69', 'learning_rate': '8.429e-07', 'epoch': '0.0885'} +{'loss': '1.626', 'grad_norm': '12.19', 'learning_rate': '6.576e-07', 'epoch': '0.1106'} +{'loss': '1.639', 'grad_norm': '12.75', 'learning_rate': '4.665e-07', 'epoch': '0.1327'} +{'loss': '1.557', 'grad_norm': '21.88', 'learning_rate': '2.89e-07', 'epoch': '0.1549'} +{'loss': '1.526', 'grad_norm': '11.75', 'learning_rate': '1.431e-07', 'epoch': '0.177'} +{'loss': '1.522', 'grad_norm': '23.5', 'learning_rate': '4.385e-08', 'epoch': '0.1991'} +{'loss': '1.646', 'grad_norm': '10.62', 'learning_rate': '1.233e-09', 'epoch': '0.2212'} +{'train_runtime': '431', 'train_samples_per_second': '0.461', 'train_steps_per_second': '0.116', 'train_loss': '1.57', 'epoch': '0.2212'} + Writing model shards: 0%| | 0/1 [00:00> Model weights saved in /home/ll/llm4rec/experiments/outputs/v28_v26_no_template_product_world_lr12e6_ep022/model.safetensors +[INFO|tokenization_utils_base.py:3278] 2026-07-12 04:33:41,299 >> chat template saved in /home/ll/llm4rec/experiments/outputs/v28_v26_no_template_product_world_lr12e6_ep022/chat_template.jinja +[INFO|tokenization_utils_base.py:2111] 2026-07-12 04:33:41,320 >> tokenizer config file saved in /home/ll/llm4rec/experiments/outputs/v28_v26_no_template_product_world_lr12e6_ep022/tokenizer_config.json +***** train metrics ***** + epoch = 0.2212 + total_flos = 21927124GF + train_loss = 1.5697 + train_runtime = 0:07:10.98 + train_samples_per_second = 0.461 + train_steps_per_second = 0.116 +Figure saved at: /home/ll/llm4rec/experiments/outputs/v28_v26_no_template_product_world_lr12e6_ep022/training_loss.png +[WARNING|2026-07-12 04:33:41] llamafactory.extras.ploting:149 >> No metric eval_loss to plot. +[WARNING|2026-07-12 04:33:41] llamafactory.extras.ploting:149 >> No metric eval_accuracy to plot. +[INFO|modelcard.py:263] 2026-07-12 04:33:41,418 >> Dropping the following result as it does not have all the necessary fields: +{'task': {'name': 'Causal Language Modeling', 'type': 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