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Model: lldois/v52_public091_full_lr2e5_ep1
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---
library_name: transformers
license: other
base_model: OpenOneRec/OneReason-0.8B-pretrain-competition
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: v52_public091_full_lr2e5_ep1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# v52_public091_full_lr2e5_ep1
This model is a fine-tuned version of [OpenOneRec/OneReason-0.8B-pretrain-competition](https://huggingface.co/OpenOneRec/OneReason-0.8B-pretrain-competition) on the exp_v49_public_091_exact 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 202607202
- 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: 0.03
- num_epochs: 1.0
### Training results
### Framework versions
- Transformers 5.6.0
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2

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"train_runtime": 2594.717,
"train_samples_per_second": 0.503,
"train_steps_per_second": 0.126
}

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{%- 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 <tools></tools> XML tags:\n<tools>" }}
{%- for tool in tools %}
{{- "\n" }}
{{- tool | tojson }}
{%- endfor %}
{{- "\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" }}
{%- 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('<tool_response>') and message.content.endswith('</tool_response>')) %}
{%- 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 '</think>' in content %}
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
{%- set content = content.split('</think>')[-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<think>\n' + reasoning_content.strip('\n') + '\n</think>\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 %}
{{- '<tool_call>\n{"name": "' }}
{{- tool_call.name }}
{{- '", "arguments": ' }}
{%- if tool_call.arguments is string %}
{{- tool_call.arguments }}
{%- else %}
{{- tool_call.arguments | tojson }}
{%- endif %}
{{- '}\n</tool_call>' }}
{%- endfor %}
{%- endif %}
{{- '<|im_end|>\n' }}
{%- elif message.role == "tool" %}
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
{{- '<|im_start|>user' }}
{%- endif %}
{{- '\n<tool_response>\n' }}
{{- content }}
{{- '\n</tool_response>' }}
{%- 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 %}
{{- '<think>\n\n</think>\n\n' }}
{%- endif %}
{%- endif %}

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"rope_type": "default"
},
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"transformers_version": "5.6.0",
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{
"created_at": "2026-07-16 23:52:50",
"name": "v52_public091_full_lr2e5_ep1",
"base": "OpenOneRec/OneReason-0.8B-pretrain-competition",
"dataset": "v49_public_091_exact",
"dataset_manifest": {
"path": "/home/ll/llm4rec/experiments/data/v49_public_091_exact.jsonl",
"records": 32705,
"groups": {
"rec": 18651,
"item": 9684,
"user": 2792,
"world": 1578
},
"routes": {
"no_think": 20934,
"think": 11771
},
"thought_modes": {
"empty": 20934,
"filled": 11771
},
"sha256": "cdedea13c560d3453697f4a3c9b96a2303bd708c84833034fa953d16482b9925",
"source_path": "/home/ll/llm4rec/data/external/kuaishou-llmrec-sft-baseline-0.91/train.jsonl",
"source_url": "https://huggingface.co/datasets/Frinkleko/kuaishou-llmrec-sft-baseline-0.91/resolve/main/train.jsonl?download=true",
"source_sha256": "4d6b29d76974c9a1517c1b583858e744cae019cb26e1e2d90066e237ebbcf5f8",
"source_license": "Apache-2.0",
"transform": "Lossless field mapping from system/prompt/response to instruction/input/output; original seed-42 order retained."
},
"learning_rate": "2.0e-5",
"epochs": 1.0,
"method": "full",
"weight_decay": 0.0,
"validation_size": 0.0,
"lora": {
"rank": null,
"alpha": null,
"dropout": null,
"target": null
},
"stages": null,
"note": "Full-SFT counterpart using v7's successful 2e-5 scale, now on balanced CoT/direct clean data instead of final-only data.",
"evaluation": null,
"cot_policy": "Preserve meaningful CoT for /think and pure final outputs for /no_think.",
"checkpoint_policy": "save_strategy=no; only the final model is retained.",
"script": "/home/ll/llm4rec/experiments/run_experiments.py",
"script_sha256": "bc57a4d1337c7182996ece63ddc844185043b68ae2a2dbe793e3969bbccc2e2d",
"data_builder": "/home/ll/llm4rec/experiments/source_data.py",
"data_builder_sha256": "a1216b14c8c516f9fde2fcaab9d70ec5b8a200033fbd1ee330c6b461213587ad",
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"data_cleaner_sha256": null,
"configs": [
"/home/ll/llm4rec/experiments/configs/v52_public091_full_lr2e5_ep1.yaml"
],
"reproduce": "/home/ll/llm4rec/demo/LLaMA-Factory/.venv/bin/python /home/ll/llm4rec/experiments/run_experiments.py --single v52_public091_full_lr2e5_ep1 --gpu <gpu>",
"training_result": {
"name": "v52_public091_full_lr2e5_ep1",
"gpu": 1,
"started_at": "2026-07-17 01:41:03",
"status": "ok",
"wall_seconds": 2611.22,
"finished_at": "2026-07-17 02:24:34",
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"total_flos": 1.563295846805975e+17,
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"train_runtime": 2594.717,
"train_samples_per_second": 0.503,
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"global_step": 326,
"first_logged_loss": 2.659077453613281,
"last_logged_loss": 1.512490463256836,
"min_logged_loss": 1.5008227348327636,
"tail_loss_mean": 1.5448276201883953,
"logged_loss_change": -1.1465869903564452,
"batch": "v49-v53"
}
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