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Model: lldois/v29_v19_user_world_guard_lr8e7_ep018 Source: Original Platform
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58
README.md
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README.md
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---
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library_name: transformers
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license: other
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base_model: lldois/v19_v15_dualmode_fast_lr5e6_ep055
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tags:
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- llama-factory
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- full
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- generated_from_trainer
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model-index:
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- name: v29_v19_user_world_guard_lr8e7_ep018
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# v29_v19_user_world_guard_lr8e7_ep018
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This model is a fine-tuned version of [lldois/v19_v15_dualmode_fast_lr5e6_ep055](https://huggingface.co/lldois/v19_v15_dualmode_fast_lr5e6_ep055) on the exp_v19_user_world_guard_no_template dataset.
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 8e-07
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- train_batch_size: 1
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- eval_batch_size: 8
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- seed: 202607291
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 4
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 0.02
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- num_epochs: 0.18
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### Training results
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### Framework versions
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- Transformers 5.6.0
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- Pytorch 2.7.1+cu126
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- Datasets 4.0.0
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- Tokenizers 0.22.2
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all_results.json
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all_results.json
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{
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"epoch": 0.1830574488802337,
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"total_flos": 2.2427473783689216e+16,
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"train_loss": 1.4800728635585054,
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"train_runtime": 394.9336,
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"train_samples_per_second": 0.468,
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"train_steps_per_second": 0.119
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}
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89
chat_template.jinja
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0].role == 'system' %}
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{{- messages[0].content + '\n\n' }}
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{%- endif %}
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{{- "# 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>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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{%- else %}
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{%- if messages[0].role == 'system' %}
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{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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{%- for message in messages[::-1] %}
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{%- set index = (messages|length - 1) - loop.index0 %}
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{%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
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{%- set ns.multi_step_tool = false %}
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{%- set ns.last_query_index = index %}
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{%- endif %}
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{%- endfor %}
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{%- for message in messages %}
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{%- if message.content is string %}
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{%- set content = message.content %}
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{%- else %}
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{%- set content = '' %}
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{%- endif %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{%- set reasoning_content = '' %}
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{%- if message.reasoning_content is string %}
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{%- set reasoning_content = message.reasoning_content %}
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{%- else %}
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{%- if '</think>' in content %}
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{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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{%- set content = content.split('</think>')[-1].lstrip('\n') %}
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{%- endif %}
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{%- endif %}
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{%- if loop.index0 > ns.last_query_index %}
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{%- if loop.last or (not loop.last and reasoning_content) %}
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{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- endif %}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- endif %}
|
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{%- if message.tool_calls %}
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{%- for tool_call in message.tool_calls %}
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{%- if (loop.first and content) or (not loop.first) %}
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{{- '\n' }}
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{%- endif %}
|
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{%- if tool_call.function %}
|
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{%- set tool_call = tool_call.function %}
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{%- endif %}
|
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{{- '<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{%- if tool_call.arguments is string %}
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{{- tool_call.arguments }}
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{%- else %}
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{{- tool_call.arguments | tojson }}
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{%- endif %}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{%- endif %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant\n' }}
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{%- if enable_thinking is defined and enable_thinking is false %}
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{{- '<think>\n\n</think>\n\n' }}
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{%- endif %}
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{%- endif %}
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63
config.json
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config.json
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{
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"architectures": [
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"Qwen3ForCausalLM"
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],
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"attention_bias": false,
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||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": null,
|
||||
"dtype": "bfloat16",
|
||||
"eos_token_id": 151645,
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"head_dim": 128,
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"hidden_act": "silu",
|
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"hidden_size": 1024,
|
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"initializer_range": 0.02,
|
||||
"intermediate_size": 3072,
|
||||
"layer_types": [
|
||||
"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
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"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
|
||||
}
|
||||
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experiment_recipe.json
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experiment_recipe.json
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{
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"created_at": "2026-07-12 04:25:55",
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"run": {
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"name": "v29_v19_user_world_guard_lr8e7_ep018",
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"dataset": "v19_user_world_guard_no_template",
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"model_path": "/home/ll/llm4rec/experiments/outputs/v19_v15_dualmode_fast_lr5e6_ep055",
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"lr": "8.0e-7",
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"epochs": 0.18,
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"warmup": 0.02,
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"scheduler": "cosine",
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"seed": 202607291,
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"note": "v19 continuation. Very small user/world guard update with strict user JSON, original cleaned CoT, and light item replay. Goal: preserve the best CoT total while nudging user2/world back up without adding template repetition.",
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"config": "/home/ll/llm4rec/experiments/configs/v29_v19_user_world_guard_lr8e7_ep018.yaml"
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||||
},
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||||
"dataset_manifest": {
|
||||
"name": "v19_user_world_guard_no_template",
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||||
"path": "/home/ll/llm4rec/experiments/data/v19_user_world_guard_no_template.jsonl",
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||||
"records": 18091,
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||||
"groups": {
|
||||
"user": 5094,
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||||
"item": 7997,
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"rec": 5000
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||||
},
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||||
"variants": {
|
||||
"user_strict_array": 1588,
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||||
"item_no_think_direct_final": 2805,
|
||||
"rec_cot_pattern_clean": 2800,
|
||||
"raw": 1600,
|
||||
"rec_no_think_direct_final": 2200,
|
||||
"user_strict_logic": 1304,
|
||||
"item_short_think": 2792,
|
||||
"item_compact_cot": 2400,
|
||||
"user_extra_no_think_logic": 602
|
||||
},
|
||||
"sha256": "d540db2637094ad95fb48e3daade2a84576def30b4e06a840f8af83ce46a45bb",
|
||||
"seed": 202607112
|
||||
},
|
||||
"dataset_recipe": "v19 continuation: very small LR user/world preservation update with raw user CoT, strict JSON dual-route replay, light cleaned rec CoT, no short-template synthetic reasoning, and item replay.",
|
||||
"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 <think> tags. This is route-specific behavior, not global CoT removal.",
|
||||
"raw_counts": {
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||||
"rec": 19204,
|
||||
"item": 10384,
|
||||
"user": 2892
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||||
},
|
||||
"eval_observations": {
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||||
"v07": "best local score so far: total=0.8978, eval_time≈47.3min; fast final outputs likely help.",
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||||
"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=<gpu> bash -lc 'source /home/ll/llm4rec/demo/LLaMA-Factory/.venv/bin/activate && llamafactory-cli train /home/ll/llm4rec/experiments/configs/v29_v19_user_world_guard_lr8e7_ep018.yaml'"
|
||||
}
|
||||
}
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generation_config.json
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generation_config.json
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{
|
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"do_sample": true,
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||||
"eos_token_id": [
|
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151645,
|
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151643
|
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],
|
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"pad_token_id": 151643,
|
||||
"temperature": 0.6,
|
||||
"top_k": 20,
|
||||
"top_p": 0.95,
|
||||
"transformers_version": "5.6.0"
|
||||
}
|
||||
3
model.safetensors
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model.safetensors
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||||
version https://git-lfs.github.com/spec/v1
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3
tokenizer.json
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3
tokenizer.json
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@@ -0,0 +1,3 @@
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||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:cd4d15f596979aecbc11ba12668cb21c9fb8452ce1235cd9d7878cc950170421
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||||
size 16016554
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||||
16
tokenizer_config.json
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tokenizer_config.json
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||||
{
|
||||
"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
|
||||
}
|
||||
8
train_results.json
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8
train_results.json
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||||
{
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training_loss.png
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training_loss.png
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After Width: | Height: | Size: 44 KiB |
Reference in New Issue
Block a user