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README.md
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| 1 |
+
---
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| 2 |
+
license: mit
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| 3 |
+
datasets:
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| 4 |
+
- GAIR/LIMO
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| 5 |
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language:
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| 6 |
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- en
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| 7 |
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base_model:
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- deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
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| 9 |
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tags:
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| 10 |
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- R1
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| 11 |
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- DeepSeek
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| 12 |
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- Distill
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| 13 |
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- Qwen
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| 14 |
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- 7B
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| 15 |
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- LIMO
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| 16 |
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---
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| 17 |
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# LIMO-R1-Distill-Qwen-7B
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| 18 |
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Using [deepseek-ai/DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B) as base model.
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| 19 |
+
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| 20 |
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Fine-tuned on [GAIR/LIMO](https://huggingface.co/GAIR/LIMO).
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| 21 |
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| 22 |
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Trained using LLaMA-Factory with the config:
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| 23 |
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```
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| 24 |
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max_seq_length = 6*1024
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| 25 |
+
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| 26 |
+
lora_rank = 32
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| 27 |
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lora_alpha = lora_rank * 2
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| 28 |
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lora_target = ["q_proj", "k_proj", "v_proj", "o_proj",
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| 29 |
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"gate_proj", "up_proj", "down_proj"]
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| 30 |
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| 31 |
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args = dict(
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| 32 |
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stage="sft",
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| 33 |
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do_train=True,
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| 34 |
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model_name_or_path="unsloth/DeepSeek-R1-Distill-Qwen-7B-bnb-4bit",
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| 35 |
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dataset="limo_restructured",
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| 36 |
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template="custom_template",
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| 37 |
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finetuning_type="lora",
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| 38 |
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lora_target=lora_target,
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| 39 |
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output_dir="qwen_distill_7b_lora",
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| 40 |
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per_device_train_batch_size=1,
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| 41 |
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gradient_accumulation_steps=3,
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| 42 |
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lr_scheduler_type="cosine",
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| 43 |
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logging_steps=1,
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| 44 |
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warmup_ratio=0.1,
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| 45 |
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save_steps=100,
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| 46 |
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learning_rate=1e-4,
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| 47 |
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num_train_epochs=1.0,
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| 48 |
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max_grad_norm=1.0,
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| 49 |
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loraplus_lr_ratio=16.0,
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| 50 |
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fp16=True,
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| 51 |
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report_to="none",
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| 52 |
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preprocessing_num_workers=16,
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| 53 |
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cutoff_len=max_seq_length,
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| 54 |
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)
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| 55 |
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```
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| 56 |
+
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| 57 |
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System used:
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| 58 |
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```
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| 59 |
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'You are a helpful assistant. Please reason step by step inside the tags <think> and </think>. Conclude with **Answer** and put your final answer within \\boxed{}.'
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| 60 |
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```
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| 61 |
+
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| 62 |
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Custom template used in training:
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| 63 |
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```
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| 64 |
+
register_template(
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| 65 |
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name="custom_template",
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| 66 |
+
format_user=StringFormatter(
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| 67 |
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slots=["<|User|>{{content}}"]
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| 68 |
+
),
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| 69 |
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format_assistant=StringFormatter(
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| 70 |
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slots=["<|Assistant|>{{content}}<|end▁of▁sentence|>"]
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| 71 |
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),
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| 72 |
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format_system=StringFormatter(
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| 73 |
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slots=["{{content}}"]
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| 74 |
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),
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| 75 |
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format_function=FunctionFormatter(
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| 76 |
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slots=[
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| 77 |
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"<|Assistant|><|tool▁calls▁begin|><|tool▁call▁begin|>{{type}}<|tool▁sep|>{{name}}\n```json\n{{arguments}}\n```<|tool▁call▁end|><|tool▁calls▁end|><|end▁of▁sentence|>"
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| 78 |
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],
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| 79 |
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tool_format="qwen"
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| 80 |
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),
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| 81 |
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format_observation=StringFormatter(
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| 82 |
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slots=[
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| 83 |
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"<|tool▁outputs▁begin|><|tool▁output_begin|>{{content}}<|tool▁output▁end|><|tool▁outputs▁end|>"
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| 84 |
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]
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| 85 |
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),
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| 86 |
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format_tools=ToolFormatter(tool_format="qwen"),
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| 87 |
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default_system="",
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| 88 |
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stop_words=["<|end▁of▁sentence|>"]
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| 89 |
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)
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| 90 |
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```
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| 91 |
+
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| 92 |
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In the dataset for variation, I randomly replaced the start of the string "Okay," with one of the following:
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| 93 |
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```
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| 94 |
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starts = [
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| 95 |
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"Alright,",
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| 96 |
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"Well,",
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| 97 |
+
"So,",
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| 98 |
+
"Hmm,",
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| 99 |
+
"Okay then,",
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| 100 |
+
"Right,",
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| 101 |
+
"Let's see,",
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| 102 |
+
"Now,",
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| 103 |
+
"Alrighty,",
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| 104 |
+
"Thinking about it,",
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| 105 |
+
"You know,",
|
| 106 |
+
"Well then,",
|
| 107 |
+
"Come to think of it,",
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| 108 |
+
"Actually,",
|
| 109 |
+
"Now that I think about it,",
|
| 110 |
+
"Good question,",
|
| 111 |
+
"Let me think,",
|
| 112 |
+
"Let's see now,",
|
| 113 |
+
"Interesting,",
|
| 114 |
+
"Now then,"
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| 115 |
+
]
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| 116 |
+
```
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