初始化项目，由ModelHub XC社区提供模型
Model: kaushik-harsh-99/Math-Instruct-v1 Source: Original Platform
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---
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license: apache-2.0
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language:
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- en
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tags:
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- mathematics
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- math
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- sft
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- instruction-tuning
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- transformers
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pipeline_tag: text-generation
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pretty_name: MathInstruct v1
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library_name: transformers
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datasets:
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- nvidia/OpenMathInstruct-2
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base_model:
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- Qwen/Qwen3-0.6B
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---
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# MathInstruct v1
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MathInstruct v1 is a mathematics-focused instruction-tuned language model created by supervised fine-tuning a pretrained base model on curated mathematics training data.
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This release aims to improve mathematical instruction following, solution generation, and benchmark performance while maintaining the original capabilities of the base model.
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## Results
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Benchmark performance compared with the original base model is shown below.
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MathInstruct v1 demonstrates improvements across mathematical evaluation tasks and stronger instruction-following behavior.
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## Training
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MathInstruct v1 was trained using supervised fine-tuning (SFT) on the NVIDIA OpenMath dataset.
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The model was trained for **0.1 epoch** to adapt the base model toward stronger mathematical instruction following and solution generation while preserving its original capabilities.
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Training setup:
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* Supervised fine-tuning (SFT)
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* Dataset: NVIDIA OpenMath
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* Training duration: 0.1 epoch
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* No manual filtering or removal of noisy samples
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* Original dataset distribution preserved
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* Minimal preprocessing for training compatibility
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## Limitations
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The model may still generate incorrect reasoning or inaccurate answers. Verify outputs before using them in important scenarios.
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||||
"eos_token": "<|endoftext|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 32768,
|
||||
"pad_token": "<|PAD_TOKEN|>",
|
||||
"padding_side": "right",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user