---
title: corrector_text
canonical_url: "https://www.modelscope.cn/models/bmz123/corrector_text"
md_url: "https://www.modelscope.cn/models/bmz123/corrector_text.md"
repository: bmz123/corrector_text
last_updated: 2026-07-23
license: other
pipeline_tag: text-error-correction
tasks:
  - text-error-correction
model_type:
  - qwen2
architectures:
  - Qwen2ForCausalLM
base_model:
  - Qwen/Qwen2.5-7B-Instruct
base_model_relation: finetune
parameters: 7.6B
tensor_type:
  - BF16
library_name:
  - safetensors
  - pytorch
frameworks:
  - Pytorch
downloads: 10
stars: 0
tags:
  - llama-factory
  - full
  - generated_from_trainer
---

# corrector_text

> corrector_text - bmz123 在 ModelScope 开源的模型。qwen2.5-7b-reasoning-corrector-text

bmz123/corrector_text 是 ModelScope 魔搭社区上的 7.6B 参数text-error-correction模型，采用 other 许可，基于 Qwen/Qwen2.5-7B-Instruct 构建。

- **Repository**: bmz123/corrector_text
- **License**: other
- **Tasks**: text-error-correction
- **Parameters**: 7.6B
- **Base model**: Qwen/Qwen2.5-7B-Instruct
- **Tags**: llama-factory, full, generated_from_trainer
- **Downloads**: 10
- **Stars**: 0
- **Last updated**: 2026-07-23

Source: https://www.modelscope.cn/models/bmz123/corrector_text

---

<!-- 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. -->

# qwen2.5-7b-reasoning-corrector-text

This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the train dataset. (text only ablation)

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Use adamw_torch_fused 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: 100
- num_epochs: 6.0

### Training results



### Framework versions

- Transformers 4.57.1
- Pytorch 2.9.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.1