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BenchHub-Cat-7b-backup/README.md

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----
-license: apache-2.0
-language:
-  - en
-tags:
-  - LLM
-  - classification
-  - instruction-tuned
-  - multi-label
-  - qwen
-datasets:
-  - custom
-pipeline_tag: text-classification
----
-
-
-# BenchHub-Cat-7b
-
-<div style="text-align: center;">
-  <img src="https://cdn-uploads.huggingface.co/production/uploads/6576ace7769f3ee9bd7b1b88/P_Csm4Gc5eOLYcq5I__0R.png" width="200"/>
-</div>
-
-
-**BenchHub-Cat-7b** is a category classification model based on **Qwen2.5-7B**, fine-tuned to assign natural language queries to structured category triplets: `(subject, skill, target)`.
-
-## 🔧 Model Details
-
-- **Base Model**: [Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)
-- **Task**: Structured multi-label classification (triple: subject, skill, target)
-- **Prompting Style**: Instruction-style with expected format output
-- **Training Framework**: [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) + DeepSpeed ZeRO-3
-
-## 🧪 Training Configuration
-
-| Hyperparameter          | Value                |
-|--------------------------|----------------------|
-| Sequence Length          | 8192                 |
-| Learning Rate            | 2 × 10⁻⁵             |
-| Batch Size (Effective)   | 256                  |
-| Epochs                   | 3                    |
-| Scheduler                | Cosine Decay         |
-| Warmup Ratio             | 0.05                 |
-| Optimizer                | Method from [19]     |
-| Trainer                  | DeepSpeed ZeRO-3     |
-| Hardware                 | 4× A6000 48GB GPUs   |
-| Training Time            | ~5 hours per run     |
-
-## 🧠 Intended Use
-
-**Input**: Natural language question or instruction  
-**Output**: Triplet `(subject, skill, target)`, such as:
-
-```yaml
-{ "subject_type": "history",  
-"task_type": "reasoning",  
-"target_type": "korea"}
-````
-
-
-## ✨ Prompt Example
-
-```
-### Instruction:
-Classify the following query into subject, skill, and target.
-
-### Query:
-How did Confucianism shape education in East Asia?
-
-### Output:
-{ "subject_type": "history",  
-"task_type": "reasoning",  
-"target_type": "korea"}
-```
-
-## 📜 License
-
-Apache 2.0
-