---
language: en
license: apache-2.0
tags:
- qwen2
- reasoning
- fine-tuned
- english
- instruction-tuned
- chat
- gguf
metrics:
- accuracy
- f1
base_model:
- Qwen/Qwen2.5-3B-Instruct
library_name: transformers
pipeline_tag: text-generation
datasets:
- openai/gsm8k
---

# Model Card for CALISTA-INDUSTRY/qwen_2_3B_reasoning_en_ft_v1

## Model Details

- **Model Name**: qwen_2_3B_reasoning_en_ft_v1
- **Developed by**: Mohammad Yani & Rizky Sulaeman, Politeknik Negeri Indramayu
- **Model Type**: Transformer-based language model
- **Base Model**: [Qwen/Qwen2-3B](https://huggingface.co/Qwen/Qwen2-3B)
- **Parameter Count**: 3.09 billion
- **Language**: English
- **License**: Apache 2.0
- **Fine-tuned from**: Qwen2-3B

## Model Description

This model is a fine-tuned version of Qwen2-3B, optimized for enhanced reasoning capabilities in English. It has been trained on a curated dataset to improve performance on tasks requiring logical inference, comprehension, and instruction following.

## Intended Uses & Limitations

### Direct Use

- **Applications**:
  - Logical reasoning tasks
  - Instruction-based question answering
  - Conversational agents requiring enhanced reasoning

### Downstream Use

- **Potential Applications**:
  - Integration into AI systems requiring reasoning capabilities
  - Further fine-tuning for domain-specific tasks

### Out-of-Scope Use

- **Not Recommended For**:
  - Tasks requiring real-time decision-making in critical systems
  - Applications involving sensitive or personal data without proper safeguards

## Bias, Risks, and Limitations

While efforts have been made to reduce biases during fine-tuning, the model may still exhibit biases present in the training data. Users should be cautious and evaluate the model's outputs, especially in sensitive applications.

## How to Use

```python
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="CALISTA-INDUSTRY/qwen_2_3B_reasoning_en_ft_v1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)
```