---
language:
- en
license: mit
datasets:
- fdyrd/MATH
base_model:
- Qwen/Qwen2.5-0.5B
library_name: transformers
tags:
- text-generation-inference
metrics:
- accuracy
---

# QwenMath

A generation LLM which can solve math problems.

## Training Statistics
```yaml
training-method: lora
training-time: "5:42"
data-size: 500
epoch: 3
total_flos: "1372250GF"
train_loss: 0.6441
train_samples_per_second: 4.385
train_steps_per_second: 0.544
```

## Validation Set Performance
Dataset used: test split of [fdyrd/MATH](https://huggingface.co/datasets/fdyrd/MATH).
Metric: accuracy

<table>
        <tr>
                <th> Level </th>
                <th> Algebra </th>
                <th> Intermediate Algebra </th>
                <th> Prealgebra </th>
                <th> Precalculus </th>
                <th> Number Theory </th>
                <th> Geometry </th>
                <th> Counting & Probability </th>
                <th> Average </th>
        </tr>
        <tr>
                <td> Level 1 </td>
                <td> 0.541 : 135 </td>
                <td> 0.192 : 52 </td>
                <td> 0.477 : 86 </td>
                <td> 0.228 : 57 </td>
                <td> 0.467 : 30 </td>
                <td> 0.263 : 38 </td>
                <td> 0.359 : 39 </td>
                <td> 0.361 </td>
        </tr>
        <tr>
                <td> Level 2 </td>
                <td> 0.323 : 201 </td>
                <td> 0.109 : 128 </td>
                <td> 0.367 : 177 </td>
                <td> 0.044 : 113 </td>
                <td> 0.38 : 92 </td>
                <td> 0.134 : 82 </td>
                <td> 0.248 : 101 </td>
                <td> 0.229 </td>
        </tr>
        <tr>
                <td> Level 3 </td>
                <td> 0.291 : 261 </td>
                <td> 0.046 : 195 </td>
                <td> 0.308 : 224 </td>
                <td> 0.0 : 127 </td>
                <td> 0.262 : 122 </td>
                <td> 0.088 : 102 </td>
                <td> 0.16 : 100 </td>
                <td> 0.165 </td>
        </tr>
        <tr>
                <td> Level 4 </td>
                <td> 0.18 : 283 </td>
                <td> 0.024 : 248 </td>
                <td> 0.22 : 191 </td>
                <td> 0.009 : 114 </td>
                <td> 0.169 : 142 </td>
                <td> 0.064 : 125 </td>
                <td> 0.09 : 111 </td>
                <td> 0.108 </td>
        </tr>
        <tr>
                <td> Level 5 </td>
                <td> 0.088 : 307 </td>
                <td> 0.004 : 280 </td>
                <td> 0.104 : 193 </td>
                <td> 0.0 : 135 </td>
                <td> 0.136 : 154 </td>
                <td> 0.023 : 132 </td>
                <td> 0.065 : 123 </td>
                <td> 0.06 </td>
        </tr>
        <tr>
                <td> Average </td>
                <td> 0.285 </td>
                <td> 0.075 </td>
                <td> 0.295 </td>
                <td> 0.056 </td>
                <td> 0.283 </td>
                <td> 0.114 </td>
                <td> 0.184 </td>
                <td> 0.166 </td>
        </tr>
</table>

## Test Set Performance

```json
[
  {
    "dataset": "MATH500",
    "url": "https://huggingface.co/datasets/qq8933/MATH500",
    "accuracy": 0.286
  },
  {
    "dataset": "GSM8K",
    "url": "https://huggingface.co/datasets/openai/gsm8k",
    "accuracy": 0.382
  }
]
```