
# Fine-tune LLaMA 2 (7B) with LoRA on meta-math/MetaMathQA
Fine-tune for two epochs

## Result:
**Reload the saved adapter**:
Invalid output length: 3, Testing length: 1319, **Accuracy: 0.635**

## Comparison
The official report **accuracy is 0.665** by fine-tuning the whole LLaMA 2 7B model for 3 epochs.

**Note**: The LoRA adapter is being used for future research purposes.

# 🚀 Adapter Usage
```python
# Load the Pre-trained LoRA Adapter
model.load_adapter("shuyuej/metamath_lora_llama2_7b_2_epoch")
model.enable_adapters()
```

{"license": "apache-2.0", "model-index": [{"name": "MetaMath-LoRA-LLaMA-7B", "results": [{"task": {"type": "text-generation"}, "dataset": {"name": "meta-math/MetaMathQA", "type": "meta-math/MetaMathQA"}, "metrics": [{"type": "Accuracy (zero-shot)", "value": 0.635, "name": "Accuracy (zero-shot)", "verified": true}], "source": {"url": "https://paperswithcode.com/sota/arithmetic-reasoning-on-gsm8k", "name": "Arithmetic Reasoning on GSM8K"}}]}]}
license:apache-2.0 model-index region:us