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