peft pytorch mistral Mistral text-generation en license:llama2 model-index region:us
---
language:
- en
library_name: peft
pipeline_tag: text-generation
tags:
- Mistral
license: llama2
model-index:
- name: SpeechlessCoder
  results:
  - task:
      type: text-generation
    dataset:
      type: openai_humaneval
      name: HumanEval
    metrics:
    - name: pass@1
      type: pass@1
      value: 0.0
      verified: false
---

# Mistral-7B-OpenOrca-lora-merged

**This is a test.**

This is a regenerated model that combines the base model Mistral-7B-v0.1 with the LoRA model [Mistral-7B-OpenOrca-lora](https://huggingface.co/uukuguy/Mistral-7B-OpenOrca-lora).

This LoRA model is extracted from the efficient parameter fine-tuned model ([Mistral-7B-OpenOra](https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca)), and now it needs to be verified whether this LoRA model can achieve comparable performance with the original model.

The final goal is to create a toolkit that can simultaneously load multiple LoRA modules, and automatically switch to the appropriate combination of LoRA modules based on user queries to generate the best answer.

The source code is [here](https://github.com/uukuguy/multi_loras)


## Mistral-7B-OpenOrca

- Extract lora model [Mistral-7B-OpenOrca-lora](https://huggingface.co/uukuguy/Mistral-7B-OpenOrca-lora) from [Mistral-7B-OpenOrca](https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca);

- Merge the base model [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) with lora model to [Mistral-7B-OpenOrca-lora-merged](https://huggingface.co/uukuguy/Mistral-7B-OpenOrca-lora-merged)

- LLM Evaluation ...

### Local Test

| | ARC_acc_norm (25-shot) | HellaSwag_acc_norm (10-shot) | MMLU_acc (5-shot) | TruthfulQA_mc2 (0-shot) | GSM8K_acc (8-shot) | Open LLM Score |
| ------ | ------ | ------ | ------ | ------ | ------ | ------ |
| Mistral-7B-OpenOrca | **71** | 83 | 61.42 | 45 | 40 | 65.11 |
| **r=256** | 68 | **84** | **64.28** | 46.953 | **41** |  **65.81** |
| r=64 | 67 | 84 | 64.26 | **47.32** | **41** | 65.65 |
| *r=16* | *65* | *83* | *62.84* | *46.95* | *38* | *64.45* |

### Open LLM Leaderboard
| | ARC_acc_norm (25-shot) | HellaSwag_acc_norm (10-shot) | MMLU_acc (5-shot) | TruthfulQA_mc2 (0-shot) | Open LLM Score |
| ------ | ------ | ------ | ------ | ------ | ------ |
| Mistral-7B-SlimOrca | 62.54 | 83.86 | **62.77** | **54.23** |  **65.85** |
| Mistral-7B-OpenOrca | **64.08** | **83.99** | 62.24 | 53.05 |  65.84 |


## lm-evaluation-harness


[Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)

| Metric | Mistral-7B-OpenOrca | Mistral-7B-OpenOrca-lora| Mistral-7B-OpenOrca-lora-merged |
| --- | --- |--- | --- |
| ARC | 64.08 | | |
| HellaSwag | 83.99 | | |
| MMLU | 62.24 | | |
| TruthfulQA | 53.05 | | |
| Average | 65.84 | | |

## HumanEval

| Metric | Mistral-7B-OpenOrca | Mistral-7B-OpenOrca-lora| Mistral-7B-OpenOrca-lora-merged |
| --- | --- | --- | --- |
| humaneval-python | 35.976 | | |


## Training procedure

The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: True
- bnb_4bit_compute_dtype: bfloat16
### Framework versions


- PEFT 0.5.0
