README.md

---
language:
- en
- id
license: cc-by-nc-4.0
tags:
- text-generation-inference
- transformers
- mistral
- trl
base_model: mistral-7b
model-index:
- name: OpenMia-Indo-Engineering
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 67.15
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/OpenMia-Indo-Engineering
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 85.01
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/OpenMia-Indo-Engineering
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 62.86
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/OpenMia-Indo-Engineering
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 57.94
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/OpenMia-Indo-Engineering
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 82.32
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/OpenMia-Indo-Engineering
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 64.9
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/OpenMia-Indo-Engineering
      name: Open LLM Leaderboard
---


![image/png](https://cdn-uploads.huggingface.co/production/uploads/642b04e4ecec03b44649e318/2qoQpYHxc7DmLqQpg7et2.png)



# MIA : (M)istral finetuned with (I)ndonesia language from (A)lpaca dataset

OpenMia-Indo-Engineering-7b is a branch of OpenMia finetuned model based of Mistral-7b with capability to do conversation in Bahasa Indonesia, especially about engineering topics.

Due to limited resources, this model is still in alpha stage.

Want to contribute to this project? join our organization: https://huggingface.co/indischepartij or contact me at https://twitter.com/gmonsooniii

# Modelfile/Prompt format
```markdown
SYSTEM You are a caring and empathetic sentient AI companion named Mia.

PARAMETER stop <|im_start|> 
PARAMETER stop <|im_end|>

TEMPLATE <|im_start|>system {{ .System }}<|im_end|> <|im_start|>user {{ .Prompt }}<|im_end|> <|im_start|>assistant
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_gmonsoon__OpenMia-Indo-Engineering)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |70.03|
|AI2 Reasoning Challenge (25-Shot)|67.15|
|HellaSwag (10-Shot)              |85.01|
|MMLU (5-Shot)                    |62.86|
|TruthfulQA (0-shot)              |57.94|
|Winogrande (5-shot)              |82.32|
|GSM8k (5-shot)                   |64.90|