README.md

---
license: apache-2.0
model-index:
- name: Mistral-T5-7B-v1
  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: 68.6
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ignos/Mistral-T5-7B-v1
      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: 86.3
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ignos/Mistral-T5-7B-v1
      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: 64.62
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ignos/Mistral-T5-7B-v1
      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: 61.86
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ignos/Mistral-T5-7B-v1
      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: 80.27
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ignos/Mistral-T5-7B-v1
      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: 73.16
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ignos/Mistral-T5-7B-v1
      name: Open LLM Leaderboard
---

# Model Card for Model ID

  This model is a finetuning of [Toten5/Marcoroni-neural-chat-7B-v2](https://huggingface.co/Toten5/Marcoroni-neural-chat-7B-v2)
    
## Model Details

### Model Description

- **Developed by:** Ignos
- **Model type:** Mistral
- **License:** Apache-2.0

## Uses

  Model created to improve instructional behavior.

## Bias, Risks, and Limitations

  The same bias, risks and limitations from base models.

## Training Details

### Training Data

- [tatsu-lab/alpaca](https://huggingface.co/datasets/tatsu-lab/alpaca)

### Training Procedure

- Training with QLoRA approach and merging with base model.

### Results

- Huggingface evaluation pending

#### Summary

## Technical Specifications

### Model Architecture and Objective

- Models based on Mistral Architecture

### Compute Infrastructure

- Training on RunPod

#### Hardware

- 3 x RTX 4090
- 48 vCPU 377 GB RAM

#### Software

- Axolotl 0.3.0

### Framework versions

- PEFT 0.6.0

# [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_ignos__Mistral-T5-7B-v1)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |72.47|
|AI2 Reasoning Challenge (25-Shot)|68.60|
|HellaSwag (10-Shot)              |86.30|
|MMLU (5-Shot)                    |64.62|
|TruthfulQA (0-shot)              |61.86|
|Winogrande (5-shot)              |80.27|
|GSM8k (5-shot)                   |73.16|