README.md

---
language:
- en
license: apache-2.0
datasets:
- Open-Orca/SlimOrca
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: mistral-11b-slimorca
  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: 64.25
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chargoddard/mistral-11b-slimorca
      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: 83.81
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chargoddard/mistral-11b-slimorca
      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: 63.66
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chargoddard/mistral-11b-slimorca
      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: 54.66
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chargoddard/mistral-11b-slimorca
      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: 77.98
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chargoddard/mistral-11b-slimorca
      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: 52.39
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=chargoddard/mistral-11b-slimorca
      name: Open LLM Leaderboard
---

Full weight fine tuned on two epochs of [SlimOrca](https://huggingface.co/datasets/Open-Orca/SlimOrca). Uses Mistral Instruct's prompt format.

The base model for this came from a variation on Undi's [Mistral 11B recipe](https://huggingface.co/Undi95/Mistral-11B-v0.1). The `o_proj` and `down_proj` tensors were set to zero in the added layers, making the output exactly identical to Mistral 7B before training.

~Benchmarks look good locally but still evaluating actual usefulness.~
Update: this turned out great! 10/10 would recommend as a training approach.


### Reproducing

This [mergekit](https://github.com/cg123/mergekit) config was used to produce the base model:
```yml
slices:
  - sources:
      - model: mistralai/Mistral-7B-v0.1
        layer_range: [0, 24]
  - sources: # add middle layers with residuals scaled to zero
      - model: mistralai/Mistral-7B-v0.1
        layer_range: [8, 24]
        parameters:
          scale:
            - filter: o_proj
              value: 0.0
            - filter: down_proj
              value: 0.0
            - value: 1.0
  - sources:
      - model: mistralai/Mistral-7B-v0.1
        layer_range: [24, 32]
merge_method: passthrough
dtype: bfloat16
```

The axolotl config for fine tuning is available [here](https://huggingface.co/chargoddard/mistral-11b-slimorca/blob/main/axolotl_config.yaml).

# [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_chargoddard__mistral-11b-slimorca)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |66.12|
|AI2 Reasoning Challenge (25-Shot)|64.25|
|HellaSwag (10-Shot)              |83.81|
|MMLU (5-Shot)                    |63.66|
|TruthfulQA (0-shot)              |54.66|
|Winogrande (5-shot)              |77.98|
|GSM8k (5-shot)                   |52.39|