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---
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|
|