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---
license: apache-2.0
library_name: peft
tags:
- code
- instruct
- mistral
datasets:
- cognitivecomputations/dolphin-coder
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: mistral_7b_DolphinCoder
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: 59.73
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Zangs3011/mistral_7b_DolphinCoder
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: 81.64
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Zangs3011/mistral_7b_DolphinCoder
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: 59.87
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Zangs3011/mistral_7b_DolphinCoder
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: 43.95
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Zangs3011/mistral_7b_DolphinCoder
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: 74.59
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Zangs3011/mistral_7b_DolphinCoder
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: 26.23
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Zangs3011/mistral_7b_DolphinCoder
name: Open LLM Leaderboard
---
### Finetuning Overview:
**Model Used:** mistralai/Mistral-7B-v0.1
**Dataset:** cognitivecomputations/dolphin-coder
#### Dataset Insights:
[Dolphin-Coder](https://huggingface.co/datasets/cognitivecomputations/dolphin-coder) dataset – a high-quality collection of 100,000+ coding questions and responses. It's perfect for supervised fine-tuning (SFT), and teaching language models to improve on coding-based tasks.
#### Finetuning Details:
With the utilization of [MonsterAPI](https://monsterapi.ai)'s [no-code LLM finetuner](https://monsterapi.ai/finetuning), this finetuning:
- Was achieved with great cost-effectiveness.
- Completed in a total duration of 15hr 36mins for 1 epochs using an A6000 48GB GPU.
- Costed `$31.51` for the entire 1 epoch.
#### Hyperparameters & Additional Details:
- **Epochs:** 1
- **Cost Per Epoch:** $31.51
- **Model Path:** mistralai/Mistral-7B-v0.1
- **Learning Rate:** 0.0002
- **Data Split:** 100% train
- **Gradient Accumulation Steps:** 128
- **lora r:** 32
- **lora alpha:** 64
---
license: apache-2.0
# [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_Zangs3011__mistral_7b_DolphinCoder)
| Metric |Value|
|---------------------------------|----:|
|Avg. |57.67|
|AI2 Reasoning Challenge (25-Shot)|59.73|
|HellaSwag (10-Shot) |81.64|
|MMLU (5-Shot) |59.87|
|TruthfulQA (0-shot) |43.95|
|Winogrande (5-shot) |74.59|
|GSM8k (5-shot) |26.23|
|