PEFT
code
instruct
mistral
leaderboard-pr-bot's picture
Adding Evaluation Results
0476236 verified
|
raw
history blame
4.75 kB
---
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_HalfEpoch_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: 61.77
name: normalized accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_HalfEpoch_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: 82.26
name: normalized accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_HalfEpoch_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: 61.75
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_HalfEpoch_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: 45.46
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_HalfEpoch_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: 75.53
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_HalfEpoch_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: 29.64
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_HalfEpoch_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 7hrs 36min for 0.5 epochs using an A6000 48GB GPU.
- Costed `$15.2` for the entire run
#### Hyperparameters & Additional Details:
- **Epochs:** 0.5
- **Cost for full run:** $15.2
- **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
![image/png](https://cdn-uploads.huggingface.co/production/uploads/6313732454e6e5d9f0f797cd/0O1VKp3SJNfrhTd5earci.png)
---
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_qblocks__mistral_7b_HalfEpoch_DolphinCoder)
| Metric |Value|
|---------------------------------|----:|
|Avg. |59.40|
|AI2 Reasoning Challenge (25-Shot)|61.77|
|HellaSwag (10-Shot) |82.26|
|MMLU (5-Shot) |61.75|
|TruthfulQA (0-shot) |45.46|
|Winogrande (5-shot) |75.53|
|GSM8k (5-shot) |29.64|