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---
license: apache-2.0
library_name: peft
tags:
- code
- instruct
- mistral
datasets:
- HuggingFaceH4/no_robots
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: mistral_7b_norobots
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: 58.96
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_norobots
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: 80.57
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_norobots
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: 57.66
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_norobots
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: 41.91
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_norobots
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: 75.61
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_norobots
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: 38.36
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_norobots
name: Open LLM Leaderboard
---
### Finetuning Overview:
**Model Used:** mistralai/Mistral-7B-v0.1
**Dataset:** HuggingFaceH4/no_robots
#### Dataset Insights:
[No Robots](https://huggingface.co/datasets/HuggingFaceH4/no_robots) is a high-quality dataset of 10,000 instructions and demonstrations created by skilled human annotators. This data can be used for supervised fine-tuning (SFT) to make language models follow instructions better.
#### 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 1h 15m 3s for 2 epochs using an A6000 48GB GPU.
- Costed `$2.525` for the entire 2 epochs.
#### Hyperparameters & Additional Details:
- **Epochs:** 2
- **Cost Per Epoch:** $1.26
- **Total Finetuning Cost:** $2.525
- **Model Path:** mistralai/Mistral-7B-v0.1
- **Learning Rate:** 0.0002
- **Data Split:** 100% train
- **Gradient Accumulation Steps:** 64
- **lora r:** 64
- **lora alpha:** 16
#### Prompt Structure
```
<|system|> </s> <|user|> [USER PROMPT] </s> <|assistant|> [ASSISTANT ANSWER] </s>
```
#### Train loss :
### Benchmarking results :
---
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_norobots)
| Metric |Value|
|---------------------------------|----:|
|Avg. |58.85|
|AI2 Reasoning Challenge (25-Shot)|58.96|
|HellaSwag (10-Shot) |80.57|
|MMLU (5-Shot) |57.66|
|TruthfulQA (0-shot) |41.91|
|Winogrande (5-shot) |75.61|
|GSM8k (5-shot) |38.36|
|