README.md

---
license: apache-2.0
library_name: peft
tags:
- code
- instruct
- gpt2
datasets:
- cognitivecomputations/dolphin-coder
base_model: gpt2
model-index:
- name: gpt2_137m_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: 21.84
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/gpt2_137m_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: 31.35
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/gpt2_137m_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: 25.4
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/gpt2_137m_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: 41.58
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/gpt2_137m_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: 52.01
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/gpt2_137m_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: 1.06
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/gpt2_137m_DolphinCoder
      name: Open LLM Leaderboard
---

### Finetuning Overview:

**Model Used:** gpt2

**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 58mins 48s for 1 epochs using an A6000 48GB GPU.
- Costed `$1.96` for the entire 1 epoch.

#### Hyperparameters & Additional Details:

- **Epochs:** 1
- **Total Finetuning Cost:** $1.96
- **Model Path:** gpt2
- **Learning Rate:** 0.0002
- **Data Split:** 100% train 
- **Gradient Accumulation Steps:** 128
- **lora r:** 32
- **lora alpha:** 64

![Train Loss](https://cdn-uploads.huggingface.co/production/uploads/63ba46aa0a9866b28cb19a14/3XcaHhWcu0hTqq_zf0WSH.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__gpt2_137m_DolphinCoder)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |28.87|
|AI2 Reasoning Challenge (25-Shot)|21.84|
|HellaSwag (10-Shot)              |31.35|
|MMLU (5-Shot)                    |25.40|
|TruthfulQA (0-shot)              |41.58|
|Winogrande (5-shot)              |52.01|
|GSM8k (5-shot)                   | 1.06|