File size: 4,593 Bytes
37aea0b 7d70135 37aea0b a558223 50cfcb6 a558223 7d70135 37aea0b a558223 37aea0b a558223 37aea0b 50cfcb6 a558223 08f9b72 a558223 50cfcb6 a558223 50cfcb6 a558223 50cfcb6 a558223 50cfcb6 a558223 906d8a0 50cfcb6 7d70135 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 |
---
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
---
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|
|