File size: 6,140 Bytes
a7ddde5 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 |
---
language:
- en
license: apache-2.0
tags:
- smol_llama
- llama2
datasets:
- JeanKaddour/minipile
- pszemraj/simple_wikipedia_LM
- mattymchen/refinedweb-3m
- BEE-spoke-data/knowledge-inoc-concat-v1
inference:
parameters:
max_new_tokens: 64
do_sample: true
temperature: 0.8
repetition_penalty: 1.05
no_repeat_ngram_size: 4
eta_cutoff: 0.0006
renormalize_logits: true
widget:
- text: My name is El Microondas the Wise, and
example_title: El Microondas
- text: Kennesaw State University is a public
example_title: Kennesaw State University
- text: Bungie Studios is an American video game developer. They are most famous for
developing the award winning Halo series of video games. They also made Destiny.
The studio was founded
example_title: Bungie
- text: The Mona Lisa is a world-renowned painting created by
example_title: Mona Lisa
- text: The Harry Potter series, written by J.K. Rowling, begins with the book titled
example_title: Harry Potter Series
- text: 'Question: I have cities, but no houses. I have mountains, but no trees. I
have water, but no fish. What am I?
Answer:'
example_title: Riddle
- text: The process of photosynthesis involves the conversion of
example_title: Photosynthesis
- text: Jane went to the store to buy some groceries. She picked up apples, oranges,
and a loaf of bread. When she got home, she realized she forgot
example_title: Story Continuation
- text: 'Problem 2: If a train leaves Station A at 9:00 AM and travels at 60 mph,
and another train leaves Station B at 10:00 AM and travels at 80 mph, when will
they meet if the distance between the stations is 300 miles?
To determine'
example_title: Math Problem
- text: In the context of computer programming, an algorithm is
example_title: Algorithm Definition
pipeline_tag: text-generation
model-index:
- name: smol_llama-220M-GQA
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: 24.83
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-GQA
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: 29.76
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-GQA
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: 25.85
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-GQA
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: 44.55
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-GQA
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: 50.99
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-GQA
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: 0.68
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BEE-spoke-data/smol_llama-220M-GQA
name: Open LLM Leaderboard
---
# smol_llama: 220M GQA
> model card WIP, more details to come
A small 220M param (total) decoder model. This is the first version of the model.
- 1024 hidden size, 10 layers
- GQA (32 heads, 8 key-value), context length 2048
- train-from-scratch on one GPU :)
## Links
[Here](https://huggingface.co/collections/BEE-spoke-data/finetuned-smol-220m-65998b080ae723e79c830f83) are some fine-tunes we did, but there are many more possibilities out there!
- instruct
- openhermes - [link](https://huggingface.co/BEE-spoke-data/smol_llama-220M-openhermes)
- open-instruct - [link](https://huggingface.co/BEE-spoke-data/smol_llama-220M-open_instruct)
- code
- python (pypi) - [link](https://huggingface.co/BEE-spoke-data/beecoder-220M-python)
- zephyr DPO tune
- SFT - [link](https://huggingface.co/BEE-spoke-data/zephyr-220m-sft-full)
- full DPO - [link](https://huggingface.co/BEE-spoke-data/zephyr-220m-dpo-full)
---
# [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_BEE-spoke-data__smol_llama-220M-GQA)
| Metric |Value|
|---------------------------------|----:|
|Avg. |29.44|
|AI2 Reasoning Challenge (25-Shot)|24.83|
|HellaSwag (10-Shot) |29.76|
|MMLU (5-Shot) |25.85|
|TruthfulQA (0-shot) |44.55|
|Winogrande (5-shot) |50.99|
|GSM8k (5-shot) | 0.68|
|