File size: 4,239 Bytes
d1decb5 f39b904 d1decb5 3c83c14 d1decb5 f39b904 d1decb5 3c83c14 |
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 |
---
library_name: transformers
tags:
- merge
- llama-3.1
- roleplay
- function calling
base_model:
- unsloth/Meta-Llama-3.1-8B-Instruct
- yuriachermann/Not-so-bright-AGI-Llama3.1-8B-UC200k-v2
datasets:
- HuggingFaceH4/ultrachat_200k
base_model_relation: merge
model-index:
- name: KRONOS-8B-V1-P1
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: wis-k/instruction-following-eval
split: train
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 78.5
name: averaged accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P1
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: SaylorTwift/bbh
split: test
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 29.97
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P1
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: lighteval/MATH-Hard
split: test
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 18.96
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P1
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
split: train
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 6.04
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P1
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 8.48
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P1
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 30.67
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FKRONOS-8B-V1-P1
name: Open LLM Leaderboard
---
# KRONOS 8B V1 P1
This is a merge of Meta Llama 3.1 Instruct and the "Not so Bright" LORA, created using [llm-tools](https://github.com/oobabooga/llm-tools).
The primary purpose of this model is to be merged into other models in the same family using the TIES merge method.
Creating quants for this is entirely unnecessary.
## Merge Details
### Configuration
The following Bash command was used to produce this model:
```bash
python /llm-tools/merge-lora.py -m unsloth/Meta-Llama-3.1-8B-Instruct -l yuriachermann/Not-so-bright-AGI-Llama3.1-8B-UC200k-v2
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/T145__KRONOS-8B-V1-P1-details)!
Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=T145%2FKRONOS-8B-V1-P1&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!
| Metric |Value (%)|
|-------------------|--------:|
|**Average** | 28.77|
|IFEval (0-Shot) | 78.50|
|BBH (3-Shot) | 29.97|
|MATH Lvl 5 (4-Shot)| 18.96|
|GPQA (0-shot) | 6.04|
|MuSR (0-shot) | 8.48|
|MMLU-PRO (5-shot) | 30.67|
|