lemon07r's picture
Adding Evaluation Results (#1)
a7e7ee1 verified
|
raw
history blame
4.7 kB
---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- unsloth/gemma-2-9b-it
- jsgreenawalt/gemma-2-9B-it-advanced-v2.1
- lemon07r/Gemma-2-Ataraxy-9B
- ifable/gemma-2-Ifable-9B
model-index:
- name: Gemma-2-Ataraxy-v2f-9B
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 37.91
name: strict accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2f-9B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 31.42
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2f-9B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 0.0
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2f-9B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 11.86
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2f-9B
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: 3.59
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2f-9B
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: 27.81
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-v2f-9B
name: Open LLM Leaderboard
---
# Gemma-2-Ataraxy-v2f-9B
Another test model you should probably ignore.
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the della merge method using [unsloth/gemma-2-9b-it](https://huggingface.co/unsloth/gemma-2-9b-it) as a base.
### Models Merged
The following models were included in the merge:
* [jsgreenawalt/gemma-2-9B-it-advanced-v2.1](https://huggingface.co/jsgreenawalt/gemma-2-9B-it-advanced-v2.1)
* [lemon07r/Gemma-2-Ataraxy-9B](https://huggingface.co/lemon07r/Gemma-2-Ataraxy-9B)
* [ifable/gemma-2-Ifable-9B](https://huggingface.co/ifable/gemma-2-Ifable-9B)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
base_model: unsloth/gemma-2-9b-it
dtype: bfloat16
merge_method: della
parameters:
epsilon: 0.1
int8_mask: 1.0
lambda: 1.0
normalize: 1.0
slices:
- sources:
- layer_range: [0, 42]
model: unsloth/gemma-2-9b-it
- layer_range: [0, 42]
model: jsgreenawalt/gemma-2-9B-it-advanced-v2.1
parameters:
density: 0.55
weight: 0.6
- layer_range: [0, 42]
model: lemon07r/Gemma-2-Ataraxy-9B
parameters:
density: 0.35
weight: 0.6
- layer_range: [0, 42]
model: ifable/gemma-2-Ifable-9B
parameters:
density: 0.25
weight: 0.4
```
# [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/details_lemon07r__Gemma-2-Ataraxy-v2f-9B)
| Metric |Value|
|-------------------|----:|
|Avg. |18.77|
|IFEval (0-Shot) |37.91|
|BBH (3-Shot) |31.42|
|MATH Lvl 5 (4-Shot)| 0.00|
|GPQA (0-shot) |11.86|
|MuSR (0-shot) | 3.59|
|MMLU-PRO (5-shot) |27.81|