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Adding Evaluation Results (#1)
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---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- Qwen/Qwen2.5-14B
- Qwen/Qwen2.5-14B-Instruct
model-index:
- name: qwen-carpmuscle-r-v0.3
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: 44.55
name: strict accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=TheTsar1209/qwen-carpmuscle-r-v0.3
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: 46.38
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=TheTsar1209/qwen-carpmuscle-r-v0.3
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: 27.19
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=TheTsar1209/qwen-carpmuscle-r-v0.3
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: 13.42
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=TheTsar1209/qwen-carpmuscle-r-v0.3
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: 12.0
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=TheTsar1209/qwen-carpmuscle-r-v0.3
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: 45.59
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=TheTsar1209/qwen-carpmuscle-r-v0.3
name: Open LLM Leaderboard
---
A Fishy Model
qwen-carpmuscle-r-v0.3 was made using Rombodawg's Shared Continuous Finetuning method.
qwen-carpmuscle-v0.3 was made using Unsloth's continuous pretraining on the ChatML format with 24k context on (unsloth/Qwen2.5-14B-bnb-4bit)[https://huggingface.co/unsloth/Qwen2.5-14B-bnb-4bit].
Then qwen-carpmuscle-v0.3 was merged with [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct) and [Qwen/Qwen2.5-14B](https://huggingface.co/Qwen/Qwen2.5-14B) using [TIES](https://arxiv.org/abs/2306.01708) to create this model.
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
### Configuration
The following YAML configuration was used to produce this model:
```yaml
models:
- model: qwen-carpmuscle-v0.3
parameters:
weight: 1
density: 1
- model: Qwen/Qwen2.5-14B-Instruct
parameters:
weight: 1
density: 1
merge_method: ties
base_model: Qwen/Qwen2.5-14B
parameters:
weight: 1
density: 1
normalize: true
int8_mask: true
tokenizer_source: qwen-carpmuscle-v0.3
dtype: bfloat16
```
- **Developed by:** TheTsar1209
- **License:** apache-2.0
- **Finetuned from model :** unsloth/Qwen2.5-14B-bnb-4bit
This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
# [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_TheTsar1209__qwen-carpmuscle-r-v0.3)
| Metric |Value|
|-------------------|----:|
|Avg. |31.52|
|IFEval (0-Shot) |44.55|
|BBH (3-Shot) |46.38|
|MATH Lvl 5 (4-Shot)|27.19|
|GPQA (0-shot) |13.42|
|MuSR (0-shot) |12.00|
|MMLU-PRO (5-shot) |45.59|