README.md

---
license: llama3.2
library_name: transformers
tags:
- mergekit
- merge
base_model:
- NotASI/FineTome-Llama3.2-1B-0929
- unsloth/Llama-3.2-1B-Instruct
model-index:
- name: FineTome-v1.5-Llama3.2-1B-1007
  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: 39.24
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=NotASI/FineTome-v1.5-Llama3.2-1B-1007
      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: 5.8
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=NotASI/FineTome-v1.5-Llama3.2-1B-1007
      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: 1.36
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=NotASI/FineTome-v1.5-Llama3.2-1B-1007
      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: 0.0
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=NotASI/FineTome-v1.5-Llama3.2-1B-1007
      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: 2.5
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=NotASI/FineTome-v1.5-Llama3.2-1B-1007
      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: 4.74
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=NotASI/FineTome-v1.5-Llama3.2-1B-1007
      name: Open LLM Leaderboard
---
# merge

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 [TIES](https://arxiv.org/abs/2306.01708) merge method using [unsloth/Llama-3.2-1B-Instruct](https://huggingface.co/unsloth/Llama-3.2-1B-Instruct) as a base.

### Models Merged

The following models were included in the merge:
* [NotASI/FineTome-Llama3.2-1B-0929](https://huggingface.co/NotASI/FineTome-Llama3.2-1B-0929)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: NotASI/FineTome-Llama3.2-1B-0929
    parameters:
      weight: 1
  - model: unsloth/Llama-3.2-1B-Instruct
    parameters:
      weight: 1
merge_method: ties
base_model: unsloth/Llama-3.2-1B-Instruct
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16
```
# [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_NotASI__FineTome-v1.5-Llama3.2-1B-1007)

|      Metric       |Value|
|-------------------|----:|
|Avg.               | 8.94|
|IFEval (0-Shot)    |39.24|
|BBH (3-Shot)       | 5.80|
|MATH Lvl 5 (4-Shot)| 1.36|
|GPQA (0-shot)      | 0.00|
|MuSR (0-shot)      | 2.50|
|MMLU-PRO (5-shot)  | 4.74|