---
language:
- en
license: llama3.2
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- llama-3
- trl
- sft
base_model: unsloth/Llama-3.2-3B-Instruct-bnb-4bit
datasets:
- mlabonne/FineTome-100k
model-index:
- name: FineTome-Llama3.2-3B-1002
  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: 54.74
      name: strict accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=NotASI/FineTome-Llama3.2-3B-1002
      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: 19.52
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=NotASI/FineTome-Llama3.2-3B-1002
      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: 5.29
      name: exact match
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=NotASI/FineTome-Llama3.2-3B-1002
      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: 0.11
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=NotASI/FineTome-Llama3.2-3B-1002
      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: 3.96
      name: acc_norm
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=NotASI/FineTome-Llama3.2-3B-1002
      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: 15.96
      name: accuracy
    source:
      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=NotASI/FineTome-Llama3.2-3B-1002
      name: Open LLM Leaderboard
---

# IMPORTANT

In case you got the following error:
```
exception: data did not match any variant of untagged enum modelwrapper at line 1251003 column 3
```
Please upgrade your **transformer** package, that is, use the following code:
```
pip install --upgrade "transformers>=4.45"
```

# Uploaded  model

- **Developed by:** NotASI
- **License:** apache-2.0
- **Finetuned from model :** unsloth/Llama-3.2-3B-Instruct-bnb-4bit

# Details

This model was trained on **mlabonne/FineTome-100k** for *2* epochs with **rslora** + **qlora**, and achieve the final training loss: *0.596400*.

This model follows the same chat template as the base model one.

This llama 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_NotASI__FineTome-Llama3.2-3B-1002)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |16.60|
|IFEval (0-Shot)    |54.74|
|BBH (3-Shot)       |19.52|
|MATH Lvl 5 (4-Shot)| 5.29|
|GPQA (0-shot)      | 0.11|
|MuSR (0-shot)      | 3.96|
|MMLU-PRO (5-shot)  |15.96|