Tiny Fine Tunes🤏
Collection
A collection of SLM (Small Language Model) fine tunes.
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4 items
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Updated
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 and Huggingface's TRL library.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| 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 |
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Model tree for NotASI/FineTome-Llama3.2-3B-1002
Base model
meta-llama/Llama-3.2-3B-Instruct
Quantized
unsloth/Llama-3.2-3B-Instruct-bnb-4bit
Dataset used to train NotASI/FineTome-Llama3.2-3B-1002
Collection including NotASI/FineTome-Llama3.2-3B-1002
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard54.740
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard19.520
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard5.290
- acc_norm on GPQA (0-shot)Open LLM Leaderboard0.110
- acc_norm on MuSR (0-shot)Open LLM Leaderboard3.960
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard15.960