Model Overview
This model is a fine-tuned variant of Llama-3.2-1B, leveraging ORPO (Optimized Regularization for Prompt Optimization) for enhanced performance. It has been fine-tuned using the mlabonne/orpo-dpo-mix-40k dataset as part of the Finetuning Open Source LLMs Course - Week 2 Project.
Intended Use
This model is optimized for general-purpose language tasks, including text parsing, understanding contextual prompts, and enhanced interpretability in natural language processing applications.
Evaluation Results
The model was evaluated on the following benchmarks, with the following performance metrics:
| Tasks | Version | Filter | n-shot | Metric | Value | Stderr | ||
|---|---|---|---|---|---|---|---|---|
| eq_bench | 2.1 | none | 0 | eqbench | ↑ | 1.5355 | ± | 0.9184 |
| none | 0 | percent_parseable | ↑ | 16.9591 | ± | 2.8782 | ||
| hellaswag | 1 | none | 0 | acc | ↑ | 0.4812 | ± | 0.0050 |
| none | 0 | acc_norm | ↑ | 0.6467 | ± | 0.0049 | ||
| ifeval | 4 | none | 0 | inst_level_loose_acc | ↑ | 0.3984 | ± | N/A |
| none | 0 | inst_level_strict_acc | ↑ | 0.2974 | ± | N/A | ||
| none | 0 | prompt_level_loose_acc | ↑ | 0.2755 | ± | 0.0193 | ||
| none | 0 | prompt_level_strict_acc | ↑ | 0.1848 | ± | 0.0168 | ||
| tinyMMLU | 0 | none | 0 | acc_norm | ↑ | 0.3995 | ± | N/A |
Key Features
- Model Size: 1 Billion parameters
- Fine-tuning Method: ORPO
- Dataset: mlabonne/orpo-dpo-mix-40k
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Model tree for JPBianchi/llm_uplimit_P2_llama3
Base model
meta-llama/Llama-3.2-1BDataset used to train JPBianchi/llm_uplimit_P2_llama3
Evaluation results
- EQ-Bench (0-Shot) on mlabonne/orpo-dpo-mix-40kself-reported1.536