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Llama-3_1-8B-Instruct-orca-ORPO
monsterapi/Llama-3_1-8B-Instruct-orca-ORPO
Llama-3_1-8B-Instruct-orca-ORPO is a machine learning model from monsterapi. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
Model Used: meta-llama/Meta-Llama-3.1-8B-Instruct Dataset: Intel/orcadpopairs
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At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Aug 1, 2024
- Updated
- Aug 9, 2024
- SHA
- a11ea6ec
Base models
Datasets
Model card
From the Hugging Face model README
Finetuning Overview:
Model Used: meta-llama/Meta-Llama-3.1-8B-Instruct
Dataset: Intel/orca_dpo_pairs
Dataset Insights:
The Intel Orca dataset is a specialized version of the OpenOrca dataset, which includes ~1M GPT-4 completions and ~3.2M GPT-3.5 completions. This dataset is tabularized to align with the distributions in the ORCA paper and focuses on preference optimization by clearly indicating which responses are good and which are bad. It is primarily used in natural language processing for training and evaluation.
Finetuning Details:
This finetuning run was performed using MonsterAPI's LLM finetuner with ORPO (Optimized Response Preference Optimization) for enhancing preference optimization.
- Completed in a total duration of 1 hour and 39 minutes for 1 epoch.
- Costed
$2.69for the entire process.
Hyperparameters & Additional Details:
- Epochs: 1
- Cost Per Epoch: $2.69
- Total Finetuning Cost: $2.69
- Model Path: meta-llama/Meta-Llama-3.1-8B-Instruct
- Learning Rate: 0.001
- Data Split: 90% train 10% validation
- Gradient Accumulation Steps: 16
- Library
- peft
- License
- apache-2.0
- Created
- Aug 1, 2024
- Updated
- Aug 9, 2024