XXsongLALA/Llama-3.1-8B-instruct-RAG-RL
XXsongLALA/Llama-3.1-8B-instruct-RAG-RL is an 8 billion parameter instruction-tuned model based on the Llama 3.1 architecture, developed by XXsongLALA. This model was trained from scratch and features a 32768 token context length. It is designed for general language understanding and generation tasks, with specific optimization for instruction following.
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Model Overview
XXsongLALA/Llama-3.1-8B-instruct-RAG-RL is an 8 billion parameter instruction-tuned model built upon the Llama 3.1 architecture. Developed by XXsongLALA, this model was trained from scratch, though specific details regarding its training dataset are not provided. It supports a substantial context length of 32768 tokens, enabling it to process and generate longer sequences of text.
Key Training Details
The model's training procedure involved specific hyperparameters:
- Learning Rate: 5e-05
- Batch Size: 8 (for both training and evaluation)
- Optimizer: AdamW with default betas and epsilon
- LR Scheduler: Linear
- Epochs: 3.0
Intended Uses
While specific intended uses are not detailed in the provided information, as an instruction-tuned model, it is generally suitable for a wide range of natural language processing tasks that require following explicit instructions. Its large context window suggests potential for applications involving extensive document analysis, summarization, or conversational AI where long-term memory is beneficial.