flytech/Ruckus-13b-X
Ruckus-13b-X is a 13 billion parameter language model developed by flytech, fine-tuned from Meta's Llama-2-13b-hf architecture. This model was trained with a learning rate of 0.0002 over 6 epochs, utilizing an Adam optimizer. While specific differentiators and intended uses are not detailed, its Llama-2 base suggests general language understanding and generation capabilities.
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Ruckus-13b-X: A Fine-Tuned Llama-2 Model
Ruckus-13b-X is a 13 billion parameter language model developed by flytech, built upon the robust meta-llama/Llama-2-13b-hf architecture. This model underwent a fine-tuning process, though the specific dataset used for this fine-tuning is not publicly detailed.
Training Details
The model was trained using the following key hyperparameters:
- Learning Rate: 0.0002
- Batch Size: 16 (for both training and evaluation)
- Optimizer: Adam with betas=(0.9, 0.999) and epsilon=1e-08
- LR Scheduler Type: Constant
- Epochs: 6
This training was conducted using Transformers 4.33.2, Pytorch 2.0.1+cu118, Datasets 2.14.5, and Tokenizers 0.13.3.
Potential Use Cases
Given its Llama-2-13b foundation, Ruckus-13b-X is likely suitable for a range of natural language processing tasks, including:
- Text generation
- Summarization
- Question answering
- Conversational AI
Further information regarding its specific optimizations, intended uses, and performance benchmarks would provide clearer guidance on its unique strengths and ideal applications.