sunzx0810/llama2-7b-science
The sunzx0810/llama2-7b-science model is a 7 billion parameter Llama 2-based language model fine-tuned on a specialized dataset. This model is designed for scientific applications, leveraging its Llama 2 architecture to process and generate content relevant to scientific domains. It was trained with a learning rate of 1e-05 over 3 epochs, making it suitable for tasks requiring domain-specific knowledge in science.
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Overview
The sunzx0810/llama2-7b-science model is a 7 billion parameter language model based on the Llama 2 architecture. It has been fine-tuned on a custom dataset, indicating a specialization in a particular domain, likely scientific given its name. The base model is llama2/Llama-2-7b-hf.
Training Details
The model underwent training with specific hyperparameters:
- Learning Rate: 1e-05
- Batch Size: 6 (train), 8 (eval)
- Epochs: 3.0
- Optimizer: Adam with betas=(0.9, 0.999) and epsilon=1e-08
- Devices: Trained across 4 multi-GPU devices.
Key Capabilities
- Domain Specialization: Fine-tuned on a customized dataset, suggesting enhanced performance for tasks within its specialized domain (implied to be science).
- Llama 2 Foundation: Benefits from the robust capabilities and architecture of the Llama 2 7B model.
Intended Use Cases
While specific intended uses and limitations are not detailed in the provided README, its fine-tuning on a custom dataset implies suitability for applications requiring domain-specific understanding and generation, particularly in scientific contexts. Users should consider its 7B parameter size for tasks requiring a balance between performance and computational resources.