Overview

abeiler/AlphaRep is a fine-tuned language model based on meta-llama/Llama-2-7b-hf. This model leverages the Llama 2 architecture, which is a 7 billion parameter causal language model.

Training Details

The model was trained using the following hyperparameters:

• Learning Rate: 0.0001
• Optimizer: Adam with betas=(0.9, 0.999) and epsilon=1e-08
• Epochs: 1
• Batch Size: 4 (train), 8 (eval)
• Frameworks: Transformers 4.33.3, Pytorch 2.0.0, Datasets 2.12.0, Tokenizers 0.13.3

Limitations and Further Information

Currently, detailed information regarding the specific dataset used for fine-tuning, the model's intended uses, and its performance characteristics is not available. Users should exercise caution and conduct their own evaluations before deploying this model for specific applications, as its unique differentiators and optimal use cases are not yet documented.