layai/syn-news-vanilla
layai/syn-news-vanilla is an 8 billion parameter language model, fine-tuned from Meta-Llama-3-8B. It was trained with a learning rate of 5e-05 over 3 epochs, achieving a loss of 1.3088 and an accuracy of 0.8162 on its evaluation set. The primary use case and specific differentiators are not detailed in the provided information.
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Overview
layai/syn-news-vanilla is an 8 billion parameter language model, fine-tuned from the Meta-Llama-3-8B architecture. The specific dataset used for fine-tuning is not detailed in the available information.
Key Capabilities
- Base Model: Built upon the robust Meta-Llama-3-8B foundation.
- Evaluation Performance: Achieved an accuracy of 0.8162 and a loss of 1.3088 on its evaluation set.
Training Details
The model was trained using the following key hyperparameters:
- Learning Rate: 5e-05
- Batch Size: 40 (train and eval)
- Epochs: 3.0
- Optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- Scheduler: Cosine learning rate scheduler
Good for
Due to limited information on the fine-tuning dataset and intended uses, specific recommendations for this model's optimal use cases are not available. Users should conduct further evaluation to determine suitability for their specific tasks.