layai/syn-dataaug-youtube-vanilla
The layai/syn-dataaug-youtube-vanilla model 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 3.3634 and an accuracy of 0.5275 on its evaluation set. This model is a foundational Llama-3 variant, suitable for general language tasks where a pre-trained base model is required.
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Model Overview
The layai/syn-dataaug-youtube-vanilla model is an 8 billion parameter language model, derived from the meta-llama/Meta-Llama-3-8B architecture. It has been fine-tuned, though the specific dataset used for this fine-tuning is not detailed in the available information.
Training Details
During its training, the model utilized the following key hyperparameters:
- Base Model:
meta-llama/Meta-Llama-3-8B - Learning Rate: 5e-05
- Batch Size: 40 (train and eval), with a total effective batch size of 160 due to gradient accumulation steps.
- Optimizer: Adam with default betas and epsilon.
- Epochs: 3.0
Performance Metrics
On its evaluation set, the model achieved:
- Loss: 3.3634
- Accuracy: 0.5275
Intended Uses
Given its foundational nature as a fine-tuned Llama-3 variant, this model is suitable for general language understanding and generation tasks. Specific use cases or limitations are not detailed in the provided documentation, suggesting it can serve as a base for further specialization or for tasks where a robust, general-purpose language model is needed.