Finetuned from model: meta-llama/Meta-Llama-3.1-8B
Created on: 25th September, 2024
Acknowledgement
Model Description
This model is fine-tuned from the meta-llama/Meta-Llama-3.1-8B base model to enhance its capabilities in generating relevant and accurate responses related to generic medications under the PMBJP scheme. The fine-tuning process included the following hyperparameters:
Fine Tuning Template: Llama 3.1 Q&A
Max Tokens: 512
LoRA Alpha: 10
LoRA Rank (r): 128
Learning rate: 2e-4
Gradient Accumulation Steps: 32
Batch Size: 4
Qunatization: 16 bits
Model Quantitative Performace
Training Quantitative Loss: 0.1676 (at final 160th epoch)
Limitations
Token Limitations: With a max token limit of 512, the model might not handle very long queries or contexts effectively.
Training Data Limitations: The model’s performance is contingent on the quality and coverage of the fine-tuning dataset, which may affect its generalizability to different contexts or medications not covered in the dataset.
Potential Biases: As with any model fine-tuned on specific data, there may be biases based on the dataset used for training.
