This model is fine-tuned from the meta-llama/Llama-3.2-1B 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 Q&A
Max Tokens: 512
LoRA Alpha: 6
LoRA Rank (r): 128
Learning rate: 5e-5
Gradient Accumulation Steps: 2
Batch Size: 4
Quantization: 16 bits
Model Quantitative Performace
Training Quantitative Loss: 0.1407 (at final 5th epoch 5150th Step)
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.
Model Performace Evaluation:
Evaluation on 1000 Questions based on dataset (to evaluate the finetuned knowledge base)
