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  • Developed by: student-abdullah
  • License: apache-2.0
  • Finetuned from model: meta-llama/Llama-3.2-1B
  • Created on: 8th October, 2024

Acknowledgement


Model Description

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: 1024
  • LoRA Alpha: 5
  • LoRA Rank (r): 1024
  • Learning rate: 5e-5
  • Gradient Accumulation Steps: 1
  • Batch Size: 8
  • Quantization: None

Model Quantitative Performace

  • Training Quantitative Loss: 0.1351 (at final 12th epoch 10820th Step)

Limitations

  • Token Limitations: With a max token limit of 1024, 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)
  • At temperature 0.7
  • Correct Responses: 87.57%
  • Incorrect Responses: 12.43%

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