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  • Developed by: student-abdullah
  • License: apache-2.0
  • Finetuned from model: meta-llama/Llama-3.2-1B
  • Created on: 3st 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: 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)
  • At temperature 0.3
  • Correct Responses: 76%
  • Incorrect Responses: 24%

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