metadata

base_model: meta-llama/Llama-3.2-1B
datasets:
  - student-abdullah/Experimental
language:
  - en
license: apache-2.0
tags:
  - text-generation-inference
  - transformers
  - torch
  - trl
  - unsloth
  - llama
  - gguf

Uploaded model

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%