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README.md
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---
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base_model:
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language:
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- en
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license: apache-2.0
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- llama
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- gguf
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---
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- **Developed by:** student-abdullah
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- **License:** apache-2.0
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- **Finetuned from model
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base_model: meta-llama/Llama-3.2-1B
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datasets:
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- student-abdullah/Experimental
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language:
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- en
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license: apache-2.0
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tags:
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- text-generation-inference
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- transformers
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- torch
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- trl
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- unsloth
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- llama
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- gguf
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---
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# Uploaded model
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- **Developed by:** student-abdullah
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- **License:** apache-2.0
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- **Finetuned from model:** meta-llama/Llama-3.2-1B
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- **Created on:** 3st October, 2024
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---
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# Acknowledgement
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<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>
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---
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# Model Description
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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:
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- Fine Tuning Template: Llama Q&A
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- Max Tokens: 512
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- LoRA Alpha: 6
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- LoRA Rank (r): 128
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- Learning rate: 5e-5
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- Gradient Accumulation Steps: 2
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- Batch Size: 4
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- Quantization: 16 bits
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---
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# Model Quantitative Performace
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- Training Quantitative Loss: 0.1407 (at final 5th epoch 5150th Step)
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---
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# Limitations
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- Token Limitations: With a max token limit of 512, the model might not handle very long queries or contexts effectively.
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- 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.
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- Potential Biases: As with any model fine-tuned on specific data, there may be biases based on the dataset used for training.
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---
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# Model Performace Evaluation:
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- Evaluation on 1000 Questions based on dataset (to evaluate the finetuned knowledge base)
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- At temperature 0.3
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- Correct Responses: %
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- Incorrect Responses: %
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<p align="center">
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<img src="" width="20%" style="display:inline-block;"/>
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<img src="" width="35%" style="display:inline-block;"/>
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<img src="" width="35%" style="display:inline-block;"/>
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</p>
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