---
base_model: meta-llama/Llama-3.2-1B
language:
- en
- hi
datasets:
- student-abdullah/BigPharma_Generic_Q-A_Format_Augemented_Hinglish_Dataset
---
# LoRA Adapter Layers!
# Uploaded model

- **Developed by:** student-abdullah
- **Finetuned from model:** meta-llama/Llama-3.2-1B
- **Created on:** 29th September, 2024
- **Full model:** student-abdullah/Llama3.2_Medicine-Hinglish-Dataset_Fine-Tuned_29-09

---
# Acknowledgement
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

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# Model Description
This LoRA adapter layer model is fine-tuned from the meta-llama/Llama-3.2-1B base model to specialisation 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: 32
- LoRA Rank (r): 128
- Learning rate: 1.5e-4
- Gradient Accumulation Steps: 4
- Batch Size: 8

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# Model Quantitative Performace
- Training Quantitative Loss: 0.1207 (at final 800th epoch)

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# Limitations
- This is not a fully compiled model, rather just LoRA layers