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base_model: meta-llama/Llama-3.2-1B |
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datasets: |
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- student-abdullah/BigPharma_Generic_Q-A_Format_Augemented_Hinglish_Dataset |
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language: |
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- en |
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- hi |
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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:** 29th September, 2024 |
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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"/>](https://github.com/unslothai/unsloth) |
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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: 32 |
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- LoRA Rank (r): 128 |
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- Learning rate: 1.5e-4 |
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- Gradient Accumulation Steps: 4 |
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- Batch Size: 8 |
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# Model Quantitative Performace |
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- Training Quantitative Loss: 0.1207 (at final 800th epoch) |
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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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