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@@ -28,6 +28,33 @@ The instructions and training datasets used are:
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  - `pubmedqa_testset.csv` for inference.
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  The datasets are available under `med-rcq/med-rcq-dataset`: https://huggingface.co/datasets/med-rcq/med-rcq-dataset/tree/main
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Environment Setup
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  - OS: Ubuntu 22.04.3
 
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  - `pubmedqa_testset.csv` for inference.
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  The datasets are available under `med-rcq/med-rcq-dataset`: https://huggingface.co/datasets/med-rcq/med-rcq-dataset/tree/main
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+ ## Training and Inference Parameters
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+
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+ | Training Parameter | MedConclusion |
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+ |----------------------------------|---------------|
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+ | Learning rate | 2e-04 |
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+ | Seed | 42 |
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+ | Scheduler | cosine |
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+ | Warmup Ratio | 0.05 |
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+ | Optimizer | AdamW |
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+ | Gradient Accumulation steps | 4 |
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+ | Train batch size per device | 8 |
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+ | Effective Batch size | 192 |
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+ | Evaluation batch size | 4 |
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+ | Cut-off Length | 1024 |
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+ | Number of GPU | 6 |
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+ | LoRA Rank | 32 |
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+ | LoRA Alpha | 32 |
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+ | LoRA Dropout | 0.05 |
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+ | LoRA Target | All |
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+ | Number of epochs | 1 |
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+ | Max Grad Norm | 1.0 |
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+ | **Training Time** | **11.5 hours** |
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+
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+ | Inference Parameter | MedConclusion |
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+ |----------------------|---------------|
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+ | Temperature | 0.01 |
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+ | Max Token | 250 |
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  ## Environment Setup
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  - OS: Ubuntu 22.04.3