GGUF
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Overview

This model, elucidator8918/clinical-ehr-prototype-0.3_GGUF is a Q5_K_M type GGUF and is tailored for clinical documentation, based on the Mistral-7B-Instruct-v0.3-sharded architecture fine-tuned on the Asclepius-Synthetic-Clinical-Notes dataset.

Key Information

  • Model Name: Mistral-7B-Instruct-v0.3-sharded
  • Fine-tuned Model Name: elucidator8918/clinical-ehr-prototype-0.3_GGUF
  • Dataset: starmpcc/Asclepius-Synthetic-Clinical-Notes
  • Language: English (en)

Model Details

  • LoRA Parameters (QLoRA):

    • LoRA attention dimension: 64
    • Alpha parameter for LoRA scaling: 16
    • Dropout probability for LoRA layers: 0.1
  • bitsandbytes Parameters:

    • Activate 4-bit precision base model loading
    • Compute dtype for 4-bit base models: float16
    • Quantization type: nf4
    • Activate nested quantization for 4-bit base models: No
  • TrainingArguments Parameters:

    • Number of training epochs: 1
    • Batch size per GPU for training: 4
    • Batch size per GPU for evaluation: 4
    • Gradient accumulation steps: 1
    • Enable gradient checkpointing: Yes
    • Maximum gradient norm: 0.3
    • Initial learning rate: 2e-4
    • Weight decay: 0.001
    • Optimizer: paged_adamw_32bit
    • Learning rate scheduler type: cosine
    • Warm-up ratio: 0.03
    • Group sequences into batches with the same length: Yes

License

This model is released under the MIT License.

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GGUF
Model size
7.25B params
Architecture
llama

5-bit

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Dataset used to train elucidator8918/clinical-ehr-prototype-0.3_GGUF