elucidator8918/

clinical-ehr-prototype-0.2_GGUF

Overview

Key Information

• Model Name: Mistral-7B-Instruct-v0.3-sharded
• Fine-tuned Model Name: elucidator8918/clinical-ehr-prototype-0.2_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