Model: Adilbai/medical-qa-t5-lora
Author: Adilbai
Pipeline: question-answering
Library: peft
Tags: peft, tensorboard, safetensors, t5, text2text-generation, medical, healthcare, clinical, biomedical, question-answering, lora, transformer, huggingface, low-resource, fine-tuned, adapter, alpaca-style, prompt-based-learning, hf-trainer, multilingual, attention, medical-ai, evidence-based, smart-health, base_model:google-t5/t5-base, base_model:adapter:google-t5/t5-base, license:apache-2.0, model-index, region:us
Base models (adapter): id: google-t5/t5-base
Card metadata: library_name: peft
license: apache-2.0
base_model: google-t5/t5-base
tags: t5, text2text-generation, medical, healthcare, clinical, biomedical, question-answering, lora, peft, transformer, huggingface, low-resource, fine-tuned, adapter, alpaca-style, prompt-based-learning, hf-trainer, multilingual, attention, medical-ai, evidence-based, smart-health
model-index: name: medical-qa-t5-lora
results: task: type: text2text-generation
name: Medical Question Answering
dataset: name: Custom Medical QA Dataset
type: medical-qa
metrics: name: Exact Match
type: exact_match
value: 0.41
verified: no, name: Token F1
type: f1
value: 0.66
verified: no, name: Medical Keyword Coverage
type: custom
value: 0.84
verified: no
Likes: 0 | All-time downloads: 945
Created: 2025-06-27 15:34:10