|
--- |
|
language: ger |
|
license: apache-2.0 |
|
widget: |
|
- text: '###Context |
|
|
|
Der Patient hat Brustkrebs. |
|
|
|
|
|
###Answer' |
|
example_title: Patient mit Brustkreb |
|
pipeline_tag: text-generation |
|
--- |
|
tiny Llama trained on BRO dataset with NER tags, Labels and Tokens. |
|
|
|
WCETrainer r100_O10_f100 , run lemon-fog-11 checkpoint-1623. |
|
|
|
- EVAL |
|
|
|
AVGf1 = 93%, overall_f1 = 82% |
|
|
|
- TEST |
|
|
|
'DIAG': {'precision': 0.710079275198188, 'recall': 0.7674418604651163, 'f1': 0.7376470588235293, 'number': 817}, |
|
|
|
'MED': {'precision': 0.9379084967320261, 'recall': 0.959866220735786, 'f1': 0.9487603305785124, 'number': 299}, |
|
|
|
'TREAT': {'precision': 0.8542914171656687, 'recall': 0.856, 'f1': 0.8551448551448552, 'number': 500}, |
|
|
|
'overall_precision': 0.7672955974842768, 'overall_recall': 0.8304455445544554, 'overall_f1': 0.7976225854383358, 'overall_accuracy': 0.9280119624038735} |
|
|
|
average_f1 = 0.8471840815156323 |
|
|
|
- Prompt Format (see example): |
|
|
|
### ### Context\n{Nachricht}\n\n### Answer |
|
|
|
|
|
def context_text(text): |
|
return f"### Context\n{text}\n\n### Answer" |
