| | --- |
| | library_name: transformers |
| | tags: |
| | - trl |
| | - sft |
| | language: |
| | - de |
| | base_model: |
| | - TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T |
| | pipeline_tag: text-generation |
| | --- |
| | |
| | # Model Card for Model ID |
| |
|
| | We fine-tuned our base model for 21 epochs on the Ca dataset, epoch 1 showed the best macro average f1 score on the evaluation dataset. |
| |
|
| | ## Context format |
| | "### Context\n\nText to analyse.\n\n###Answer" |
| |
|
| |
|
| | ## Metric |
| |
|
| | eval_AVGf1 0.9102075019834961 |
| | |
| | eval_DIAGNOSIS.f1 0.8808602150537634 |
| |
|
| | eval_DIAGNOSIS.precision 0.8943231441048035 |
| | |
| | eval_DIAGNOSIS.recall 0.8677966101694915 |
| |
|
| | eval_DIAGNOSTIC.f1 0.9472166137871358 |
| | |
| | eval_DIAGNOSTIC.precision 0.9624853458382181 |
| |
|
| | eval_DIAGNOSTIC.recall 0.9324247586598523 |
| | |
| | eval_DRUG.f1 0.9440145653163405 |
| |
|
| | eval_DRUG.precision 0.9792256846081209 |
| | |
| | eval_DRUG.recall 0.9112478031634447 |
| |
|
| | eval_MEDICAL_FINDING.f1 0.9092427259297321 |
| |
|
| | eval_MEDICAL_FINDING.precision 0.9073195744135367 |
| |
|
| | eval_MEDICAL_FINDING.recall 0.9111740473738414 |
| |
|
| | eval_THERAPY.f1 0.8697033898305084 |
| | |
| | eval_THERAPY.precision 0.8729399255715046 |
| |
|
| | eval_THERAPY.recall 0.8664907651715039 |
| | |
| | eval_accuracy 0.9618960382191458 |
| |
|
| | eval_f1 0.7632318301785055 |
| | |
| | eval_loss 0.006697072647511959 |
| |
|
| | eval_model_preparation_time 0 |
| | |
| | eval_precision 0.6619246861924686 |
| |
|
| | eval_recall 0.9011526605012733 |
| | |
| | eval_runtime 341.5967 |
| |
|
| | eval_samples_per_second 23.952 |
| | |
| | eval_steps_per_second 5.99 |
| |
|
| | test_AVGf1 0.8676664044743045 |
| | |
| | test_DIAGNOSIS.f1 0.7754658946987515 |
| |
|
| | test_DIAGNOSIS.precision 0.7846942511900403 |
| | |
| | test_DIAGNOSIS.recall 0.7664520743919886 |
| |
|
| | test_DIAGNOSTIC.f1 0.9211950129381322 |
| | |
| | test_DIAGNOSTIC.precision 0.9346062052505967 |
| |
|
| | test_DIAGNOSTIC.recall 0.9081632653061225 |
| | |
| | test_DRUG.f1 0.9448028673835126 |
| |
|
| | test_DRUG.precision 0.9835820895522388 |
| | |
| | test_DRUG.recall 0.9089655172413793 |
| |
|
| | test_MEDICAL_FINDING.f1 0.879590997238056 |
| |
|
| | test_MEDICAL_FINDING.precision 0.8656025907934305 |
| |
|
| | test_MEDICAL_FINDING.recall 0.8940389439732409 |
| |
|
| | test_THERAPY.f1 0.8172772501130711 |
| | |
| | test_THERAPY.precision 0.8187584956955143 |
| |
|
| | test_THERAPY.recall 0.8158013544018059 |
| | |
| | test_accuracy 0.9665184459433998 |
| |
|
| | test_f1 0.7391588362393848 |
| | |
| | test_loss 0.009836438111960888 |
| |
|
| | test_model_preparation_time 0 |
| | |
| | test_precision 0.6447795213465416 |
| |
|
| | test_recall 0.865905344949376 |
| | |
| | test_runtime 394.9961 |
| |
|
| | test_samples_per_second 24.023 |
| | |
| | test_steps_per_second 6.008 |
