RichardErkhov/MSey_-_Ca-lower_labels_r100_O2_f100_LT-gguf

Quantization made by Richard Erkhov.

Github

Discord

Request more models

Ca-lowerlabelsr100O2f100_LT - GGUF

• —Model creator: https://huggingface.co/MSey/
• —Original model: https://huggingface.co/MSey/Ca-lowerlabelsr100O2f100_LT/

Original model description: --- library_name: transformers tags:

• —trl
• —sft base_model:
• —TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T ---

Model Card for Model ID

TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T trained for one epoch on Ca-lowerlabels dataset with r100O2_F100 WCE Trainer.

"evalAVGf1": 0.9223289834840258, "evalaccuracy": 0.9272914758360438, "evaldiagnosis.avgwordsperentity": 2.2245762711864407, "evaldiagnosis.entitycount": 2360, "evaldiagnosis.f1": 0.8788986878898688, "evaldiagnosis.precision": 0.8925294888597641, "evaldiagnosis.recall": 0.8656779661016949, "evaldiagnosis.wordcount": 5250, "evaldiagnostic.avgwordsperentity": 1.8057921635434413, "evaldiagnostic.entitycount": 1761, "evaldiagnostic.f1": 0.9564464955292761, "evaldiagnostic.precision": 0.9718640093786636, "evaldiagnostic.recall": 0.9415105053946621, "evaldiagnostic.wordcount": 3180, "evaldrug.avgwordsperentity": 1.0905096660808435, "evaldrug.entitycount": 1138, "evaldrug.f1": 0.957187922487607, "evaldrug.precision": 0.9824236817761333, "evaldrug.recall": 0.9332161687170475, "evaldrug.wordcount": 1241, "evalf1": 0.6559352257940142, "evalloss": 0.005444246344268322, "evalmedicalfinding.avgwordsperentity": 4.152033985581874, "evalmedicalfinding.entitycount": 7768, "evalmedicalfinding.f1": 0.9184775620419185, "evalmedicalfinding.precision": 0.917415874646802, "evalmedicalfinding.recall": 0.9195417095777549, "evalmedicalfinding.wordcount": 32253, "evalmodelpreparationtime": 0.0, "evalprecision": 0.5121161950632149, "evalrecall": 0.9120761292052004, "evalruntime": 311.6758, "evalsamplespersecond": 26.252, "evalstepspersecond": 6.565, "evaltherapy.avgwordsperentity": 3.6986807387862797, "evaltherapy.entitycount": 1895, "evaltherapy.f1": 0.9006342494714588, "evaltherapy.precision": 0.9020645844362096, "evaltherapy.recall": 0.8992084432717679, "evaltherapy.word_count": 7009,

"testAVGf1": 0.8991844061835648, "testaccuracy": 0.9393252816821795, "testdiagnosis.avgwordsperentity": 2.540414878397711, "testdiagnosis.entitycount": 2796, "testdiagnosis.f1": 0.7905454545454544, "testdiagnosis.precision": 0.8039940828402367, "testdiagnosis.recall": 0.7775393419170243, "testdiagnosis.wordcount": 7103, "testdiagnostic.avgwordsperentity": 1.9772727272727273, "testdiagnostic.entitycount": 2156, "testdiagnostic.f1": 0.9380572501173158, "testdiagnostic.precision": 0.9491927825261158, "testdiagnostic.recall": 0.9271799628942486, "testdiagnostic.wordcount": 4263, "testdrug.avgwordsperentity": 1.033793103448276, "testdrug.entitycount": 1450, "testdrug.f1": 0.9711267605633803, "testdrug.precision": 0.9920863309352518, "testdrug.recall": 0.9510344827586207, "testdrug.wordcount": 1499, "testf1": 0.6601992430504198, "testloss": 0.005932590924203396, "testmedicalfinding.avgwordsperentity": 4.681758451797873, "testmedicalfinding.entitycount": 8371, "testmedicalfinding.f1": 0.900312076782665, "testmedicalfinding.precision": 0.8877148165350673, "testmedicalfinding.recall": 0.9132720105124835, "testmedicalfinding.wordcount": 39191, "testmodelpreparationtime": 0.0, "testprecision": 0.5235630994273097, "testrecall": 0.8933364728043325, "testruntime": 357.9554, "testsamplespersecond": 26.509, "teststepspersecond": 6.629, "testtherapy.avgwordsperentity": 3.9787810383747177, "testtherapy.entitycount": 2215, "testtherapy.f1": 0.8958804889090086, "testtherapy.precision": 0.8983204720835225, "testtherapy.recall": 0.8934537246049662, "testtherapy.word_count": 8813