multilabel_paragraph

This model is a fine-tuned version of answerdotai/ModernBERT-large on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.2041
• Classification Report Lin: {'~LIN': {'precision': 0.9908008658008658, 'recall': 0.9978201634877384, 'f1-score': 0.9942981265272876, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 17.0}, 'accuracy': 0.9886609071274298, 'macro avg': {'precision': 0.4954004329004329, 'recall': 0.4989100817438692, 'f1-score': 0.4971490632636438, 'support': 1852.0}, 'weighted avg': {'precision': 0.9817060414387628, 'recall': 0.9886609071274298, 'f1-score': 0.9851711998798988, 'support': 1852.0}}
• Hamming Lin: 0.0113
• Classification Report Si: {'~SI': {'precision': 0.9830878341516639, 'recall': 0.9933847850055126, 'f1-score': 0.9882094872497944, 'support': 1814.0}, 'SI': {'precision': 0.3684210526315789, 'recall': 0.18421052631578946, 'f1-score': 0.24561403508771928, 'support': 38.0}, 'accuracy': 0.9767818574514039, 'macro avg': {'precision': 0.6757544433916214, 'recall': 0.588797655660651, 'f1-score': 0.6169117611687569, 'support': 1852.0}, 'weighted avg': {'precision': 0.9704758807511438, 'recall': 0.9767818574514039, 'f1-score': 0.9729726475186071, 'support': 1852.0}}
• Hamming Si: 0.0232
• Classification Report Cl: {'~CL': {'precision': 0.9706227967097533, 'recall': 0.9886295631358468, 'f1-score': 0.9795434331455678, 'support': 1671.0}, 'CL': {'precision': 0.8733333333333333, 'recall': 0.7237569060773481, 'f1-score': 0.7915407854984894, 'support': 181.0}, 'accuracy': 0.962742980561555, 'macro avg': {'precision': 0.9219780650215432, 'recall': 0.8561932346065975, 'f1-score': 0.8855421093220286, 'support': 1852.0}, 'weighted avg': {'precision': 0.9611144852242608, 'recall': 0.962742980561555, 'f1-score': 0.9611695242772519, 'support': 1852.0}}
• Hamming Cl: 0.0373
• Classification Report D: {'~D': {'precision': 0.9978331527627302, 'recall': 1.0, 'f1-score': 0.9989154013015185, 'support': 1842.0}, 'D': {'precision': 1.0, 'recall': 0.6, 'f1-score': 0.75, 'support': 10.0}, 'accuracy': 0.9978401727861771, 'macro avg': {'precision': 0.9989165763813651, 'recall': 0.8, 'f1-score': 0.8744577006507592, 'support': 1852.0}, 'weighted avg': {'precision': 0.9978448528018083, 'recall': 0.9978401727861771, 'f1-score': 0.9975713656573418, 'support': 1852.0}}
• Hamming D: 0.0022
• Classification Report Hi: {'~HI': {'precision': 0.997289972899729, 'recall': 0.997289972899729, 'f1-score': 0.997289972899729, 'support': 1845.0}, 'HI': {'precision': 0.2857142857142857, 'recall': 0.2857142857142857, 'f1-score': 0.2857142857142857, 'support': 7.0}, 'accuracy': 0.9946004319654428, 'macro avg': {'precision': 0.6415021293070073, 'recall': 0.6415021293070073, 'f1-score': 0.6415021293070073, 'support': 1852.0}, 'weighted avg': {'precision': 0.9946004319654428, 'recall': 0.9946004319654428, 'f1-score': 0.9946004319654428, 'support': 1852.0}}
• Hamming Hi: 0.0054
• Classification Report Pl: {'~PL': {'precision': 0.9792349726775956, 'recall': 0.9944506104328524, 'f1-score': 0.986784140969163, 'support': 1802.0}, 'PL': {'precision': 0.5454545454545454, 'recall': 0.24, 'f1-score': 0.3333333333333333, 'support': 50.0}, 'accuracy': 0.9740820734341252, 'macro avg': {'precision': 0.7623447590660706, 'recall': 0.6172253052164263, 'f1-score': 0.6600587371512482, 'support': 1852.0}, 'weighted avg': {'precision': 0.9675238380333449, 'recall': 0.9740820734341252, 'f1-score': 0.9691423805038328, 'support': 1852.0}}
• Hamming Pl: 0.0259
• Classification Report Ti: {'~TI': {'precision': 0.9778516057585825, 'recall': 0.9838440111420613, 'f1-score': 0.9808386559289086, 'support': 1795.0}, 'TI': {'precision': 0.3695652173913043, 'recall': 0.2982456140350877, 'f1-score': 0.3300970873786408, 'support': 57.0}, 'accuracy': 0.962742980561555, 'macro avg': {'precision': 0.6737084115749434, 'recall': 0.6410448125885745, 'f1-score': 0.6554678716537747, 'support': 1852.0}, 'weighted avg': {'precision': 0.9591300484492224, 'recall': 0.962742980561555, 'f1-score': 0.9608104327067891, 'support': 1852.0}}
• Hamming Ti: 0.0373
• Classification Report Pc: {'~PC': {'precision': 0.986420423682781, 'recall': 0.9945235487404163, 'f1-score': 0.9904554131442597, 'support': 1826.0}, 'PC': {'precision': 0.09090909090909091, 'recall': 0.038461538461538464, 'f1-score': 0.05405405405405406, 'support': 26.0}, 'accuracy': 0.9811015118790497, 'macro avg': {'precision': 0.538664757295936, 'recall': 0.5164925436009774, 'f1-score': 0.5222547335991569, 'support': 1852.0}, 'weighted avg': {'precision': 0.9738484503285068, 'recall': 0.9811015118790497, 'f1-score': 0.9773093897445052, 'support': 1852.0}}
• Hamming Pc: 0.0189
• Global Avg: {'f1-score': 0.669168013264547, 'hamming': 0.020180885529157665}

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0001
• train_batch_size: 16
• eval_batch_size: 16
• seed: 32
• distributed_type: multi-GPU
• num_devices: 4
• total_train_batch_size: 64
• total_eval_batch_size: 64
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Classification Report Lin	Hamming Lin	Classification Report Si	Hamming Si	Classification Report Cl	Hamming Cl	Classification Report D	Hamming D	Classification Report Hi	Hamming Hi	Classification Report Pl	Hamming Pl	Classification Report Ti	Hamming Ti	Classification Report Pc	Hamming Pc	Global Avg
No log	1.0	98	0.0861	{'~LIN': {'precision': 0.9908207343412527, 'recall': 1.0, 'f1-score': 0.9953892053159751, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 17.0}, 'accuracy': 0.9908207343412527, 'macro avg': {'precision': 0.49541036717062636, 'recall': 0.5, 'f1-score': 0.49769460265798754, 'support': 1852.0}, 'weighted avg': {'precision': 0.9817257276005392, 'recall': 0.9908207343412527, 'f1-score': 0.9862522633665304, 'support': 1852.0}}	0.0092	{'~SI': {'precision': 0.9794816414686826, 'recall': 1.0, 'f1-score': 0.9896344789961812, 'support': 1814.0}, 'SI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 38.0}, 'accuracy': 0.9794816414686826, 'macro avg': {'precision': 0.4897408207343413, 'recall': 0.5, 'f1-score': 0.4948172394980906, 'support': 1852.0}, 'weighted avg': {'precision': 0.9593842859741848, 'recall': 0.9794816414686826, 'f1-score': 0.9693288039411839, 'support': 1852.0}}	0.0205	{'~CL': {'precision': 0.9056399132321041, 'recall': 0.9994015559545183, 'f1-score': 0.9502133712660028, 'support': 1671.0}, 'CL': {'precision': 0.875, 'recall': 0.03867403314917127, 'f1-score': 0.07407407407407407, 'support': 181.0}, 'accuracy': 0.9055075593952484, 'macro avg': {'precision': 0.890319956616052, 'recall': 0.5190377945518447, 'f1-score': 0.5121437226700385, 'support': 1852.0}, 'weighted avg': {'precision': 0.902645407673243, 'recall': 0.9055075593952484, 'f1-score': 0.8645863665188435, 'support': 1852.0}}	0.0945	{'~D': {'precision': 0.9946004319654428, 'recall': 1.0, 'f1-score': 0.9972929074174337, 'support': 1842.0}, 'D': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 10.0}, 'accuracy': 0.9946004319654428, 'macro avg': {'precision': 0.4973002159827214, 'recall': 0.5, 'f1-score': 0.49864645370871685, 'support': 1852.0}, 'weighted avg': {'precision': 0.9892300192658454, 'recall': 0.9946004319654428, 'f1-score': 0.9919079565134519, 'support': 1852.0}}	0.0054	{'~HI': {'precision': 0.9962203023758099, 'recall': 1.0, 'f1-score': 0.9981065728969435, 'support': 1845.0}, 'HI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 7.0}, 'accuracy': 0.9962203023758099, 'macro avg': {'precision': 0.49811015118790497, 'recall': 0.5, 'f1-score': 0.49905328644847174, 'support': 1852.0}, 'weighted avg': {'precision': 0.9924548908657502, 'recall': 0.9962203023758099, 'f1-score': 0.9943340318546764, 'support': 1852.0}}	0.0038	{'~PL': {'precision': 0.9730021598272138, 'recall': 1.0, 'f1-score': 0.9863163656267104, 'support': 1802.0}, 'PL': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 50.0}, 'accuracy': 0.9730021598272138, 'macro avg': {'precision': 0.4865010799136069, 'recall': 0.5, 'f1-score': 0.4931581828133552, 'support': 1852.0}, 'weighted avg': {'precision': 0.9467332030284229, 'recall': 0.9730021598272138, 'f1-score': 0.9596879540277172, 'support': 1852.0}}	0.0270	{'~TI': {'precision': 0.9692224622030238, 'recall': 1.0, 'f1-score': 0.9843707156567041, 'support': 1795.0}, 'TI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 57.0}, 'accuracy': 0.9692224622030238, 'macro avg': {'precision': 0.4846112311015119, 'recall': 0.5, 'f1-score': 0.49218535782835204, 'support': 1852.0}, 'weighted avg': {'precision': 0.9393921812388919, 'recall': 0.9692224622030238, 'f1-score': 0.9540742087493432, 'support': 1852.0}}	0.0308	{'~PC': {'precision': 0.9859611231101512, 'recall': 1.0, 'f1-score': 0.9929309407286568, 'support': 1826.0}, 'PC': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 26.0}, 'accuracy': 0.9859611231101512, 'macro avg': {'precision': 0.4929805615550756, 'recall': 0.5, 'f1-score': 0.4964654703643284, 'support': 1852.0}, 'weighted avg': {'precision': 0.9721193362846307, 'recall': 0.9859611231101512, 'f1-score': 0.9789913054916455, 'support': 1852.0}}	0.0140	{'f1-score': 0.4980205394986676, 'hamming': 0.02564794816414687}
No log	2.0	196	0.0755	{'~LIN': {'precision': 0.9908207343412527, 'recall': 1.0, 'f1-score': 0.9953892053159751, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 17.0}, 'accuracy': 0.9908207343412527, 'macro avg': {'precision': 0.49541036717062636, 'recall': 0.5, 'f1-score': 0.49769460265798754, 'support': 1852.0}, 'weighted avg': {'precision': 0.9817257276005392, 'recall': 0.9908207343412527, 'f1-score': 0.9862522633665304, 'support': 1852.0}}	0.0092	{'~SI': {'precision': 0.9794816414686826, 'recall': 1.0, 'f1-score': 0.9896344789961812, 'support': 1814.0}, 'SI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 38.0}, 'accuracy': 0.9794816414686826, 'macro avg': {'precision': 0.4897408207343413, 'recall': 0.5, 'f1-score': 0.4948172394980906, 'support': 1852.0}, 'weighted avg': {'precision': 0.9593842859741848, 'recall': 0.9794816414686826, 'f1-score': 0.9693288039411839, 'support': 1852.0}}	0.0205	{'~CL': {'precision': 0.9351381838691484, 'recall': 0.9922202274087373, 'f1-score': 0.9628339140534262, 'support': 1671.0}, 'CL': {'precision': 0.8354430379746836, 'recall': 0.36464088397790057, 'f1-score': 0.5076923076923077, 'support': 181.0}, 'accuracy': 0.9308855291576674, 'macro avg': {'precision': 0.885290610921916, 'recall': 0.6784305556933189, 'f1-score': 0.7352631108728669, 'support': 1852.0}, 'weighted avg': {'precision': 0.9253947597833503, 'recall': 0.9308855291576674, 'f1-score': 0.9183519320062543, 'support': 1852.0}}	0.0691	{'~D': {'precision': 0.9946004319654428, 'recall': 1.0, 'f1-score': 0.9972929074174337, 'support': 1842.0}, 'D': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 10.0}, 'accuracy': 0.9946004319654428, 'macro avg': {'precision': 0.4973002159827214, 'recall': 0.5, 'f1-score': 0.49864645370871685, 'support': 1852.0}, 'weighted avg': {'precision': 0.9892300192658454, 'recall': 0.9946004319654428, 'f1-score': 0.9919079565134519, 'support': 1852.0}}	0.0054	{'~HI': {'precision': 0.9962203023758099, 'recall': 1.0, 'f1-score': 0.9981065728969435, 'support': 1845.0}, 'HI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 7.0}, 'accuracy': 0.9962203023758099, 'macro avg': {'precision': 0.49811015118790497, 'recall': 0.5, 'f1-score': 0.49905328644847174, 'support': 1852.0}, 'weighted avg': {'precision': 0.9924548908657502, 'recall': 0.9962203023758099, 'f1-score': 0.9943340318546764, 'support': 1852.0}}	0.0038	{'~PL': {'precision': 0.9755434782608695, 'recall': 0.9961154273029966, 'f1-score': 0.985722130697419, 'support': 1802.0}, 'PL': {'precision': 0.4166666666666667, 'recall': 0.1, 'f1-score': 0.16129032258064516, 'support': 50.0}, 'accuracy': 0.9719222462203023, 'macro avg': {'precision': 0.6961050724637681, 'recall': 0.5480577136514984, 'f1-score': 0.5735062266390321, 'support': 1852.0}, 'weighted avg': {'precision': 0.9604550114251728, 'recall': 0.9719222462203023, 'f1-score': 0.9634642525085212, 'support': 1852.0}}	0.0281	{'~TI': {'precision': 0.9692224622030238, 'recall': 1.0, 'f1-score': 0.9843707156567041, 'support': 1795.0}, 'TI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 57.0}, 'accuracy': 0.9692224622030238, 'macro avg': {'precision': 0.4846112311015119, 'recall': 0.5, 'f1-score': 0.49218535782835204, 'support': 1852.0}, 'weighted avg': {'precision': 0.9393921812388919, 'recall': 0.9692224622030238, 'f1-score': 0.9540742087493432, 'support': 1852.0}}	0.0308	{'~PC': {'precision': 0.9859611231101512, 'recall': 1.0, 'f1-score': 0.9929309407286568, 'support': 1826.0}, 'PC': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 26.0}, 'accuracy': 0.9859611231101512, 'macro avg': {'precision': 0.4929805615550756, 'recall': 0.5, 'f1-score': 0.4964654703643284, 'support': 1852.0}, 'weighted avg': {'precision': 0.9721193362846307, 'recall': 0.9859611231101512, 'f1-score': 0.9789913054916455, 'support': 1852.0}}	0.0140	{'f1-score': 0.5359539685022308, 'hamming': 0.022610691144708425}
No log	3.0	294	0.0681	{'~LIN': {'precision': 0.9908207343412527, 'recall': 1.0, 'f1-score': 0.9953892053159751, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 17.0}, 'accuracy': 0.9908207343412527, 'macro avg': {'precision': 0.49541036717062636, 'recall': 0.5, 'f1-score': 0.49769460265798754, 'support': 1852.0}, 'weighted avg': {'precision': 0.9817257276005392, 'recall': 0.9908207343412527, 'f1-score': 0.9862522633665304, 'support': 1852.0}}	0.0092	{'~SI': {'precision': 0.9794816414686826, 'recall': 1.0, 'f1-score': 0.9896344789961812, 'support': 1814.0}, 'SI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 38.0}, 'accuracy': 0.9794816414686826, 'macro avg': {'precision': 0.4897408207343413, 'recall': 0.5, 'f1-score': 0.4948172394980906, 'support': 1852.0}, 'weighted avg': {'precision': 0.9593842859741848, 'recall': 0.9794816414686826, 'f1-score': 0.9693288039411839, 'support': 1852.0}}	0.0205	{'~CL': {'precision': 0.9633353045535187, 'recall': 0.9748653500897666, 'f1-score': 0.9690660321237359, 'support': 1671.0}, 'CL': {'precision': 0.7391304347826086, 'recall': 0.6574585635359116, 'f1-score': 0.695906432748538, 'support': 181.0}, 'accuracy': 0.9438444924406048, 'macro avg': {'precision': 0.8512328696680637, 'recall': 0.8161619568128391, 'f1-score': 0.832486232436137, 'support': 1852.0}, 'weighted avg': {'precision': 0.9414232735445907, 'recall': 0.9438444924406048, 'f1-score': 0.942369548599486, 'support': 1852.0}}	0.0562	{'~D': {'precision': 0.9946004319654428, 'recall': 1.0, 'f1-score': 0.9972929074174337, 'support': 1842.0}, 'D': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 10.0}, 'accuracy': 0.9946004319654428, 'macro avg': {'precision': 0.4973002159827214, 'recall': 0.5, 'f1-score': 0.49864645370871685, 'support': 1852.0}, 'weighted avg': {'precision': 0.9892300192658454, 'recall': 0.9946004319654428, 'f1-score': 0.9919079565134519, 'support': 1852.0}}	0.0054	{'~HI': {'precision': 0.9962203023758099, 'recall': 1.0, 'f1-score': 0.9981065728969435, 'support': 1845.0}, 'HI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 7.0}, 'accuracy': 0.9962203023758099, 'macro avg': {'precision': 0.49811015118790497, 'recall': 0.5, 'f1-score': 0.49905328644847174, 'support': 1852.0}, 'weighted avg': {'precision': 0.9924548908657502, 'recall': 0.9962203023758099, 'f1-score': 0.9943340318546764, 'support': 1852.0}}	0.0038	{'~PL': {'precision': 0.9730021598272138, 'recall': 1.0, 'f1-score': 0.9863163656267104, 'support': 1802.0}, 'PL': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 50.0}, 'accuracy': 0.9730021598272138, 'macro avg': {'precision': 0.4865010799136069, 'recall': 0.5, 'f1-score': 0.4931581828133552, 'support': 1852.0}, 'weighted avg': {'precision': 0.9467332030284229, 'recall': 0.9730021598272138, 'f1-score': 0.9596879540277172, 'support': 1852.0}}	0.0270	{'~TI': {'precision': 0.9692224622030238, 'recall': 1.0, 'f1-score': 0.9843707156567041, 'support': 1795.0}, 'TI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 57.0}, 'accuracy': 0.9692224622030238, 'macro avg': {'precision': 0.4846112311015119, 'recall': 0.5, 'f1-score': 0.49218535782835204, 'support': 1852.0}, 'weighted avg': {'precision': 0.9393921812388919, 'recall': 0.9692224622030238, 'f1-score': 0.9540742087493432, 'support': 1852.0}}	0.0308	{'~PC': {'precision': 0.9859611231101512, 'recall': 1.0, 'f1-score': 0.9929309407286568, 'support': 1826.0}, 'PC': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 26.0}, 'accuracy': 0.9859611231101512, 'macro avg': {'precision': 0.4929805615550756, 'recall': 0.5, 'f1-score': 0.4964654703643284, 'support': 1852.0}, 'weighted avg': {'precision': 0.9721193362846307, 'recall': 0.9859611231101512, 'f1-score': 0.9789913054916455, 'support': 1852.0}}	0.0140	{'f1-score': 0.5380633532194299, 'hamming': 0.020855831533477323}
No log	4.0	392	0.0752	{'~LIN': {'precision': 0.9908207343412527, 'recall': 1.0, 'f1-score': 0.9953892053159751, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 17.0}, 'accuracy': 0.9908207343412527, 'macro avg': {'precision': 0.49541036717062636, 'recall': 0.5, 'f1-score': 0.49769460265798754, 'support': 1852.0}, 'weighted avg': {'precision': 0.9817257276005392, 'recall': 0.9908207343412527, 'f1-score': 0.9862522633665304, 'support': 1852.0}}	0.0092	{'~SI': {'precision': 0.9794816414686826, 'recall': 1.0, 'f1-score': 0.9896344789961812, 'support': 1814.0}, 'SI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 38.0}, 'accuracy': 0.9794816414686826, 'macro avg': {'precision': 0.4897408207343413, 'recall': 0.5, 'f1-score': 0.4948172394980906, 'support': 1852.0}, 'weighted avg': {'precision': 0.9593842859741848, 'recall': 0.9794816414686826, 'f1-score': 0.9693288039411839, 'support': 1852.0}}	0.0205	{'~CL': {'precision': 0.936026936026936, 'recall': 0.9982046678635548, 'f1-score': 0.9661164205039097, 'support': 1671.0}, 'CL': {'precision': 0.9571428571428572, 'recall': 0.3701657458563536, 'f1-score': 0.5338645418326693, 'support': 181.0}, 'accuracy': 0.9368250539956804, 'macro avg': {'precision': 0.9465848965848966, 'recall': 0.6841852068599542, 'f1-score': 0.7499904811682895, 'support': 1852.0}, 'weighted avg': {'precision': 0.9380906410604034, 'recall': 0.9368250539956804, 'f1-score': 0.923871501476105, 'support': 1852.0}}	0.0632	{'~D': {'precision': 0.9946004319654428, 'recall': 1.0, 'f1-score': 0.9972929074174337, 'support': 1842.0}, 'D': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 10.0}, 'accuracy': 0.9946004319654428, 'macro avg': {'precision': 0.4973002159827214, 'recall': 0.5, 'f1-score': 0.49864645370871685, 'support': 1852.0}, 'weighted avg': {'precision': 0.9892300192658454, 'recall': 0.9946004319654428, 'f1-score': 0.9919079565134519, 'support': 1852.0}}	0.0054	{'~HI': {'precision': 0.9962203023758099, 'recall': 1.0, 'f1-score': 0.9981065728969435, 'support': 1845.0}, 'HI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 7.0}, 'accuracy': 0.9962203023758099, 'macro avg': {'precision': 0.49811015118790497, 'recall': 0.5, 'f1-score': 0.49905328644847174, 'support': 1852.0}, 'weighted avg': {'precision': 0.9924548908657502, 'recall': 0.9962203023758099, 'f1-score': 0.9943340318546764, 'support': 1852.0}}	0.0038	{'~PL': {'precision': 0.9730021598272138, 'recall': 1.0, 'f1-score': 0.9863163656267104, 'support': 1802.0}, 'PL': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 50.0}, 'accuracy': 0.9730021598272138, 'macro avg': {'precision': 0.4865010799136069, 'recall': 0.5, 'f1-score': 0.4931581828133552, 'support': 1852.0}, 'weighted avg': {'precision': 0.9467332030284229, 'recall': 0.9730021598272138, 'f1-score': 0.9596879540277172, 'support': 1852.0}}	0.0270	{'~TI': {'precision': 0.9692224622030238, 'recall': 1.0, 'f1-score': 0.9843707156567041, 'support': 1795.0}, 'TI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 57.0}, 'accuracy': 0.9692224622030238, 'macro avg': {'precision': 0.4846112311015119, 'recall': 0.5, 'f1-score': 0.49218535782835204, 'support': 1852.0}, 'weighted avg': {'precision': 0.9393921812388919, 'recall': 0.9692224622030238, 'f1-score': 0.9540742087493432, 'support': 1852.0}}	0.0308	{'~PC': {'precision': 0.9859611231101512, 'recall': 1.0, 'f1-score': 0.9929309407286568, 'support': 1826.0}, 'PC': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 26.0}, 'accuracy': 0.9859611231101512, 'macro avg': {'precision': 0.4929805615550756, 'recall': 0.5, 'f1-score': 0.4964654703643284, 'support': 1852.0}, 'weighted avg': {'precision': 0.9721193362846307, 'recall': 0.9859611231101512, 'f1-score': 0.9789913054916455, 'support': 1852.0}}	0.0140	{'f1-score': 0.5277513843109489, 'hamming': 0.021733261339092872}
No log	5.0	490	0.0725	{'~LIN': {'precision': 0.9908207343412527, 'recall': 1.0, 'f1-score': 0.9953892053159751, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 17.0}, 'accuracy': 0.9908207343412527, 'macro avg': {'precision': 0.49541036717062636, 'recall': 0.5, 'f1-score': 0.49769460265798754, 'support': 1852.0}, 'weighted avg': {'precision': 0.9817257276005392, 'recall': 0.9908207343412527, 'f1-score': 0.9862522633665304, 'support': 1852.0}}	0.0092	{'~SI': {'precision': 0.9794816414686826, 'recall': 1.0, 'f1-score': 0.9896344789961812, 'support': 1814.0}, 'SI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 38.0}, 'accuracy': 0.9794816414686826, 'macro avg': {'precision': 0.4897408207343413, 'recall': 0.5, 'f1-score': 0.4948172394980906, 'support': 1852.0}, 'weighted avg': {'precision': 0.9593842859741848, 'recall': 0.9794816414686826, 'f1-score': 0.9693288039411839, 'support': 1852.0}}	0.0205	{'~CL': {'precision': 0.9834050399508297, 'recall': 0.9575104727707959, 'f1-score': 0.9702850212249848, 'support': 1671.0}, 'CL': {'precision': 0.6844444444444444, 'recall': 0.850828729281768, 'f1-score': 0.7586206896551724, 'support': 181.0}, 'accuracy': 0.9470842332613391, 'macro avg': {'precision': 0.833924742197637, 'recall': 0.904169601026282, 'f1-score': 0.8644528554400785, 'support': 1852.0}, 'weighted avg': {'precision': 0.9541869687917284, 'recall': 0.9470842332613391, 'f1-score': 0.9495986043706998, 'support': 1852.0}}	0.0529	{'~D': {'precision': 0.9946004319654428, 'recall': 1.0, 'f1-score': 0.9972929074174337, 'support': 1842.0}, 'D': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 10.0}, 'accuracy': 0.9946004319654428, 'macro avg': {'precision': 0.4973002159827214, 'recall': 0.5, 'f1-score': 0.49864645370871685, 'support': 1852.0}, 'weighted avg': {'precision': 0.9892300192658454, 'recall': 0.9946004319654428, 'f1-score': 0.9919079565134519, 'support': 1852.0}}	0.0054	{'~HI': {'precision': 0.9962203023758099, 'recall': 1.0, 'f1-score': 0.9981065728969435, 'support': 1845.0}, 'HI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 7.0}, 'accuracy': 0.9962203023758099, 'macro avg': {'precision': 0.49811015118790497, 'recall': 0.5, 'f1-score': 0.49905328644847174, 'support': 1852.0}, 'weighted avg': {'precision': 0.9924548908657502, 'recall': 0.9962203023758099, 'f1-score': 0.9943340318546764, 'support': 1852.0}}	0.0038	{'~PL': {'precision': 0.9868646487721302, 'recall': 0.9589345172031076, 'f1-score': 0.9726991274978891, 'support': 1802.0}, 'PL': {'precision': 0.26732673267326734, 'recall': 0.54, 'f1-score': 0.3576158940397351, 'support': 50.0}, 'accuracy': 0.9476241900647948, 'macro avg': {'precision': 0.6270956907226988, 'recall': 0.7494672586015538, 'f1-score': 0.6651575107688121, 'support': 1852.0}, 'weighted avg': {'precision': 0.9674386791150335, 'recall': 0.9476241900647948, 'f1-score': 0.9560932086680254, 'support': 1852.0}}	0.0524	{'~TI': {'precision': 0.9718004338394793, 'recall': 0.9983286908077994, 'f1-score': 0.9848859576806815, 'support': 1795.0}, 'TI': {'precision': 0.625, 'recall': 0.08771929824561403, 'f1-score': 0.15384615384615385, 'support': 57.0}, 'accuracy': 0.9703023758099352, 'macro avg': {'precision': 0.7984002169197397, 'recall': 0.5430239945267067, 'f1-score': 0.5693660557634177, 'support': 1852.0}, 'weighted avg': {'precision': 0.961126770378977, 'recall': 0.9703023758099352, 'f1-score': 0.9593085987073726, 'support': 1852.0}}	0.0297	{'~PC': {'precision': 0.9859611231101512, 'recall': 1.0, 'f1-score': 0.9929309407286568, 'support': 1826.0}, 'PC': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 26.0}, 'accuracy': 0.9859611231101512, 'macro avg': {'precision': 0.4929805615550756, 'recall': 0.5, 'f1-score': 0.4964654703643284, 'support': 1852.0}, 'weighted avg': {'precision': 0.9721193362846307, 'recall': 0.9859611231101512, 'f1-score': 0.9789913054916455, 'support': 1852.0}}	0.0140	{'f1-score': 0.573206684331238, 'hamming': 0.023488120950323974}
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0.0034	27.0	2646	0.1765	{'~LIN': {'precision': 0.9907958852192745, 'recall': 0.997275204359673, 'f1-score': 0.9940249864204237, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 17.0}, 'accuracy': 0.9881209503239741, 'macro avg': {'precision': 0.49539794260963727, 'recall': 0.4986376021798365, 'f1-score': 0.49701249321021185, 'support': 1852.0}, 'weighted avg': {'precision': 0.9817011065752531, 'recall': 0.9881209503239741, 'f1-score': 0.9849005669986379, 'support': 1852.0}}	0.0119	{'~SI': {'precision': 0.9825041006014216, 'recall': 0.9906284454244763, 'f1-score': 0.9865495470765853, 'support': 1814.0}, 'SI': {'precision': 0.2608695652173913, 'recall': 0.15789473684210525, 'f1-score': 0.19672131147540983, 'support': 38.0}, 'accuracy': 0.9735421166306696, 'macro avg': {'precision': 0.6216868329094064, 'recall': 0.5742615911332908, 'f1-score': 0.5916354292759975, 'support': 1852.0}, 'weighted avg': {'precision': 0.9676973444758312, 'recall': 0.9735421166306696, 'f1-score': 0.9703435681603625, 'support': 1852.0}}	0.0265	{'~CL': {'precision': 0.9723040659988215, 'recall': 0.9874326750448833, 'f1-score': 0.9798099762470309, 'support': 1671.0}, 'CL': {'precision': 0.864516129032258, 'recall': 0.7403314917127072, 'f1-score': 0.7976190476190477, 'support': 181.0}, 'accuracy': 0.9632829373650108, 'macro avg': {'precision': 0.9184100975155398, 'recall': 0.8638820833787952, 'f1-score': 0.8887145119330393, 'support': 1852.0}, 'weighted avg': {'precision': 0.9617697157877264, 'recall': 0.9632829373650108, 'f1-score': 0.9620040593562831, 'support': 1852.0}}	0.0367	{'~D': {'precision': 0.9978331527627302, 'recall': 1.0, 'f1-score': 0.9989154013015185, 'support': 1842.0}, 'D': {'precision': 1.0, 'recall': 0.6, 'f1-score': 0.75, 'support': 10.0}, 'accuracy': 0.9978401727861771, 'macro avg': {'precision': 0.9989165763813651, 'recall': 0.8, 'f1-score': 0.8744577006507592, 'support': 1852.0}, 'weighted avg': {'precision': 0.9978448528018083, 'recall': 0.9978401727861771, 'f1-score': 0.9975713656573418, 'support': 1852.0}}	0.0022	{'~HI': {'precision': 0.9978319783197832, 'recall': 0.9978319783197832, 'f1-score': 0.9978319783197832, 'support': 1845.0}, 'HI': {'precision': 0.42857142857142855, 'recall': 0.42857142857142855, 'f1-score': 0.42857142857142855, 'support': 7.0}, 'accuracy': 0.9956803455723542, 'macro avg': {'precision': 0.7132017034456059, 'recall': 0.7132017034456059, 'f1-score': 0.7132017034456059, 'support': 1852.0}, 'weighted avg': {'precision': 0.9956803455723542, 'recall': 0.9956803455723542, 'f1-score': 0.9956803455723542, 'support': 1852.0}}	0.0043	{'~PL': {'precision': 0.9797037849698299, 'recall': 0.9911209766925638, 'f1-score': 0.9853793103448276, 'support': 1802.0}, 'PL': {'precision': 0.4482758620689655, 'recall': 0.26, 'f1-score': 0.3291139240506329, 'support': 50.0}, 'accuracy': 0.9713822894168467, 'macro avg': {'precision': 0.7139898235193978, 'recall': 0.625560488346282, 'f1-score': 0.6572466171977303, 'support': 1852.0}, 'weighted avg': {'precision': 0.9653563788439967, 'recall': 0.9713822894168467, 'f1-score': 0.9676615623347252, 'support': 1852.0}}	0.0286	{'~TI': {'precision': 0.9804469273743017, 'recall': 0.9777158774373259, 'f1-score': 0.9790794979079498, 'support': 1795.0}, 'TI': {'precision': 0.3548387096774194, 'recall': 0.38596491228070173, 'f1-score': 0.3697478991596639, 'support': 57.0}, 'accuracy': 0.9595032397408207, 'macro avg': {'precision': 0.6676428185258605, 'recall': 0.6818403948590138, 'f1-score': 0.6744136985338068, 'support': 1852.0}, 'weighted avg': {'precision': 0.9611922468080369, 'recall': 0.9595032397408207, 'f1-score': 0.9603257715965825, 'support': 1852.0}}	0.0405	{'~PC': {'precision': 0.9862788144895719, 'recall': 0.984118291347207, 'f1-score': 0.9851973684210527, 'support': 1826.0}, 'PC': {'precision': 0.03333333333333333, 'recall': 0.038461538461538464, 'f1-score': 0.03571428571428571, 'support': 26.0}, 'accuracy': 0.9708423326133909, 'macro avg': {'precision': 0.5098060739114526, 'recall': 0.5112899149043727, 'f1-score': 0.5104558270676692, 'support': 1852.0}, 'weighted avg': {'precision': 0.9729005301968817, 'recall': 0.9708423326133909, 'f1-score': 0.9718676923139381, 'support': 1852.0}}	0.0292	{'f1-score': 0.6758922476643525, 'hamming': 0.022475701943844496}
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0.0034	29.0	2842	0.1745	{'~LIN': {'precision': 0.9907759088442757, 'recall': 0.9950953678474115, 'f1-score': 0.9929309407286568, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 17.0}, 'accuracy': 0.9859611231101512, 'macro avg': {'precision': 0.49538795442213784, 'recall': 0.49754768392370574, 'f1-score': 0.4964654703643284, 'support': 1852.0}, 'weighted avg': {'precision': 0.9816813135687074, 'recall': 0.9859611231101512, 'f1-score': 0.9838165638429186, 'support': 1852.0}}	0.0140	{'~SI': {'precision': 0.984065934065934, 'recall': 0.9873208379272327, 'f1-score': 0.9856906989543203, 'support': 1814.0}, 'SI': {'precision': 0.28125, 'recall': 0.23684210526315788, 'f1-score': 0.2571428571428571, 'support': 38.0}, 'accuracy': 0.9719222462203023, 'macro avg': {'precision': 0.6326579670329671, 'recall': 0.6120814715951953, 'f1-score': 0.6214167780485886, 'support': 1852.0}, 'weighted avg': {'precision': 0.9696453047492464, 'recall': 0.9719222462203023, 'f1-score': 0.9707420931288151, 'support': 1852.0}}	0.0281	{'~CL': {'precision': 0.9695014662756598, 'recall': 0.9892280071813285, 'f1-score': 0.9792654028436019, 'support': 1671.0}, 'CL': {'precision': 0.8775510204081632, 'recall': 0.712707182320442, 'f1-score': 0.7865853658536586, 'support': 181.0}, 'accuracy': 0.9622030237580994, 'macro avg': {'precision': 0.9235262433419116, 'recall': 0.8509675947508852, 'f1-score': 0.8829253843486302, 'support': 1852.0}, 'weighted avg': {'precision': 0.9605149486179834, 'recall': 0.9622030237580994, 'f1-score': 0.9604343625114313, 'support': 1852.0}}	0.0378	{'~D': {'precision': 0.9978331527627302, 'recall': 1.0, 'f1-score': 0.9989154013015185, 'support': 1842.0}, 'D': {'precision': 1.0, 'recall': 0.6, 'f1-score': 0.75, 'support': 10.0}, 'accuracy': 0.9978401727861771, 'macro avg': {'precision': 0.9989165763813651, 'recall': 0.8, 'f1-score': 0.8744577006507592, 'support': 1852.0}, 'weighted avg': {'precision': 0.9978448528018083, 'recall': 0.9978401727861771, 'f1-score': 0.9975713656573418, 'support': 1852.0}}	0.0022	{'~HI': {'precision': 0.9972840847365562, 'recall': 0.9951219512195122, 'f1-score': 0.9962018448182312, 'support': 1845.0}, 'HI': {'precision': 0.18181818181818182, 'recall': 0.2857142857142857, 'f1-score': 0.2222222222222222, 'support': 7.0}, 'accuracy': 0.9924406047516199, 'macro avg': {'precision': 0.589551133277369, 'recall': 0.6404181184668989, 'f1-score': 0.6092120335202267, 'support': 1852.0}, 'weighted avg': {'precision': 0.9942018702006875, 'recall': 0.9924406047516199, 'f1-score': 0.9932764358775334, 'support': 1852.0}}	0.0076	{'~PL': {'precision': 0.9823982398239824, 'recall': 0.9911209766925638, 'f1-score': 0.9867403314917127, 'support': 1802.0}, 'PL': {'precision': 0.5294117647058824, 'recall': 0.36, 'f1-score': 0.42857142857142855, 'support': 50.0}, 'accuracy': 0.9740820734341252, 'macro avg': {'precision': 0.7559050022649324, 'recall': 0.6755604883462819, 'f1-score': 0.7076558800315706, 'support': 1852.0}, 'weighted avg': {'precision': 0.9701685833683102, 'recall': 0.9740820734341252, 'f1-score': 0.9716709766612514, 'support': 1852.0}}	0.0259	{'~TI': {'precision': 0.9746556473829201, 'recall': 0.9855153203342618, 'f1-score': 0.9800554016620499, 'support': 1795.0}, 'TI': {'precision': 0.2972972972972973, 'recall': 0.19298245614035087, 'f1-score': 0.23404255319148937, 'support': 57.0}, 'accuracy': 0.9611231101511879, 'macro avg': {'precision': 0.6359764723401087, 'recall': 0.5892488882373064, 'f1-score': 0.6070489774267696, 'support': 1852.0}, 'weighted avg': {'precision': 0.9538082251610625, 'recall': 0.9611231101511879, 'f1-score': 0.9570949630212173, 'support': 1852.0}}	0.0389	{'~PC': {'precision': 0.986870897155361, 'recall': 0.9879518072289156, 'f1-score': 0.9874110563765737, 'support': 1826.0}, 'PC': {'precision': 0.08333333333333333, 'recall': 0.07692307692307693, 'f1-score': 0.08, 'support': 26.0}, 'accuracy': 0.9751619870410367, 'macro avg': {'precision': 0.5351021152443471, 'recall': 0.5324374420759963, 'f1-score': 0.5337055281882869, 'support': 1852.0}, 'weighted avg': {'precision': 0.9741862445315097, 'recall': 0.9751619870410367, 'f1-score': 0.9746720242676152, 'support': 1852.0}}	0.0248	{'f1-score': 0.666610969072395, 'hamming': 0.022408207343412527}
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0.0002	50.0	4900	0.2041	{'~LIN': {'precision': 0.9908008658008658, 'recall': 0.9978201634877384, 'f1-score': 0.9942981265272876, 'support': 1835.0}, 'LIN': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 17.0}, 'accuracy': 0.9886609071274298, 'macro avg': {'precision': 0.4954004329004329, 'recall': 0.4989100817438692, 'f1-score': 0.4971490632636438, 'support': 1852.0}, 'weighted avg': {'precision': 0.9817060414387628, 'recall': 0.9886609071274298, 'f1-score': 0.9851711998798988, 'support': 1852.0}}	0.0113	{'~SI': {'precision': 0.9830878341516639, 'recall': 0.9933847850055126, 'f1-score': 0.9882094872497944, 'support': 1814.0}, 'SI': {'precision': 0.3684210526315789, 'recall': 0.18421052631578946, 'f1-score': 0.24561403508771928, 'support': 38.0}, 'accuracy': 0.9767818574514039, 'macro avg': {'precision': 0.6757544433916214, 'recall': 0.588797655660651, 'f1-score': 0.6169117611687569, 'support': 1852.0}, 'weighted avg': {'precision': 0.9704758807511438, 'recall': 0.9767818574514039, 'f1-score': 0.9729726475186071, 'support': 1852.0}}	0.0232	{'~CL': {'precision': 0.9706227967097533, 'recall': 0.9886295631358468, 'f1-score': 0.9795434331455678, 'support': 1671.0}, 'CL': {'precision': 0.8733333333333333, 'recall': 0.7237569060773481, 'f1-score': 0.7915407854984894, 'support': 181.0}, 'accuracy': 0.962742980561555, 'macro avg': {'precision': 0.9219780650215432, 'recall': 0.8561932346065975, 'f1-score': 0.8855421093220286, 'support': 1852.0}, 'weighted avg': {'precision': 0.9611144852242608, 'recall': 0.962742980561555, 'f1-score': 0.9611695242772519, 'support': 1852.0}}	0.0373	{'~D': {'precision': 0.9978331527627302, 'recall': 1.0, 'f1-score': 0.9989154013015185, 'support': 1842.0}, 'D': {'precision': 1.0, 'recall': 0.6, 'f1-score': 0.75, 'support': 10.0}, 'accuracy': 0.9978401727861771, 'macro avg': {'precision': 0.9989165763813651, 'recall': 0.8, 'f1-score': 0.8744577006507592, 'support': 1852.0}, 'weighted avg': {'precision': 0.9978448528018083, 'recall': 0.9978401727861771, 'f1-score': 0.9975713656573418, 'support': 1852.0}}	0.0022	{'~HI': {'precision': 0.997289972899729, 'recall': 0.997289972899729, 'f1-score': 0.997289972899729, 'support': 1845.0}, 'HI': {'precision': 0.2857142857142857, 'recall': 0.2857142857142857, 'f1-score': 0.2857142857142857, 'support': 7.0}, 'accuracy': 0.9946004319654428, 'macro avg': {'precision': 0.6415021293070073, 'recall': 0.6415021293070073, 'f1-score': 0.6415021293070073, 'support': 1852.0}, 'weighted avg': {'precision': 0.9946004319654428, 'recall': 0.9946004319654428, 'f1-score': 0.9946004319654428, 'support': 1852.0}}	0.0054	{'~PL': {'precision': 0.9792349726775956, 'recall': 0.9944506104328524, 'f1-score': 0.986784140969163, 'support': 1802.0}, 'PL': {'precision': 0.5454545454545454, 'recall': 0.24, 'f1-score': 0.3333333333333333, 'support': 50.0}, 'accuracy': 0.9740820734341252, 'macro avg': {'precision': 0.7623447590660706, 'recall': 0.6172253052164263, 'f1-score': 0.6600587371512482, 'support': 1852.0}, 'weighted avg': {'precision': 0.9675238380333449, 'recall': 0.9740820734341252, 'f1-score': 0.9691423805038328, 'support': 1852.0}}	0.0259	{'~TI': {'precision': 0.9778516057585825, 'recall': 0.9838440111420613, 'f1-score': 0.9808386559289086, 'support': 1795.0}, 'TI': {'precision': 0.3695652173913043, 'recall': 0.2982456140350877, 'f1-score': 0.3300970873786408, 'support': 57.0}, 'accuracy': 0.962742980561555, 'macro avg': {'precision': 0.6737084115749434, 'recall': 0.6410448125885745, 'f1-score': 0.6554678716537747, 'support': 1852.0}, 'weighted avg': {'precision': 0.9591300484492224, 'recall': 0.962742980561555, 'f1-score': 0.9608104327067891, 'support': 1852.0}}	0.0373	{'~PC': {'precision': 0.986420423682781, 'recall': 0.9945235487404163, 'f1-score': 0.9904554131442597, 'support': 1826.0}, 'PC': {'precision': 0.09090909090909091, 'recall': 0.038461538461538464, 'f1-score': 0.05405405405405406, 'support': 26.0}, 'accuracy': 0.9811015118790497, 'macro avg': {'precision': 0.538664757295936, 'recall': 0.5164925436009774, 'f1-score': 0.5222547335991569, 'support': 1852.0}, 'weighted avg': {'precision': 0.9738484503285068, 'recall': 0.9811015118790497, 'f1-score': 0.9773093897445052, 'support': 1852.0}}	0.0189	{'f1-score': 0.669168013264547, 'hamming': 0.020180885529157665}

Framework versions

• Transformers 4.53.1
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.21.1