diff --git "a/README.md" "b/README.md" --- "a/README.md" +++ "b/README.md" @@ -16,24 +16,24 @@ should probably proofread and complete it, then remove this comment. --> This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset. It achieves the following results on the evaluation set: -- Loss: 0.1883 -- Classification Report Lin: {'~LIN': {'precision': 0.9913466738777718, 'recall': 0.9989100817438692, 'f1-score': 0.995114006514658, 'support': 1835.0}, 'LIN': {'precision': 0.3333333333333333, 'recall': 0.058823529411764705, 'f1-score': 0.1, 'support': 17.0}, 'accuracy': 0.990280777537797, 'macro avg': {'precision': 0.6623400036055526, 'recall': 0.528866805577817, 'f1-score': 0.547557003257329, 'support': 1852.0}, 'weighted avg': {'precision': 0.9853065946179146, 'recall': 0.990280777537797, 'f1-score': 0.9868975172539942, 'support': 1852.0}} -- Hamming Lin: 0.0097 -- Classification Report Si: {'~SI': {'precision': 0.983032293377121, 'recall': 0.9900771775082691, 'f1-score': 0.9865421587475968, 'support': 1814.0}, 'SI': {'precision': 0.28, 'recall': 0.18421052631578946, 'f1-score': 0.2222222222222222, 'support': 38.0}, 'accuracy': 0.9735421166306696, 'macro avg': {'precision': 0.6315161466885605, 'recall': 0.5871438519120292, 'f1-score': 0.6043821904849095, 'support': 1852.0}, 'weighted avg': {'precision': 0.9686072247225148, 'recall': 0.9735421166306696, 'f1-score': 0.9708595682573352, 'support': 1852.0}} -- Hamming Si: 0.0265 -- Classification Report Cl: {'~CL': {'precision': 0.9747652582159625, 'recall': 0.9940155595451825, 'f1-score': 0.9842962962962963, 'support': 1671.0}, 'CL': {'precision': 0.9324324324324325, 'recall': 0.7624309392265194, 'f1-score': 0.8389057750759878, 'support': 181.0}, 'accuracy': 0.9713822894168467, 'macro avg': {'precision': 0.9535988453241975, 'recall': 0.878223249385851, 'f1-score': 0.9116010356861421, 'support': 1852.0}, 'weighted avg': {'precision': 0.970627978806233, 'recall': 0.9713822894168467, 'f1-score': 0.9700869634988472, 'support': 1852.0}} -- Hamming Cl: 0.0286 -- Classification Report D: {'~D': {'precision': 0.9972929074174337, 'recall': 1.0, 'f1-score': 0.9986446191379778, 'support': 1842.0}, 'D': {'precision': 1.0, 'recall': 0.5, 'f1-score': 0.6666666666666666, 'support': 10.0}, 'accuracy': 0.9973002159827213, 'macro avg': {'precision': 0.9986464537087169, 'recall': 0.75, 'f1-score': 0.8326556429023222, 'support': 1852.0}, 'weighted avg': {'precision': 0.9973075245480091, 'recall': 0.9973002159827213, 'f1-score': 0.9968520815976359, 'support': 1852.0}} -- Hamming D: 0.0027 -- Classification Report Hi: {'~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}} -- Hamming Hi: 0.0038 -- Classification Report Pl: {'~PL': {'precision': 0.9818880351262349, 'recall': 0.9927857935627081, 'f1-score': 0.9873068432671082, 'support': 1802.0}, 'PL': {'precision': 0.5666666666666667, 'recall': 0.34, 'f1-score': 0.425, 'support': 50.0}, 'accuracy': 0.9751619870410367, 'macro avg': {'precision': 0.7742773508964508, 'recall': 0.666392896781354, 'f1-score': 0.7061534216335541, 'support': 1852.0}, 'weighted avg': {'precision': 0.9706779549842379, 'recall': 0.9751619870410367, 'f1-score': 0.9721257729845189, 'support': 1852.0}} -- Hamming Pl: 0.0248 -- Classification Report Ti: {'~TI': {'precision': 0.9837716843872412, 'recall': 0.9793871866295265, 'f1-score': 0.981574539363484, 'support': 1795.0}, 'TI': {'precision': 0.4307692307692308, 'recall': 0.49122807017543857, 'f1-score': 0.45901639344262296, 'support': 57.0}, 'accuracy': 0.9643628509719222, 'macro avg': {'precision': 0.707270457578236, 'recall': 0.7353076284024825, 'f1-score': 0.7202954664030535, 'support': 1852.0}, 'weighted avg': {'precision': 0.9667516304691922, 'recall': 0.9643628509719222, 'f1-score': 0.965491486276287, 'support': 1852.0}} -- Hamming Ti: 0.0356 -- Classification Report Pc: {'~PC': {'precision': 0.986449864498645, 'recall': 0.9967141292442497, 'f1-score': 0.991555434486516, 'support': 1826.0}, 'PC': {'precision': 0.14285714285714285, 'recall': 0.038461538461538464, 'f1-score': 0.06060606060606061, 'support': 26.0}, 'accuracy': 0.9832613390928726, 'macro avg': {'precision': 0.5646535036778939, 'recall': 0.5175878338528941, 'f1-score': 0.5260807475462883, 'support': 1852.0}, 'weighted avg': {'precision': 0.9746067701343475, 'recall': 0.9832613390928726, 'f1-score': 0.9784859508359264, 'support': 1852.0}} -- Hamming Pc: 0.0167 -- Global Avg: {'f1-score': 0.6684723492952589, 'hamming': 0.0185610151187905} +- Loss: 0.2319 +- Classification Report Lin: {'~LIN': {'precision': 0.9923830250272034, 'recall': 0.9940054495912807, 'f1-score': 0.9931935747345494, 'support': 1835.0}, 'LIN': {'precision': 0.21428571428571427, 'recall': 0.17647058823529413, 'f1-score': 0.1935483870967742, 'support': 17.0}, 'accuracy': 0.9865010799136069, 'macro avg': {'precision': 0.6033343696564588, 'recall': 0.5852380189132874, 'f1-score': 0.5933709809156618, 'support': 1852.0}, 'weighted avg': {'precision': 0.9852406631035504, 'recall': 0.9865010799136069, 'f1-score': 0.9858534191244834, 'support': 1852.0}} +- Hamming Lin: 0.0135 +- Classification Report Si: {'~SI': {'precision': 0.9798365122615804, 'recall': 0.9911797133406836, 'f1-score': 0.9854754727322554, 'support': 1814.0}, 'SI': {'precision': 0.058823529411764705, 'recall': 0.02631578947368421, 'f1-score': 0.03636363636363636, 'support': 38.0}, 'accuracy': 0.9713822894168467, 'macro avg': {'precision': 0.5193300208366726, 'recall': 0.5087477514071839, 'f1-score': 0.5109195545479459, 'support': 1852.0}, 'weighted avg': {'precision': 0.9609388376674698, 'recall': 0.9713822894168467, 'f1-score': 0.966001255787327, 'support': 1852.0}} +- Hamming Si: 0.0286 +- Classification Report Cl: {'~CL': {'precision': 0.9677608440797186, 'recall': 0.988031119090365, 'f1-score': 0.9777909387029908, 'support': 1671.0}, 'CL': {'precision': 0.863013698630137, 'recall': 0.6961325966850829, 'f1-score': 0.7706422018348624, 'support': 181.0}, 'accuracy': 0.9595032397408207, 'macro avg': {'precision': 0.9153872713549278, 'recall': 0.8420818578877239, 'f1-score': 0.8742165702689266, 'support': 1852.0}, 'weighted avg': {'precision': 0.9575236770568384, 'recall': 0.9595032397408207, 'f1-score': 0.9575458407693347, 'support': 1852.0}} +- Hamming Cl: 0.0405 +- Classification Report D: {'~D': {'precision': 0.997289972899729, 'recall': 0.998914223669924, 'f1-score': 0.9981014374830486, 'support': 1842.0}, 'D': {'precision': 0.7142857142857143, 'recall': 0.5, 'f1-score': 0.5882352941176471, 'support': 10.0}, 'accuracy': 0.9962203023758099, 'macro avg': {'precision': 0.8557878435927216, 'recall': 0.749457111834962, 'f1-score': 0.7931683658003479, 'support': 1852.0}, 'weighted avg': {'precision': 0.9957618721512732, 'recall': 0.9962203023758099, 'f1-score': 0.9958883373568855, 'support': 1852.0}} +- Hamming D: 0.0038 +- Classification Report Hi: {'~HI': {'precision': 0.9961935834692768, 'recall': 0.9929539295392954, 'f1-score': 0.99457111834962, 'support': 1845.0}, 'HI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 7.0}, 'accuracy': 0.9892008639308856, 'macro avg': {'precision': 0.4980967917346384, 'recall': 0.4964769647696477, 'f1-score': 0.49728555917481, 'support': 1852.0}, 'weighted avg': {'precision': 0.9924282729486045, 'recall': 0.9892008639308856, 'f1-score': 0.9908119402565059, 'support': 1852.0}} +- Hamming Hi: 0.0108 +- Classification Report Pl: {'~PL': {'precision': 0.9808533916849015, 'recall': 0.9950055493895672, 'f1-score': 0.9878787878787879, 'support': 1802.0}, 'PL': {'precision': 0.625, 'recall': 0.3, 'f1-score': 0.40540540540540543, 'support': 50.0}, 'accuracy': 0.9762419006479481, 'macro avg': {'precision': 0.8029266958424508, 'recall': 0.6475027746947836, 'f1-score': 0.6966420966420966, 'support': 1852.0}, 'weighted avg': {'precision': 0.9712461186912487, 'recall': 0.9762419006479481, 'f1-score': 0.9721532645938693, 'support': 1852.0}} +- Hamming Pl: 0.0238 +- Classification Report Ti: {'~TI': {'precision': 0.9785478547854786, 'recall': 0.9910863509749304, 'f1-score': 0.984777193468032, 'support': 1795.0}, 'TI': {'precision': 0.5294117647058824, 'recall': 0.3157894736842105, 'f1-score': 0.3956043956043956, 'support': 57.0}, 'accuracy': 0.9703023758099352, 'macro avg': {'precision': 0.7539798097456805, 'recall': 0.6534379123295704, 'f1-score': 0.6901907945362138, 'support': 1852.0}, 'weighted avg': {'precision': 0.9647245517970677, 'recall': 0.9703023758099352, 'f1-score': 0.9666439054128337, 'support': 1852.0}} +- Hamming Ti: 0.0297 +- Classification Report Pc: {'~PC': {'precision': 0.9878453038674033, 'recall': 0.9791894852135816, 'f1-score': 0.9834983498349835, 'support': 1826.0}, 'PC': {'precision': 0.09523809523809523, 'recall': 0.15384615384615385, 'f1-score': 0.11764705882352941, 'support': 26.0}, 'accuracy': 0.9676025917926566, 'macro avg': {'precision': 0.5415416995527493, 'recall': 0.5665178195298677, 'f1-score': 0.5505727043292564, 'support': 1852.0}, 'weighted avg': {'precision': 0.9753141011544648, 'recall': 0.9676025917926566, 'f1-score': 0.9713427701555571, 'support': 1852.0}} +- Hamming Pc: 0.0324 +- Global Avg: {'f1-score': 0.6507958282769073, 'hamming': 0.022880669546436288} ## Model description @@ -55,7 +55,7 @@ The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 16 - eval_batch_size: 16 -- seed: 42 +- seed: 52 - distributed_type: multi-GPU - num_devices: 4 - total_train_batch_size: 64 @@ -66,58 +66,58 @@ The following hyperparameters were used during training: ### 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 | 0.0811 | {'~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': 0.902267818574514, 'recall': 1.0, 'f1-score': 0.94862333238717, 'support': 1671.0}, 'CL': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 181.0}, 'accuracy': 0.902267818574514, 'macro avg': {'precision': 0.451133909287257, 'recall': 0.5, 'f1-score': 0.474311666193585, 'support': 1852.0}, 'weighted avg': {'precision': 0.8140872164352121, 'recall': 0.902267818574514, 'f1-score': 0.855912304761858, 'support': 1852.0}} | 0.0977 | {'~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': 0.49329153243911095, 'hamming': 0.02605291576673866} | -| No log | 2.0 | 196 | 0.0742 | {'~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': 0.9802276812462553, 'recall': 0.9790544584081389, 'f1-score': 0.9796407185628743, 'support': 1671.0}, 'CL': {'precision': 0.8087431693989071, 'recall': 0.8176795580110497, 'f1-score': 0.8131868131868132, 'support': 181.0}, 'accuracy': 0.9632829373650108, 'macro avg': {'precision': 0.8944854253225811, 'recall': 0.8983670082095943, 'f1-score': 0.8964137658748437, 'support': 1852.0}, 'weighted avg': {'precision': 0.9634681258227293, 'recall': 0.9632829373650108, 'f1-score': 0.9633728152836804, 'support': 1852.0}} | 0.0367 | {'~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': 0.9743028977583379, 'recall': 0.992757660167131, 'f1-score': 0.9834437086092715, 'support': 1795.0}, 'TI': {'precision': 0.43478260869565216, 'recall': 0.17543859649122806, 'f1-score': 0.25, 'support': 57.0}, 'accuracy': 0.9676025917926566, 'macro avg': {'precision': 0.704542753226995, 'recall': 0.5840981283291795, 'f1-score': 0.6167218543046358, 'support': 1852.0}, 'weighted avg': {'precision': 0.9576977916694756, 'recall': 0.9676025917926566, 'f1-score': 0.9608701171455952, 'support': 1852.0}} | 0.0324 | {'~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': 0.5616213569588038, 'hamming': 0.018628509719222464} | -| No log | 3.0 | 294 | 0.0844 | {'~LIN': 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| 0.0097 | {'~SI': {'precision': 0.983032293377121, 'recall': 0.9900771775082691, 'f1-score': 0.9865421587475968, 'support': 1814.0}, 'SI': {'precision': 0.28, 'recall': 0.18421052631578946, 'f1-score': 0.2222222222222222, 'support': 38.0}, 'accuracy': 0.9735421166306696, 'macro avg': {'precision': 0.6315161466885605, 'recall': 0.5871438519120292, 'f1-score': 0.6043821904849095, 'support': 1852.0}, 'weighted avg': {'precision': 0.9686072247225148, 'recall': 0.9735421166306696, 'f1-score': 0.9708595682573352, 'support': 1852.0}} | 0.0265 | {'~CL': {'precision': 0.9747652582159625, 'recall': 0.9940155595451825, 'f1-score': 0.9842962962962963, 'support': 1671.0}, 'CL': {'precision': 0.9324324324324325, 'recall': 0.7624309392265194, 'f1-score': 0.8389057750759878, 'support': 181.0}, 'accuracy': 0.9713822894168467, 'macro avg': {'precision': 0.9535988453241975, 'recall': 0.878223249385851, 'f1-score': 0.9116010356861421, 'support': 1852.0}, 'weighted avg': {'precision': 0.970627978806233, 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avg': {'precision': 0.9667516304691922, 'recall': 0.9643628509719222, 'f1-score': 0.965491486276287, 'support': 1852.0}} | 0.0356 | {'~PC': {'precision': 0.986449864498645, 'recall': 0.9967141292442497, 'f1-score': 0.991555434486516, 'support': 1826.0}, 'PC': {'precision': 0.14285714285714285, 'recall': 0.038461538461538464, 'f1-score': 0.06060606060606061, 'support': 26.0}, 'accuracy': 0.9832613390928726, 'macro avg': {'precision': 0.5646535036778939, 'recall': 0.5175878338528941, 'f1-score': 0.5260807475462883, 'support': 1852.0}, 'weighted avg': {'precision': 0.9746067701343475, 'recall': 0.9832613390928726, 'f1-score': 0.9784859508359264, 'support': 1852.0}} | 0.0167 | {'f1-score': 0.6684723492952589, 'hamming': 0.0185610151187905} | +| 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 | 0.0840 | {'~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': 0.9110497237569061, 'recall': 0.9868342309994016, 'f1-score': 0.9474288997414536, 'support': 1671.0}, 'CL': {'precision': 0.47619047619047616, 'recall': 0.11049723756906077, 'f1-score': 0.17937219730941703, 'support': 181.0}, 'accuracy': 0.9011879049676026, 'macro avg': {'precision': 0.6936200999736911, 'recall': 0.5486657342842312, 'f1-score': 0.5634005485254353, 'support': 1852.0}, 'weighted avg': {'precision': 0.8685499808791934, 'recall': 0.9011879049676026, 'f1-score': 0.8723650427543053, 'support': 1852.0}} | 0.0988 | {'~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': 0.5044276427305923, 'hamming': 0.026187904967602593} | +| No log | 2.0 | 196 | 0.0740 | {'~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': 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{'~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': 0.5162386019365819, 'hamming': 0.023758099352051837} | +| No log | 3.0 | 294 | 0.0689 | {'~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': 0.9403069926094372, 'recall': 0.9898264512268103, 'f1-score': 0.9644314868804664, 'support': 1671.0}, 'CL': {'precision': 0.8172043010752689, 'recall': 0.4198895027624309, 'f1-score': 0.5547445255474452, 'support': 181.0}, 'accuracy': 0.9341252699784017, 'macro avg': {'precision': 0.878755646842353, 'recall': 0.7048579769946206, 'f1-score': 0.7595880062139558, 'support': 1852.0}, 'weighted avg': {'precision': 0.9282758980264543, 'recall': 0.9341252699784017, 'f1-score': 0.9243918864478116, 'support': 1852.0}} | 0.0659 | {'~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': 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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': 0.9617871840094062, 'recall': 0.9790544584081389, 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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': 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0.9834983498349835, 'support': 1826.0}, 'PC': {'precision': 0.09523809523809523, 'recall': 0.15384615384615385, 'f1-score': 0.11764705882352941, 'support': 26.0}, 'accuracy': 0.9676025917926566, 'macro avg': {'precision': 0.5415416995527493, 'recall': 0.5665178195298677, 'f1-score': 0.5505727043292564, 'support': 1852.0}, 'weighted avg': {'precision': 0.9753141011544648, 'recall': 0.9676025917926566, 'f1-score': 0.9713427701555571, 'support': 1852.0}} | 0.0324 | {'f1-score': 0.6507958282769073, 'hamming': 0.022880669546436288} | +| 0.0001 | 50.0 | 4900 | 0.2319 | {'~LIN': {'precision': 0.9923830250272034, 'recall': 0.9940054495912807, 'f1-score': 0.9931935747345494, 'support': 1835.0}, 'LIN': {'precision': 0.21428571428571427, 'recall': 0.17647058823529413, 'f1-score': 0.1935483870967742, 'support': 17.0}, 'accuracy': 0.9865010799136069, 'macro avg': {'precision': 0.6033343696564588, 'recall': 0.5852380189132874, 'f1-score': 0.5933709809156618, 'support': 1852.0}, 'weighted avg': {'precision': 0.9852406631035504, 'recall': 0.9865010799136069, 'f1-score': 0.9858534191244834, 'support': 1852.0}} | 0.0135 | {'~SI': {'precision': 0.9798365122615804, 'recall': 0.9911797133406836, 'f1-score': 0.9854754727322554, 'support': 1814.0}, 'SI': {'precision': 0.058823529411764705, 'recall': 0.02631578947368421, 'f1-score': 0.03636363636363636, 'support': 38.0}, 'accuracy': 0.9713822894168467, 'macro avg': {'precision': 0.5193300208366726, 'recall': 0.5087477514071839, 'f1-score': 0.5109195545479459, 'support': 1852.0}, 'weighted avg': {'precision': 0.9609388376674698, 'recall': 0.9713822894168467, 'f1-score': 0.966001255787327, 'support': 1852.0}} | 0.0286 | {'~CL': {'precision': 0.9677608440797186, 'recall': 0.988031119090365, 'f1-score': 0.9777909387029908, 'support': 1671.0}, 'CL': {'precision': 0.863013698630137, 'recall': 0.6961325966850829, 'f1-score': 0.7706422018348624, 'support': 181.0}, 'accuracy': 0.9595032397408207, 'macro avg': {'precision': 0.9153872713549278, 'recall': 0.8420818578877239, 'f1-score': 0.8742165702689266, 'support': 1852.0}, 'weighted avg': {'precision': 0.9575236770568384, 'recall': 0.9595032397408207, 'f1-score': 0.9575458407693347, 'support': 1852.0}} | 0.0405 | {'~D': {'precision': 0.997289972899729, 'recall': 0.998914223669924, 'f1-score': 0.9981014374830486, 'support': 1842.0}, 'D': {'precision': 0.7142857142857143, 'recall': 0.5, 'f1-score': 0.5882352941176471, 'support': 10.0}, 'accuracy': 0.9962203023758099, 'macro avg': {'precision': 0.8557878435927216, 'recall': 0.749457111834962, 'f1-score': 0.7931683658003479, 'support': 1852.0}, 'weighted avg': {'precision': 0.9957618721512732, 'recall': 0.9962203023758099, 'f1-score': 0.9958883373568855, 'support': 1852.0}} | 0.0038 | {'~HI': {'precision': 0.9961935834692768, 'recall': 0.9929539295392954, 'f1-score': 0.99457111834962, 'support': 1845.0}, 'HI': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 7.0}, 'accuracy': 0.9892008639308856, 'macro avg': {'precision': 0.4980967917346384, 'recall': 0.4964769647696477, 'f1-score': 0.49728555917481, 'support': 1852.0}, 'weighted avg': {'precision': 0.9924282729486045, 'recall': 0.9892008639308856, 'f1-score': 0.9908119402565059, 'support': 1852.0}} | 0.0108 | {'~PL': {'precision': 0.9808533916849015, 'recall': 0.9950055493895672, 'f1-score': 0.9878787878787879, 'support': 1802.0}, 'PL': {'precision': 0.625, 'recall': 0.3, 'f1-score': 0.40540540540540543, 'support': 50.0}, 'accuracy': 0.9762419006479481, 'macro avg': {'precision': 0.8029266958424508, 'recall': 0.6475027746947836, 'f1-score': 0.6966420966420966, 'support': 1852.0}, 'weighted avg': {'precision': 0.9712461186912487, 'recall': 0.9762419006479481, 'f1-score': 0.9721532645938693, 'support': 1852.0}} | 0.0238 | {'~TI': {'precision': 0.9785478547854786, 'recall': 0.9910863509749304, 'f1-score': 0.984777193468032, 'support': 1795.0}, 'TI': {'precision': 0.5294117647058824, 'recall': 0.3157894736842105, 'f1-score': 0.3956043956043956, 'support': 57.0}, 'accuracy': 0.9703023758099352, 'macro avg': {'precision': 0.7539798097456805, 'recall': 0.6534379123295704, 'f1-score': 0.6901907945362138, 'support': 1852.0}, 'weighted avg': {'precision': 0.9647245517970677, 'recall': 0.9703023758099352, 'f1-score': 0.9666439054128337, 'support': 1852.0}} | 0.0297 | {'~PC': {'precision': 0.9878453038674033, 'recall': 0.9791894852135816, 'f1-score': 0.9834983498349835, 'support': 1826.0}, 'PC': {'precision': 0.09523809523809523, 'recall': 0.15384615384615385, 'f1-score': 0.11764705882352941, 'support': 26.0}, 'accuracy': 0.9676025917926566, 'macro avg': {'precision': 0.5415416995527493, 'recall': 0.5665178195298677, 'f1-score': 0.5505727043292564, 'support': 1852.0}, 'weighted avg': {'precision': 0.9753141011544648, 'recall': 0.9676025917926566, 'f1-score': 0.9713427701555571, 'support': 1852.0}} | 0.0324 | {'f1-score': 0.6507958282769073, 'hamming': 0.022880669546436288} | ### Framework versions