longformer-sep_tok_full_labels

This model is a fine-tuned version of allenai/longformer-base-4096 on the essays_su_g dataset. It achieves the following results on the evaluation set:

• Loss: 0.6997
• B-claim: {'precision': 0.6735395189003437, 'recall': 0.6901408450704225, 'f1-score': 0.6817391304347826, 'support': 284.0}
• B-majorclaim: {'precision': 0.9457364341085271, 'recall': 0.8652482269503546, 'f1-score': 0.9037037037037037, 'support': 141.0}
• B-premise: {'precision': 0.8835904628330996, 'recall': 0.8898305084745762, 'f1-score': 0.8866995073891626, 'support': 708.0}
• I-claim: {'precision': 0.6694601922602909, 'recall': 0.6661761098847192, 'f1-score': 0.6678141135972462, 'support': 4077.0}
• I-majorclaim: {'precision': 0.9496166484118291, 'recall': 0.8567193675889329, 'f1-score': 0.9007792207792208, 'support': 2024.0}
• I-premise: {'precision': 0.896984318455971, 'recall': 0.9118705035971223, 'f1-score': 0.9043661572140916, 'support': 12232.0}
• O: {'precision': 0.9986007078771916, 'recall': 0.9998351738915444, 'f1-score': 0.9992175596096035, 'support': 12134.0}
• Accuracy: 0.9077
• Macro avg: {'precision': 0.8596468975496075, 'recall': 0.8399743907796676, 'f1-score': 0.8491884846754016, 'support': 31600.0}
• Weighted avg: {'precision': 0.9079291956085084, 'recall': 0.9077215189873418, 'f1-score': 0.9076388409441786, 'support': 31600.0}

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: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	B-claim	B-majorclaim	B-premise	I-claim	I-majorclaim	I-premise	O	Accuracy	Macro avg	Weighted avg
No log	1.0	81	0.3267	{'precision': 0.3333333333333333, 'recall': 0.1619718309859155, 'f1-score': 0.21800947867298578, 'support': 284.0}	{'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 141.0}	{'precision': 0.71900826446281, 'recall': 0.9830508474576272, 'f1-score': 0.8305489260143198, 'support': 708.0}	{'precision': 0.5643589102724319, 'recall': 0.5538386068187393, 'f1-score': 0.5590492696211935, 'support': 4077.0}	{'precision': 0.7205056179775281, 'recall': 0.7603754940711462, 'f1-score': 0.7399038461538461, 'support': 2024.0}	{'precision': 0.8883965205974068, 'recall': 0.8850555918901243, 'f1-score': 0.8867229093291834, 'support': 12232.0}	{'precision': 0.9961383616794018, 'recall': 0.9991758694577221, 'f1-score': 0.9976548035383666, 'support': 12134.0}	0.8699	{'precision': 0.6031058583318446, 'recall': 0.6204954629544678, 'f1-score': 0.6045556047614136, 'support': 31600.0}	{'precision': 0.8644597558999653, 'recall': 0.8699050632911393, 'f1-score': 0.8664142595402331, 'support': 31600.0}
No log	2.0	162	0.2872	{'precision': 0.6515151515151515, 'recall': 0.45422535211267606, 'f1-score': 0.5352697095435685, 'support': 284.0}	{'precision': 0.7142857142857143, 'recall': 0.851063829787234, 'f1-score': 0.7766990291262136, 'support': 141.0}	{'precision': 0.8490813648293963, 'recall': 0.9138418079096046, 'f1-score': 0.8802721088435375, 'support': 708.0}	{'precision': 0.6325869180907484, 'recall': 0.5266127054206524, 'f1-score': 0.5747557221255521, 'support': 4077.0}	{'precision': 0.6986831913245546, 'recall': 0.8913043478260869, 'f1-score': 0.7833260963960051, 'support': 2024.0}	{'precision': 0.8971377459749553, 'recall': 0.9019784172661871, 'f1-score': 0.8995515695067264, 'support': 12232.0}	{'precision': 0.9945072962780783, 'recall': 0.9997527608373167, 'f1-score': 0.9971231300345225, 'support': 12134.0}	0.8864	{'precision': 0.7768281974712284, 'recall': 0.791254174451394, 'f1-score': 0.7781424807965893, 'support': 31600.0}	{'precision': 0.8835831101628018, 'recall': 0.8864240506329114, 'f1-score': 0.8834146129726252, 'support': 31600.0}
No log	3.0	243	0.2827	{'precision': 0.6618357487922706, 'recall': 0.4823943661971831, 'f1-score': 0.5580448065173116, 'support': 284.0}	{'precision': 0.8956521739130435, 'recall': 0.7304964539007093, 'f1-score': 0.8046875, 'support': 141.0}	{'precision': 0.8300492610837439, 'recall': 0.9519774011299436, 'f1-score': 0.8868421052631579, 'support': 708.0}	{'precision': 0.6751432664756447, 'recall': 0.4623497669855286, 'f1-score': 0.5488426262920367, 'support': 4077.0}	{'precision': 0.8620689655172413, 'recall': 0.7658102766798419, 'f1-score': 0.8110936682365254, 'support': 2024.0}	{'precision': 0.854842235662756, 'recall': 0.9590418574231524, 'f1-score': 0.9039491427470623, 'support': 12232.0}	{'precision': 0.9972023368715544, 'recall': 0.9987638041865832, 'f1-score': 0.9979824597521307, 'support': 12134.0}	0.8924	{'precision': 0.825256284045179, 'recall': 0.7644048466432775, 'f1-score': 0.7873489012583177, 'support': 31600.0}	{'precision': 0.8846770016417851, 'recall': 0.892373417721519, 'f1-score': 0.88435885840807, 'support': 31600.0}
No log	4.0	324	0.2764	{'precision': 0.6165644171779141, 'recall': 0.7077464788732394, 'f1-score': 0.659016393442623, 'support': 284.0}	{'precision': 0.8136645962732919, 'recall': 0.9290780141843972, 'f1-score': 0.8675496688741722, 'support': 141.0}	{'precision': 0.9130434782608695, 'recall': 0.8305084745762712, 'f1-score': 0.8698224852071005, 'support': 708.0}	{'precision': 0.5964839710444674, 'recall': 0.70738287956831, 'f1-score': 0.6472172351885099, 'support': 4077.0}	{'precision': 0.8131966116807846, 'recall': 0.9011857707509882, 'f1-score': 0.8549332083430982, 'support': 2024.0}	{'precision': 0.9271658801531475, 'recall': 0.8512916939175932, 'f1-score': 0.8876102800153433, 'support': 12232.0}	{'precision': 0.9970394736842105, 'recall': 0.9991758694577221, 'f1-score': 0.9981065283609122, 'support': 12134.0}	0.8913	{'precision': 0.8110226326106693, 'recall': 0.8466241687612174, 'f1-score': 0.8263222570616798, 'support': 31600.0}	{'precision': 0.9004180663566287, 'recall': 0.8912974683544304, 'f1-score': 0.8943886873545748, 'support': 31600.0}
No log	5.0	405	0.2893	{'precision': 0.6763636363636364, 'recall': 0.6549295774647887, 'f1-score': 0.665474060822898, 'support': 284.0}	{'precision': 0.8657718120805369, 'recall': 0.9148936170212766, 'f1-score': 0.8896551724137931, 'support': 141.0}	{'precision': 0.8830985915492958, 'recall': 0.885593220338983, 'f1-score': 0.8843441466854725, 'support': 708.0}	{'precision': 0.6597668332143707, 'recall': 0.6801569781702232, 'f1-score': 0.6698067632850242, 'support': 4077.0}	{'precision': 0.8751828376401756, 'recall': 0.8868577075098815, 'f1-score': 0.8809815950920246, 'support': 2024.0}	{'precision': 0.9094305163539764, 'recall': 0.8956017004578156, 'f1-score': 0.9024631353488756, 'support': 12232.0}	{'precision': 0.9967121486108828, 'recall': 0.9993406955661777, 'f1-score': 0.9980246913580246, 'support': 12134.0}	0.9048	{'precision': 0.838046625116125, 'recall': 0.8453390709327352, 'f1-score': 0.8415356521437304, 'support': 31600.0}	{'precision': 0.9056611908459661, 'recall': 0.9047784810126582, 'f1-score': 0.9051715590931133, 'support': 31600.0}
No log	6.0	486	0.3353	{'precision': 0.6330935251798561, 'recall': 0.6197183098591549, 'f1-score': 0.6263345195729537, 'support': 284.0}	{'precision': 0.9230769230769231, 'recall': 0.7659574468085106, 'f1-score': 0.8372093023255814, 'support': 141.0}	{'precision': 0.8594594594594595, 'recall': 0.8983050847457628, 'f1-score': 0.8784530386740332, 'support': 708.0}	{'precision': 0.6360499070878683, 'recall': 0.5876870247731175, 'f1-score': 0.6109127995920448, 'support': 4077.0}	{'precision': 0.9126662810873337, 'recall': 0.7796442687747036, 'f1-score': 0.8409272581934453, 'support': 2024.0}	{'precision': 0.8762685402029664, 'recall': 0.9176749509483323, 'f1-score': 0.8964938902643559, 'support': 12232.0}	{'precision': 0.9976971790443293, 'recall': 0.9997527608373167, 'f1-score': 0.9987239122380934, 'support': 12134.0}	0.8940	{'precision': 0.8340445450198194, 'recall': 0.7955342638209855, 'f1-score': 0.8127221029800725, 'support': 31600.0}	{'precision': 0.891880888702747, 'recall': 0.8939873417721519, 'f1-score': 0.8922477132246446, 'support': 31600.0}
0.2608	7.0	567	0.4514	{'precision': 0.6820512820512821, 'recall': 0.46830985915492956, 'f1-score': 0.5553235908141962, 'support': 284.0}	{'precision': 0.954954954954955, 'recall': 0.75177304964539, 'f1-score': 0.8412698412698413, 'support': 141.0}	{'precision': 0.8210399032648126, 'recall': 0.9590395480225988, 'f1-score': 0.8846905537459283, 'support': 708.0}	{'precision': 0.6880088823094005, 'recall': 0.45597252882021094, 'f1-score': 0.5484584747012834, 'support': 4077.0}	{'precision': 0.9536019536019537, 'recall': 0.7717391304347826, 'f1-score': 0.8530857454942655, 'support': 2024.0}	{'precision': 0.8438103411285132, 'recall': 0.9646010464355788, 'f1-score': 0.900171657448026, 'support': 12232.0}	{'precision': 0.9982707509881423, 'recall': 0.9990934564034943, 'f1-score': 0.9986819342614713, 'support': 12134.0}	0.8943	{'precision': 0.8488197240427228, 'recall': 0.7672183741309979, 'f1-score': 0.7973831139621446, 'support': 31600.0}	{'precision': 0.8885840321741321, 'recall': 0.8943354430379746, 'f1-score': 0.8858958517067363, 'support': 31600.0}
0.2608	8.0	648	0.4097	{'precision': 0.6814814814814815, 'recall': 0.647887323943662, 'f1-score': 0.6642599277978338, 'support': 284.0}	{'precision': 0.967479674796748, 'recall': 0.8439716312056738, 'f1-score': 0.9015151515151516, 'support': 141.0}	{'precision': 0.8687415426251691, 'recall': 0.9067796610169492, 'f1-score': 0.8873531444367657, 'support': 708.0}	{'precision': 0.6823907799517556, 'recall': 0.6244787834191807, 'f1-score': 0.6521516393442622, 'support': 4077.0}	{'precision': 0.9711649365628604, 'recall': 0.8320158102766798, 'f1-score': 0.8962213943587014, 'support': 2024.0}	{'precision': 0.8831269952503309, 'recall': 0.9272400261608895, 'f1-score': 0.9046460618145563, 'support': 12232.0}	{'precision': 0.996875, 'recall': 0.9990110433492665, 'f1-score': 0.9979418786531653, 'support': 12134.0}	0.9063	{'precision': 0.8644657729526208, 'recall': 0.8259120399103289, 'f1-score': 0.8434413139886338, 'support': 31600.0}	{'precision': 0.9047867115327305, 'recall': 0.9062974683544304, 'f1-score': 0.9047924430886448, 'support': 31600.0}
0.2608	9.0	729	0.4417	{'precision': 0.686411149825784, 'recall': 0.6936619718309859, 'f1-score': 0.6900175131348512, 'support': 284.0}	{'precision': 0.9197080291970803, 'recall': 0.8936170212765957, 'f1-score': 0.9064748201438848, 'support': 141.0}	{'precision': 0.8885754583921015, 'recall': 0.8898305084745762, 'f1-score': 0.8892025405786873, 'support': 708.0}	{'precision': 0.6771096513390601, 'recall': 0.657346087809664, 'f1-score': 0.6670815183571872, 'support': 4077.0}	{'precision': 0.9159268929503916, 'recall': 0.866600790513834, 'f1-score': 0.8905813658288906, 'support': 2024.0}	{'precision': 0.8978524893428779, 'recall': 0.9126062786134729, 'f1-score': 0.9051692681937971, 'support': 12232.0}	{'precision': 0.9976153276868679, 'recall': 0.9998351738915444, 'f1-score': 0.9987240172875077, 'support': 12134.0}	0.9077	{'precision': 0.8547427141048803, 'recall': 0.8447854046300962, 'f1-score': 0.849607291932115, 'support': 31600.0}	{'precision': 0.9068271879381139, 'recall': 0.9076582278481012, 'f1-score': 0.9071553503542205, 'support': 31600.0}
0.2608	10.0	810	0.4593	{'precision': 0.6834532374100719, 'recall': 0.6690140845070423, 'f1-score': 0.6761565836298933, 'support': 284.0}	{'precision': 0.9104477611940298, 'recall': 0.8652482269503546, 'f1-score': 0.8872727272727273, 'support': 141.0}	{'precision': 0.8821081830790569, 'recall': 0.8983050847457628, 'f1-score': 0.8901329601119664, 'support': 708.0}	{'precision': 0.6705637828007275, 'recall': 0.6330635271032622, 'f1-score': 0.6512742871561948, 'support': 4077.0}	{'precision': 0.9037947621592731, 'recall': 0.8354743083003953, 'f1-score': 0.8682926829268293, 'support': 2024.0}	{'precision': 0.8933428775948461, 'recall': 0.9182472204054938, 'f1-score': 0.905623866156017, 'support': 12232.0}	{'precision': 0.9965500246426812, 'recall': 0.9998351738915444, 'f1-score': 0.9981898963304262, 'support': 12134.0}	0.9046	{'precision': 0.8486086612686695, 'recall': 0.8313125179862652, 'f1-score': 0.8395632862262934, 'support': 31600.0}	{'precision': 0.9028380907030437, 'recall': 0.9045569620253164, 'f1-score': 0.9034697801243392, 'support': 31600.0}
0.2608	11.0	891	0.5346	{'precision': 0.7142857142857143, 'recall': 0.5809859154929577, 'f1-score': 0.6407766990291263, 'support': 284.0}	{'precision': 0.9130434782608695, 'recall': 0.8936170212765957, 'f1-score': 0.9032258064516129, 'support': 141.0}	{'precision': 0.8547120418848168, 'recall': 0.922316384180791, 'f1-score': 0.8872282608695653, 'support': 708.0}	{'precision': 0.7111412123264477, 'recall': 0.515084621044886, 'f1-score': 0.5974395448079659, 'support': 4077.0}	{'precision': 0.8927318295739348, 'recall': 0.8799407114624506, 'f1-score': 0.8862901219208758, 'support': 2024.0}	{'precision': 0.862670258943272, 'recall': 0.9423642903858731, 'f1-score': 0.9007579901539423, 'support': 12232.0}	{'precision': 0.9980258287406433, 'recall': 0.9999175869457723, 'f1-score': 0.9989708122349842, 'support': 12134.0}	0.9014	{'precision': 0.8495157662879569, 'recall': 0.8191752186841895, 'f1-score': 0.8306698907811532, 'support': 31600.0}	{'precision': 0.8957333024681017, 'recall': 0.9014240506329114, 'f1-score': 0.8957812921551218, 'support': 31600.0}
0.2608	12.0	972	0.6067	{'precision': 0.6622950819672131, 'recall': 0.7112676056338029, 'f1-score': 0.6859083191850596, 'support': 284.0}	{'precision': 0.9375, 'recall': 0.851063829787234, 'f1-score': 0.8921933085501859, 'support': 141.0}	{'precision': 0.8914285714285715, 'recall': 0.8813559322033898, 'f1-score': 0.8863636363636365, 'support': 708.0}	{'precision': 0.6508319266939957, 'recall': 0.6620063772381654, 'f1-score': 0.6563715953307394, 'support': 4077.0}	{'precision': 0.9370034052213394, 'recall': 0.8157114624505929, 'f1-score': 0.8721605916534602, 'support': 2024.0}	{'precision': 0.8954670108081949, 'recall': 0.907619359058208, 'f1-score': 0.9015022330491272, 'support': 12232.0}	{'precision': 0.9977796052631579, 'recall': 0.9999175869457723, 'f1-score': 0.9988474520457726, 'support': 12134.0}	0.9029	{'precision': 0.8531865144832105, 'recall': 0.8327060219024521, 'f1-score': 0.8419067337397116, 'support': 31600.0}	{'precision': 0.9038530884689406, 'recall': 0.902879746835443, 'f1-score': 0.9030573735174033, 'support': 31600.0}
0.0322	13.0	1053	0.5914	{'precision': 0.7125984251968503, 'recall': 0.6373239436619719, 'f1-score': 0.6728624535315986, 'support': 284.0}	{'precision': 0.9090909090909091, 'recall': 0.9219858156028369, 'f1-score': 0.9154929577464789, 'support': 141.0}	{'precision': 0.873641304347826, 'recall': 0.9081920903954802, 'f1-score': 0.8905817174515235, 'support': 708.0}	{'precision': 0.6932808546527973, 'recall': 0.6048565121412803, 'f1-score': 0.6460571129159025, 'support': 4077.0}	{'precision': 0.905688622754491, 'recall': 0.8967391304347826, 'f1-score': 0.9011916583912611, 'support': 2024.0}	{'precision': 0.8856001879257693, 'recall': 0.9246239372138653, 'f1-score': 0.9046914370275567, 'support': 12232.0}	{'precision': 0.9990935311083642, 'recall': 0.9991758694577221, 'f1-score': 0.9991346985866744, 'support': 12134.0}	0.9072	{'precision': 0.8541419764395725, 'recall': 0.8418424712725627, 'f1-score': 0.8471445765215709, 'support': 31600.0}	{'precision': 0.9039360771033997, 'recall': 0.907246835443038, 'f1-score': 0.9050120935479347, 'support': 31600.0}
0.0322	14.0	1134	0.6610	{'precision': 0.7283950617283951, 'recall': 0.6232394366197183, 'f1-score': 0.6717267552182163, 'support': 284.0}	{'precision': 0.927536231884058, 'recall': 0.9078014184397163, 'f1-score': 0.9175627240143368, 'support': 141.0}	{'precision': 0.8656914893617021, 'recall': 0.9194915254237288, 'f1-score': 0.8917808219178082, 'support': 708.0}	{'precision': 0.7092882991556092, 'recall': 0.5768947755702722, 'f1-score': 0.6362775598539159, 'support': 4077.0}	{'precision': 0.9176531137416366, 'recall': 0.8809288537549407, 'f1-score': 0.8989160574741618, 'support': 2024.0}	{'precision': 0.8762918165811835, 'recall': 0.9358240680183126, 'f1-score': 0.9050800553469064, 'support': 12232.0}	{'precision': 0.9989296006587073, 'recall': 0.9998351738915444, 'f1-score': 0.9993821821327072, 'support': 12134.0}	0.9073	{'precision': 0.8605408018730417, 'recall': 0.8348593216740333, 'f1-score': 0.8458180222797218, 'support': 31600.0}	{'precision': 0.9031477200436355, 'recall': 0.9072784810126582, 'f1-score': 0.9038759465613782, 'support': 31600.0}
0.0322	15.0	1215	0.6557	{'precision': 0.6868686868686869, 'recall': 0.7183098591549296, 'f1-score': 0.70223752151463, 'support': 284.0}	{'precision': 0.9197080291970803, 'recall': 0.8936170212765957, 'f1-score': 0.9064748201438848, 'support': 141.0}	{'precision': 0.8955650929899857, 'recall': 0.884180790960452, 'f1-score': 0.8898365316275765, 'support': 708.0}	{'precision': 0.6798825256975036, 'recall': 0.681383370125092, 'f1-score': 0.6806321205439176, 'support': 4077.0}	{'precision': 0.9241952232606438, 'recall': 0.8794466403162056, 'f1-score': 0.9012658227848102, 'support': 2024.0}	{'precision': 0.9036790384146837, 'recall': 0.9096631785480707, 'f1-score': 0.906661234467305, 'support': 12232.0}	{'precision': 0.9991764124526438, 'recall': 0.9998351738915444, 'f1-score': 0.9995056846267919, 'support': 12134.0}	0.9105	{'precision': 0.8584392869830325, 'recall': 0.8523480048961273, 'f1-score': 0.8552305336727023, 'support': 31600.0}	{'precision': 0.910730075973464, 'recall': 0.9105379746835442, 'f1-score': 0.9105896850690615, 'support': 31600.0}
0.0322	16.0	1296	0.6791	{'precision': 0.6896551724137931, 'recall': 0.6338028169014085, 'f1-score': 0.6605504587155964, 'support': 284.0}	{'precision': 0.9453125, 'recall': 0.8581560283687943, 'f1-score': 0.8996282527881041, 'support': 141.0}	{'precision': 0.8669354838709677, 'recall': 0.9110169491525424, 'f1-score': 0.8884297520661157, 'support': 708.0}	{'precision': 0.6769836803601575, 'recall': 0.5901398086828551, 'f1-score': 0.6305857685755472, 'support': 4077.0}	{'precision': 0.9421308815575987, 'recall': 0.8606719367588933, 'f1-score': 0.8995610637748515, 'support': 2024.0}	{'precision': 0.8771861940876026, 'recall': 0.9266677567037279, 'f1-score': 0.9012483104078874, 'support': 12232.0}	{'precision': 0.9991764124526438, 'recall': 0.9998351738915444, 'f1-score': 0.9995056846267919, 'support': 12134.0}	0.9038	{'precision': 0.8567686178203948, 'recall': 0.8257557814942523, 'f1-score': 0.8399298987078421, 'support': 31600.0}	{'precision': 0.9007476246179443, 'recall': 0.9038291139240506, 'f1-score': 0.9014915588643904, 'support': 31600.0}
0.0322	17.0	1377	0.6997	{'precision': 0.6735395189003437, 'recall': 0.6901408450704225, 'f1-score': 0.6817391304347826, 'support': 284.0}	{'precision': 0.952755905511811, 'recall': 0.8581560283687943, 'f1-score': 0.9029850746268657, 'support': 141.0}	{'precision': 0.8839160839160839, 'recall': 0.8926553672316384, 'f1-score': 0.8882642304989459, 'support': 708.0}	{'precision': 0.6603307825228338, 'recall': 0.6561196958547952, 'f1-score': 0.6582185039370079, 'support': 4077.0}	{'precision': 0.946725860155383, 'recall': 0.8428853754940712, 'f1-score': 0.8917929952953477, 'support': 2024.0}	{'precision': 0.8941922027915932, 'recall': 0.9112982341399608, 'f1-score': 0.902664183334683, 'support': 12232.0}	{'precision': 0.9986829107672045, 'recall': 0.9998351738915444, 'f1-score': 0.9992587101556709, 'support': 12134.0}	0.9053	{'precision': 0.8585918949378932, 'recall': 0.8358701028644611, 'f1-score': 0.8464175468976148, 'support': 31600.0}	{'precision': 0.905555556916252, 'recall': 0.9053481012658228, 'f1-score': 0.9052140894419886, 'support': 31600.0}
0.0322	18.0	1458	0.7011	{'precision': 0.6818181818181818, 'recall': 0.6866197183098591, 'f1-score': 0.6842105263157894, 'support': 284.0}	{'precision': 0.946969696969697, 'recall': 0.8865248226950354, 'f1-score': 0.9157509157509157, 'support': 141.0}	{'precision': 0.8825174825174825, 'recall': 0.8912429378531074, 'f1-score': 0.8868587491215741, 'support': 708.0}	{'precision': 0.6766766766766766, 'recall': 0.6632327691930341, 'f1-score': 0.6698872785829307, 'support': 4077.0}	{'precision': 0.9471698113207547, 'recall': 0.8680830039525692, 'f1-score': 0.9059035833977829, 'support': 2024.0}	{'precision': 0.8964162591196986, 'recall': 0.9140778286461739, 'f1-score': 0.9051608986035214, 'support': 12232.0}	{'precision': 0.9990941283043729, 'recall': 0.9998351738915444, 'f1-score': 0.9994645137372822, 'support': 12134.0}	0.9090	{'precision': 0.8615231766752662, 'recall': 0.8442308935059034, 'f1-score': 0.8524623522156853, 'support': 31600.0}	{'precision': 0.90872898138775, 'recall': 0.9090189873417721, 'f1-score': 0.9087165339227473, 'support': 31600.0}
0.0055	19.0	1539	0.7171	{'precision': 0.6834532374100719, 'recall': 0.6690140845070423, 'f1-score': 0.6761565836298933, 'support': 284.0}	{'precision': 0.9586776859504132, 'recall': 0.8226950354609929, 'f1-score': 0.8854961832061068, 'support': 141.0}	{'precision': 0.8760217983651226, 'recall': 0.9081920903954802, 'f1-score': 0.8918169209431346, 'support': 708.0}	{'precision': 0.6699947451392538, 'recall': 0.6254598969830758, 'f1-score': 0.6469618165672967, 'support': 4077.0}	{'precision': 0.9521889400921659, 'recall': 0.816699604743083, 'f1-score': 0.8792553191489363, 'support': 2024.0}	{'precision': 0.8853498200031303, 'recall': 0.9248691955526488, 'f1-score': 0.9046781287485005, 'support': 12232.0}	{'precision': 0.9987651271918992, 'recall': 0.9998351738915444, 'f1-score': 0.9992998640912648, 'support': 12134.0}	0.9050	{'precision': 0.8606359077360082, 'recall': 0.8238235830762669, 'f1-score': 0.8405235451907334, 'support': 31600.0}	{'precision': 0.9036997388825967, 'recall': 0.9049683544303797, 'f1-score': 0.9037054849825339, 'support': 31600.0}
0.0055	20.0	1620	0.6997	{'precision': 0.6735395189003437, 'recall': 0.6901408450704225, 'f1-score': 0.6817391304347826, 'support': 284.0}	{'precision': 0.9457364341085271, 'recall': 0.8652482269503546, 'f1-score': 0.9037037037037037, 'support': 141.0}	{'precision': 0.8835904628330996, 'recall': 0.8898305084745762, 'f1-score': 0.8866995073891626, 'support': 708.0}	{'precision': 0.6694601922602909, 'recall': 0.6661761098847192, 'f1-score': 0.6678141135972462, 'support': 4077.0}	{'precision': 0.9496166484118291, 'recall': 0.8567193675889329, 'f1-score': 0.9007792207792208, 'support': 2024.0}	{'precision': 0.896984318455971, 'recall': 0.9118705035971223, 'f1-score': 0.9043661572140916, 'support': 12232.0}	{'precision': 0.9986007078771916, 'recall': 0.9998351738915444, 'f1-score': 0.9992175596096035, 'support': 12134.0}	0.9077	{'precision': 0.8596468975496075, 'recall': 0.8399743907796676, 'f1-score': 0.8491884846754016, 'support': 31600.0}	{'precision': 0.9079291956085084, 'recall': 0.9077215189873418, 'f1-score': 0.9076388409441786, 'support': 31600.0}

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2