longformer-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: 1.0525
• B-claim: {'precision': 0.5714285714285714, 'recall': 0.5915492957746479, 'f1-score': 0.5813148788927336, 'support': 284.0}
• B-majorclaim: {'precision': 0.7328767123287672, 'recall': 0.7588652482269503, 'f1-score': 0.7456445993031359, 'support': 141.0}
• B-premise: {'precision': 0.7592592592592593, 'recall': 0.8107344632768362, 'f1-score': 0.7841530054644807, 'support': 708.0}
• I-claim: {'precision': 0.5995872033023736, 'recall': 0.5700269806230072, 'f1-score': 0.5844335470891487, 'support': 4077.0}
• I-majorclaim: {'precision': 0.7741293532338308, 'recall': 0.7687747035573123, 'f1-score': 0.7714427367377293, 'support': 2024.0}
• I-premise: {'precision': 0.8661675245671502, 'recall': 0.907946370176586, 'f1-score': 0.8865650195577552, 'support': 12232.0}
• O: {'precision': 0.9227995758218451, 'recall': 0.8818402918524524, 'f1-score': 0.9018551145196393, 'support': 9868.0}
• Accuracy: 0.8365
• Macro avg: {'precision': 0.746606885705971, 'recall': 0.7556767647839704, 'f1-score': 0.7507727002235176, 'support': 29334.0}
• Weighted avg: {'precision': 0.8357427933389249, 'recall': 0.8364696256903252, 'f1-score': 0.8356690155425791, 'support': 29334.0}

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	0.6443	{'precision': 0.5, 'recall': 0.0035211267605633804, 'f1-score': 0.006993006993006993, 'support': 284.0}	{'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 141.0}	{'precision': 0.5883777239709443, 'recall': 0.6864406779661016, 'f1-score': 0.6336375488917861, 'support': 708.0}	{'precision': 0.41618672324946954, 'recall': 0.3367672308069659, 'f1-score': 0.37228850325379614, 'support': 4077.0}	{'precision': 0.5611921369689283, 'recall': 0.43725296442687744, 'f1-score': 0.49153013051930017, 'support': 2024.0}	{'precision': 0.7746890504995582, 'recall': 0.9318181818181818, 'f1-score': 0.846019669697532, 'support': 12232.0}	{'precision': 0.9111808904340025, 'recall': 0.8233684637211187, 'f1-score': 0.8650519031141869, 'support': 9868.0}	0.7591	{'precision': 0.535946646446129, 'recall': 0.4598812350714013, 'f1-score': 0.4593601089242298, 'support': 29334.0}	{'precision': 0.7451676238152983, 'recall': 0.7591191109292971, 'f1-score': 0.7448054609057474, 'support': 29334.0}
No log	2.0	162	0.5139	{'precision': 0.4420731707317073, 'recall': 0.5105633802816901, 'f1-score': 0.47385620915032683, 'support': 284.0}	{'precision': 0.6274509803921569, 'recall': 0.45390070921985815, 'f1-score': 0.5267489711934156, 'support': 141.0}	{'precision': 0.7261306532663316, 'recall': 0.8163841807909604, 'f1-score': 0.7686170212765958, 'support': 708.0}	{'precision': 0.5221008840353614, 'recall': 0.49251900907530044, 'f1-score': 0.5068787075602675, 'support': 4077.0}	{'precision': 0.5741007194244604, 'recall': 0.7885375494071146, 'f1-score': 0.6644462947543713, 'support': 2024.0}	{'precision': 0.8642982877260361, 'recall': 0.8830935251798561, 'f1-score': 0.8735948241002829, 'support': 12232.0}	{'precision': 0.925979519145147, 'recall': 0.8430279691933522, 'f1-score': 0.8825588796944621, 'support': 9868.0}	0.8015	{'precision': 0.668876316388743, 'recall': 0.6840037604497332, 'f1-score': 0.6709572725328175, 'support': 29334.0}	{'precision': 0.8089032379475054, 'recall': 0.8015272380173177, 'f1-score': 0.8031401896750007, 'support': 29334.0}
No log	3.0	243	0.5770	{'precision': 0.4393939393939394, 'recall': 0.4084507042253521, 'f1-score': 0.4233576642335767, 'support': 284.0}	{'precision': 0.7181818181818181, 'recall': 0.5602836879432624, 'f1-score': 0.6294820717131473, 'support': 141.0}	{'precision': 0.6709816612729234, 'recall': 0.8785310734463276, 'f1-score': 0.7608562691131499, 'support': 708.0}	{'precision': 0.5186211141889813, 'recall': 0.41329408879077756, 'f1-score': 0.46000546000546, 'support': 4077.0}	{'precision': 0.7556615017878426, 'recall': 0.6264822134387352, 'f1-score': 0.6850351161534306, 'support': 2024.0}	{'precision': 0.7999862438957287, 'recall': 0.9508665794637018, 'f1-score': 0.8689253296477533, 'support': 12232.0}	{'precision': 0.9404692424419283, 'recall': 0.8164775030401297, 'f1-score': 0.8740981828044481, 'support': 9868.0}	0.7997	{'precision': 0.6918993601661659, 'recall': 0.6649122643354695, 'f1-score': 0.6716800133815666, 'support': 29334.0}	{'precision': 0.7980829724295806, 'recall': 0.7996863707643008, 'f1-score': 0.7930703491848509, 'support': 29334.0}
No log	4.0	324	0.5089	{'precision': 0.4666666666666667, 'recall': 0.6654929577464789, 'f1-score': 0.5486211901306242, 'support': 284.0}	{'precision': 0.6477987421383647, 'recall': 0.7304964539007093, 'f1-score': 0.6866666666666668, 'support': 141.0}	{'precision': 0.7981366459627329, 'recall': 0.7259887005649718, 'f1-score': 0.7603550295857988, 'support': 708.0}	{'precision': 0.5201636469900643, 'recall': 0.6548933038999264, 'f1-score': 0.5798045602605862, 'support': 4077.0}	{'precision': 0.7390321121664405, 'recall': 0.8073122529644269, 'f1-score': 0.7716646989374262, 'support': 2024.0}	{'precision': 0.899807994414383, 'recall': 0.842871157619359, 'f1-score': 0.8704094554664417, 'support': 12232.0}	{'precision': 0.9231016731016731, 'recall': 0.8722132144304824, 'f1-score': 0.8969362234264276, 'support': 9868.0}	0.8191	{'precision': 0.7135296402057607, 'recall': 0.7570382915894793, 'f1-score': 0.7306368320677102, 'support': 29334.0}	{'precision': 0.835926930625345, 'recall': 0.8190836571896093, 'f1-score': 0.825475128990697, 'support': 29334.0}
No log	5.0	405	0.5750	{'precision': 0.5029585798816568, 'recall': 0.5985915492957746, 'f1-score': 0.5466237942122186, 'support': 284.0}	{'precision': 0.728, 'recall': 0.6453900709219859, 'f1-score': 0.6842105263157895, 'support': 141.0}	{'precision': 0.7608695652173914, 'recall': 0.7909604519774012, 'f1-score': 0.775623268698061, 'support': 708.0}	{'precision': 0.5492530345471522, 'recall': 0.577140053961246, 'f1-score': 0.5628513335725392, 'support': 4077.0}	{'precision': 0.8153946510110893, 'recall': 0.6175889328063241, 'f1-score': 0.7028394714647174, 'support': 2024.0}	{'precision': 0.8660855784469097, 'recall': 0.8935578809679529, 'f1-score': 0.8796072750684049, 'support': 12232.0}	{'precision': 0.9043101670447515, 'recall': 0.8887312525334414, 'f1-score': 0.8964530307676581, 'support': 9868.0}	0.8224	{'precision': 0.7324102251641358, 'recall': 0.715994313209161, 'f1-score': 0.7211726714427698, 'support': 29334.0}	{'precision': 0.8246928072651426, 'recall': 0.8223904002181769, 'f1-score': 0.8223802682715222, 'support': 29334.0}
No log	6.0	486	0.5503	{'precision': 0.5160349854227405, 'recall': 0.6232394366197183, 'f1-score': 0.5645933014354066, 'support': 284.0}	{'precision': 0.6923076923076923, 'recall': 0.7659574468085106, 'f1-score': 0.7272727272727273, 'support': 141.0}	{'precision': 0.7780859916782247, 'recall': 0.7923728813559322, 'f1-score': 0.7851644506648006, 'support': 708.0}	{'precision': 0.5575316048853654, 'recall': 0.6382143733137111, 'f1-score': 0.5951509606587375, 'support': 4077.0}	{'precision': 0.7698019801980198, 'recall': 0.7682806324110671, 'f1-score': 0.7690405539070228, 'support': 2024.0}	{'precision': 0.8899397388684298, 'recall': 0.8692773054283846, 'f1-score': 0.8794871794871795, 'support': 12232.0}	{'precision': 0.9260470513767275, 'recall': 0.8895419537900284, 'f1-score': 0.907427508140797, 'support': 9868.0}	0.8323	{'precision': 0.7328212921053143, 'recall': 0.763840575675336, 'f1-score': 0.7468766687952387, 'support': 29334.0}	{'precision': 0.8403274341189826, 'recall': 0.8322765391695643, 'f1-score': 0.835690214793681, 'support': 29334.0}
0.4181	7.0	567	0.6419	{'precision': 0.5571428571428572, 'recall': 0.5492957746478874, 'f1-score': 0.5531914893617021, 'support': 284.0}	{'precision': 0.7152777777777778, 'recall': 0.7304964539007093, 'f1-score': 0.7228070175438596, 'support': 141.0}	{'precision': 0.7544529262086515, 'recall': 0.8375706214689266, 'f1-score': 0.7938420348058902, 'support': 708.0}	{'precision': 0.6019025655808591, 'recall': 0.5121412803532008, 'f1-score': 0.5534057778955738, 'support': 4077.0}	{'precision': 0.8124655267512411, 'recall': 0.7277667984189723, 'f1-score': 0.7677873338545738, 'support': 2024.0}	{'precision': 0.855129565085619, 'recall': 0.9226618705035972, 'f1-score': 0.8876130554463233, 'support': 12232.0}	{'precision': 0.9203649937785151, 'recall': 0.8994730441832185, 'f1-score': 0.9097990979909799, 'support': 9868.0}	0.8378	{'precision': 0.7452480303322171, 'recall': 0.7399151204966445, 'f1-score': 0.7412065438427005, 'support': 29334.0}	{'precision': 0.8329491032454597, 'recall': 0.8377650507943001, 'f1-score': 0.8340655773672634, 'support': 29334.0}
0.4181	8.0	648	0.6668	{'precision': 0.5745454545454546, 'recall': 0.5563380281690141, 'f1-score': 0.5652951699463328, 'support': 284.0}	{'precision': 0.7027027027027027, 'recall': 0.7375886524822695, 'f1-score': 0.7197231833910034, 'support': 141.0}	{'precision': 0.7538071065989848, 'recall': 0.8389830508474576, 'f1-score': 0.7941176470588234, 'support': 708.0}	{'precision': 0.6235260281852172, 'recall': 0.5317635516311013, 'f1-score': 0.5740005295207837, 'support': 4077.0}	{'precision': 0.8115154807170016, 'recall': 0.7381422924901185, 'f1-score': 0.773091849935317, 'support': 2024.0}	{'precision': 0.8614178024822965, 'recall': 0.9248691955526488, 'f1-score': 0.8920165582495565, 'support': 12232.0}	{'precision': 0.9189412737799835, 'recall': 0.9006890960680989, 'f1-score': 0.9097236438075741, 'support': 9868.0}	0.8427	{'precision': 0.7494936927159488, 'recall': 0.7469105524629585, 'f1-score': 0.7468526545584844, 'support': 29334.0}	{'precision': 0.8381245456177384, 'recall': 0.8426740301356788, 'f1-score': 0.8392138000943469, 'support': 29334.0}
0.4181	9.0	729	0.7192	{'precision': 0.5454545454545454, 'recall': 0.6338028169014085, 'f1-score': 0.5863192182410424, 'support': 284.0}	{'precision': 0.6928104575163399, 'recall': 0.75177304964539, 'f1-score': 0.7210884353741497, 'support': 141.0}	{'precision': 0.7757404795486601, 'recall': 0.7768361581920904, 'f1-score': 0.7762879322512349, 'support': 708.0}	{'precision': 0.5975181456333412, 'recall': 0.6259504537650233, 'f1-score': 0.6114039290848108, 'support': 4077.0}	{'precision': 0.7642474427666829, 'recall': 0.775197628458498, 'f1-score': 0.7696835908756438, 'support': 2024.0}	{'precision': 0.893157763146929, 'recall': 0.8761445389143231, 'f1-score': 0.8845693533077462, 'support': 12232.0}	{'precision': 0.9098686220592729, 'recall': 0.9053506282934739, 'f1-score': 0.9076040026413369, 'support': 9868.0}	0.8389	{'precision': 0.7398282080179673, 'recall': 0.7635793248814581, 'f1-score': 0.7509937802537092, 'support': 29334.0}	{'precision': 0.8416318009865815, 'recall': 0.8388900252266994, 'f1-score': 0.8401384747371046, 'support': 29334.0}
0.4181	10.0	810	0.8728	{'precision': 0.5584905660377358, 'recall': 0.5211267605633803, 'f1-score': 0.5391621129326047, 'support': 284.0}	{'precision': 0.6948051948051948, 'recall': 0.7588652482269503, 'f1-score': 0.7254237288135594, 'support': 141.0}	{'precision': 0.7503201024327785, 'recall': 0.827683615819209, 'f1-score': 0.7871054398925452, 'support': 708.0}	{'precision': 0.5859070464767616, 'recall': 0.4792739759627177, 'f1-score': 0.5272531030760929, 'support': 4077.0}	{'precision': 0.7485322896281801, 'recall': 0.7559288537549407, 'f1-score': 0.7522123893805309, 'support': 2024.0}	{'precision': 0.8385786052009456, 'recall': 0.92797580117724, 'f1-score': 0.8810152126668737, 'support': 12232.0}	{'precision': 0.9320967566981234, 'recall': 0.8707944872314552, 'f1-score': 0.9004034159375491, 'support': 9868.0}	0.8273	{'precision': 0.7298186516113886, 'recall': 0.7345212489622704, 'f1-score': 0.7303679146713938, 'support': 29334.0}	{'precision': 0.8231745470223255, 'recall': 0.8273334696938706, 'f1-score': 0.8231582874630071, 'support': 29334.0}
0.4181	11.0	891	0.7904	{'precision': 0.5487804878048781, 'recall': 0.6338028169014085, 'f1-score': 0.5882352941176471, 'support': 284.0}	{'precision': 0.6956521739130435, 'recall': 0.7943262411347518, 'f1-score': 0.7417218543046358, 'support': 141.0}	{'precision': 0.7777777777777778, 'recall': 0.7810734463276836, 'f1-score': 0.7794221282593374, 'support': 708.0}	{'precision': 0.600095785440613, 'recall': 0.6146676477802305, 'f1-score': 0.6072943172179812, 'support': 4077.0}	{'precision': 0.7808219178082192, 'recall': 0.7885375494071146, 'f1-score': 0.7846607669616519, 'support': 2024.0}	{'precision': 0.8951898734177215, 'recall': 0.8672334859385219, 'f1-score': 0.8809899510007474, 'support': 12232.0}	{'precision': 0.8980524642289348, 'recall': 0.9158897446291042, 'f1-score': 0.9068834035721453, 'support': 9868.0}	0.8384	{'precision': 0.742338640055884, 'recall': 0.7707901331598307, 'f1-score': 0.755601102204878, 'support': 29334.0}	{'precision': 0.8401010980182351, 'recall': 0.8383786732119725, 'f1-score': 0.8390590885154817, 'support': 29334.0}
0.4181	12.0	972	0.9021	{'precision': 0.5766423357664233, 'recall': 0.5563380281690141, 'f1-score': 0.5663082437275986, 'support': 284.0}	{'precision': 0.7272727272727273, 'recall': 0.7375886524822695, 'f1-score': 0.7323943661971831, 'support': 141.0}	{'precision': 0.7567221510883483, 'recall': 0.8347457627118644, 'f1-score': 0.793821356615178, 'support': 708.0}	{'precision': 0.6302699423718532, 'recall': 0.5096884964434634, 'f1-score': 0.5636018443178736, 'support': 4077.0}	{'precision': 0.7813152400835073, 'recall': 0.7396245059288538, 'f1-score': 0.7598984771573604, 'support': 2024.0}	{'precision': 0.8537686174213931, 'recall': 0.9278940483976456, 'f1-score': 0.889289352033221, 'support': 12232.0}	{'precision': 0.9143213210094506, 'recall': 0.892176732873936, 'f1-score': 0.9031132994819715, 'support': 9868.0}	0.8380	{'precision': 0.7486160478591003, 'recall': 0.7425794610010066, 'f1-score': 0.7440609913614838, 'support': 29334.0}	{'precision': 0.8324430451309904, 'recall': 0.838003681734506, 'f1-score': 0.8335608269497821, 'support': 29334.0}
0.0774	13.0	1053	0.9174	{'precision': 0.5379939209726444, 'recall': 0.6232394366197183, 'f1-score': 0.5774877650897227, 'support': 284.0}	{'precision': 0.7013888888888888, 'recall': 0.7163120567375887, 'f1-score': 0.7087719298245613, 'support': 141.0}	{'precision': 0.7626666666666667, 'recall': 0.807909604519774, 'f1-score': 0.784636488340192, 'support': 708.0}	{'precision': 0.5750291715285881, 'recall': 0.6043659553593328, 'f1-score': 0.5893326955273857, 'support': 4077.0}	{'precision': 0.7868589743589743, 'recall': 0.7277667984189723, 'f1-score': 0.7561601642710472, 'support': 2024.0}	{'precision': 0.8721798538290435, 'recall': 0.8975637671680837, 'f1-score': 0.8846897663174859, 'support': 12232.0}	{'precision': 0.9202434336963485, 'recall': 0.8734292663153628, 'f1-score': 0.8962254341270668, 'support': 9868.0}	0.8313	{'precision': 0.7366229871344505, 'recall': 0.7500838407341189, 'f1-score': 0.7424720347853516, 'support': 29334.0}	{'precision': 0.8344622887797986, 'recall': 0.8312879252744256, 'f1-score': 0.8324170375280131, 'support': 29334.0}
0.0774	14.0	1134	0.9774	{'precision': 0.5398773006134969, 'recall': 0.6197183098591549, 'f1-score': 0.5770491803278688, 'support': 284.0}	{'precision': 0.6871165644171779, 'recall': 0.7943262411347518, 'f1-score': 0.736842105263158, 'support': 141.0}	{'precision': 0.7735334242837654, 'recall': 0.8008474576271186, 'f1-score': 0.7869535045107564, 'support': 708.0}	{'precision': 0.5810174281676872, 'recall': 0.6051017905322541, 'f1-score': 0.5928150907124834, 'support': 4077.0}	{'precision': 0.7494387067804221, 'recall': 0.8246047430830039, 'f1-score': 0.7852270054104916, 'support': 2024.0}	{'precision': 0.8794297680412371, 'recall': 0.8926586003924133, 'f1-score': 0.8859948068808828, 'support': 12232.0}	{'precision': 0.9270302504608046, 'recall': 0.8664369679773004, 'f1-score': 0.8957100204284741, 'support': 9868.0}	0.8338	{'precision': 0.733920491823513, 'recall': 0.7719563015151424, 'f1-score': 0.751513101933445, 'support': 29334.0}	{'precision': 0.8382307794620859, 'recall': 0.8338446853480602, 'f1-score': 0.835464012013009, 'support': 29334.0}
0.0774	15.0	1215	0.9720	{'precision': 0.5487804878048781, 'recall': 0.6338028169014085, 'f1-score': 0.5882352941176471, 'support': 284.0}	{'precision': 0.7445255474452555, 'recall': 0.723404255319149, 'f1-score': 0.7338129496402878, 'support': 141.0}	{'precision': 0.7593582887700535, 'recall': 0.8022598870056498, 'f1-score': 0.7802197802197803, 'support': 708.0}	{'precision': 0.570828729281768, 'recall': 0.6335540838852097, 'f1-score': 0.6005580097651709, 'support': 4077.0}	{'precision': 0.7954422137818774, 'recall': 0.724308300395257, 'f1-score': 0.7582104990949057, 'support': 2024.0}	{'precision': 0.8803978651140223, 'recall': 0.8900425114453892, 'f1-score': 0.885193918204732, 'support': 12232.0}	{'precision': 0.9188239054010866, 'recall': 0.874037292257803, 'f1-score': 0.8958712022851208, 'support': 9868.0}	0.8322	{'precision': 0.7454510053712774, 'recall': 0.7544870210299808, 'f1-score': 0.748871664761092, 'support': 29334.0}	{'precision': 0.8376519459918353, 'recall': 0.8321742687666189, 'f1-score': 0.8343275428320325, 'support': 29334.0}
0.0774	16.0	1296	1.0037	{'precision': 0.5662251655629139, 'recall': 0.602112676056338, 'f1-score': 0.5836177474402731, 'support': 284.0}	{'precision': 0.7094594594594594, 'recall': 0.7446808510638298, 'f1-score': 0.726643598615917, 'support': 141.0}	{'precision': 0.766042780748663, 'recall': 0.809322033898305, 'f1-score': 0.7870879120879121, 'support': 708.0}	{'precision': 0.5981858298602599, 'recall': 0.5984792739759627, 'f1-score': 0.5983325159391859, 'support': 4077.0}	{'precision': 0.7981220657276995, 'recall': 0.7559288537549407, 'f1-score': 0.7764526769855367, 'support': 2024.0}	{'precision': 0.8736565560066873, 'recall': 0.8971550032701112, 'f1-score': 0.885249868914613, 'support': 12232.0}	{'precision': 0.9181542958555173, 'recall': 0.8912646939602756, 'f1-score': 0.9045096930117758, 'support': 9868.0}	0.8382	{'precision': 0.7471208790316002, 'recall': 0.7569919122828231, 'f1-score': 0.751699144713602, 'support': 29334.0}	{'precision': 0.8387644471781172, 'recall': 0.8382082225403968, 'f1-score': 0.838292846606077, 'support': 29334.0}
0.0774	17.0	1377	1.0845	{'precision': 0.5382165605095541, 'recall': 0.5950704225352113, 'f1-score': 0.5652173913043479, 'support': 284.0}	{'precision': 0.7163120567375887, 'recall': 0.7163120567375887, 'f1-score': 0.7163120567375887, 'support': 141.0}	{'precision': 0.7509627727856226, 'recall': 0.826271186440678, 'f1-score': 0.7868190988567586, 'support': 708.0}	{'precision': 0.5689655172413793, 'recall': 0.5827814569536424, 'f1-score': 0.5757906215921483, 'support': 4077.0}	{'precision': 0.7852169255490091, 'recall': 0.724308300395257, 'f1-score': 0.7535337959393473, 'support': 2024.0}	{'precision': 0.8561790861698866, 'recall': 0.9130150425114454, 'f1-score': 0.8836841272353221, 'support': 12232.0}	{'precision': 0.9375346721402419, 'recall': 0.8563032022699635, 'f1-score': 0.8950797097611355, 'support': 9868.0}	0.8289	{'precision': 0.7361982273047546, 'recall': 0.7448659525491124, 'f1-score': 0.7394909716323783, 'support': 29334.0}	{'precision': 0.8324422630439487, 'recall': 0.8289016158723665, 'f1-score': 0.829519030769714, 'support': 29334.0}
0.0774	18.0	1458	1.0618	{'precision': 0.5774647887323944, 'recall': 0.5774647887323944, 'f1-score': 0.5774647887323944, 'support': 284.0}	{'precision': 0.7571428571428571, 'recall': 0.75177304964539, 'f1-score': 0.7544483985765125, 'support': 141.0}	{'precision': 0.754863813229572, 'recall': 0.8220338983050848, 'f1-score': 0.7870182555780934, 'support': 708.0}	{'precision': 0.59768299104792, 'recall': 0.5567819475104243, 'f1-score': 0.5765079365079365, 'support': 4077.0}	{'precision': 0.7977588046958378, 'recall': 0.7386363636363636, 'f1-score': 0.767060030785018, 'support': 2024.0}	{'precision': 0.8586523736600307, 'recall': 0.9167756703727927, 'f1-score': 0.8867626126838526, 'support': 12232.0}	{'precision': 0.9229297331774211, 'recall': 0.879813538710985, 'f1-score': 0.9008560311284047, 'support': 9868.0}	0.8357	{'precision': 0.7523564802408619, 'recall': 0.7490398938447764, 'f1-score': 0.7500168648560301, 'support': 29334.0}	{'precision': 0.8340875618543231, 'recall': 0.8356514624667621, 'f1-score': 0.8340855697185618, 'support': 29334.0}
0.0228	19.0	1539	1.0645	{'precision': 0.5694444444444444, 'recall': 0.5774647887323944, 'f1-score': 0.5734265734265734, 'support': 284.0}	{'precision': 0.7394366197183099, 'recall': 0.7446808510638298, 'f1-score': 0.7420494699646644, 'support': 141.0}	{'precision': 0.7552083333333334, 'recall': 0.8192090395480226, 'f1-score': 0.7859078590785908, 'support': 708.0}	{'precision': 0.5936120488184887, 'recall': 0.5607064017660044, 'f1-score': 0.5766902119071644, 'support': 4077.0}	{'precision': 0.7824947589098532, 'recall': 0.7376482213438735, 'f1-score': 0.7594099694811801, 'support': 2024.0}	{'precision': 0.8594939629316312, 'recall': 0.9136690647482014, 'f1-score': 0.8857539132157718, 'support': 12232.0}	{'precision': 0.9252186899935994, 'recall': 0.8789014997973247, 'f1-score': 0.9014655441222326, 'support': 9868.0}	0.8344	{'precision': 0.7464155511642371, 'recall': 0.7474685524285215, 'f1-score': 0.7463862201708825, 'support': 29334.0}	{'precision': 0.8334350647066741, 'recall': 0.8344242176314175, 'f1-score': 0.8332419893084726, 'support': 29334.0}
0.0228	20.0	1620	1.0525	{'precision': 0.5714285714285714, 'recall': 0.5915492957746479, 'f1-score': 0.5813148788927336, 'support': 284.0}	{'precision': 0.7328767123287672, 'recall': 0.7588652482269503, 'f1-score': 0.7456445993031359, 'support': 141.0}	{'precision': 0.7592592592592593, 'recall': 0.8107344632768362, 'f1-score': 0.7841530054644807, 'support': 708.0}	{'precision': 0.5995872033023736, 'recall': 0.5700269806230072, 'f1-score': 0.5844335470891487, 'support': 4077.0}	{'precision': 0.7741293532338308, 'recall': 0.7687747035573123, 'f1-score': 0.7714427367377293, 'support': 2024.0}	{'precision': 0.8661675245671502, 'recall': 0.907946370176586, 'f1-score': 0.8865650195577552, 'support': 12232.0}	{'precision': 0.9227995758218451, 'recall': 0.8818402918524524, 'f1-score': 0.9018551145196393, 'support': 9868.0}	0.8365	{'precision': 0.746606885705971, 'recall': 0.7556767647839704, 'f1-score': 0.7507727002235176, 'support': 29334.0}	{'precision': 0.8357427933389249, 'recall': 0.8364696256903252, 'f1-score': 0.8356690155425791, 'support': 29334.0}

Framework versions

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