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longformer-spans

Token Classification
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Safetensors
longformer
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Theoreticallyhugo
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metadata
license: apache-2.0
base_model: allenai/longformer-base-4096
tags:
  - generated_from_trainer
datasets:
  - essays_su_g
metrics:
  - accuracy
model-index:
  - name: longformer-spans
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: essays_su_g
          type: essays_su_g
          config: spans
          split: train[0%:20%]
          args: spans
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9304561259971365

longformer-spans

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: 0.6554
  • B: {'precision': 0.8511354079058032, 'recall': 0.8932038834951457, 'f1-score': 0.8716623600344531, 'support': 1133.0}
  • I: {'precision': 0.9360508205399682, 'recall': 0.9644902634593356, 'f1-score': 0.9500577599871047, 'support': 18333.0}
  • O: {'precision': 0.9292274446245273, 'recall': 0.8715038508309688, 'f1-score': 0.8994404643622863, 'support': 9868.0}
  • Accuracy: 0.9305
  • Macro avg: {'precision': 0.9054712243567663, 'recall': 0.9097326659284835, 'f1-score': 0.907053528127948, 'support': 29334.0}
  • Weighted avg: {'precision': 0.9304756437468926, 'recall': 0.9304561259971365, 'f1-score': 0.9300020750695325, '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: 50

Training results

Training Loss Epoch Step Validation Loss B I O Accuracy Macro avg Weighted avg
No log 1.0 81 0.2531 {'precision': 0.7474747474747475, 'recall': 0.9143865842894969, 'f1-score': 0.8225486304088924, 'support': 1133.0} {'precision': 0.9081643158653351, 'recall': 0.9623084056073746, 'f1-score': 0.9344527132604147, 'support': 18333.0} {'precision': 0.9300633654071814, 'recall': 0.8032022699635184, 'f1-score': 0.8619902120717781, 'support': 9868.0} 0.9069 {'precision': 0.8619008095824213, 'recall': 0.89329908662013, 'f1-score': 0.8729971852470283, 'support': 29334.0} {'precision': 0.9093246942621582, 'recall': 0.9069339333196973, 'f1-score': 0.9057540261532953, 'support': 29334.0}
No log 2.0 162 0.2078 {'precision': 0.8297520661157025, 'recall': 0.8861429832303619, 'f1-score': 0.8570209133589416, 'support': 1133.0} {'precision': 0.9325182597650048, 'recall': 0.9610538373424972, 'f1-score': 0.9465710371504554, 'support': 18333.0} {'precision': 0.9238353196099675, 'recall': 0.8641062018646128, 'f1-score': 0.8929730861870352, 'support': 9868.0} 0.9255 {'precision': 0.8953685484968915, 'recall': 0.9037676741458239, 'f1-score': 0.898855012232144, 'support': 29334.0} {'precision': 0.9256280521269545, 'recall': 0.9255471466557578, 'f1-score': 0.9250818140522481, 'support': 29334.0}
No log 3.0 243 0.2431 {'precision': 0.8289473684210527, 'recall': 0.8896734333627537, 'f1-score': 0.8582375478927203, 'support': 1133.0} {'precision': 0.92943782301445, 'recall': 0.9613265695739922, 'f1-score': 0.9451132859632658, 'support': 18333.0} {'precision': 0.923219746614242, 'recall': 0.8566072152411837, 'f1-score': 0.8886669470142977, 'support': 9868.0} 0.9233 {'precision': 0.8938683126832482, 'recall': 0.9025357393926431, 'f1-score': 0.8973392602900946, 'support': 29334.0} {'precision': 0.9234646975296347, 'recall': 0.9233312879252744, 'f1-score': 0.9227691568304388, 'support': 29334.0}
No log 4.0 324 0.2805 {'precision': 0.8503869303525365, 'recall': 0.8729037952338923, 'f1-score': 0.8614982578397212, 'support': 1133.0} {'precision': 0.9574755315558555, 'recall': 0.9284896089019801, 'f1-score': 0.942759823876381, 'support': 18333.0} {'precision': 0.8724141248917541, 'recall': 0.9188285366842318, 'f1-score': 0.8950199891417008, 'support': 9868.0} 0.9231 {'precision': 0.8934255289333821, 'recall': 0.9067406469400346, 'f1-score': 0.8997593569526009, 'support': 29334.0} {'precision': 0.9247245481875896, 'recall': 0.9230926569850685, 'f1-score': 0.9235614178123817, 'support': 29334.0}
No log 5.0 405 0.2743 {'precision': 0.8405063291139241, 'recall': 0.8790820829655781, 'f1-score': 0.8593615185504745, 'support': 1133.0} {'precision': 0.9325283338629382, 'recall': 0.9604538264332079, 'f1-score': 0.9462851000940481, 'support': 18333.0} {'precision': 0.921333764972483, 'recall': 0.8652209160924199, 'f1-score': 0.8923961327410503, 'support': 9868.0} 0.9253 {'precision': 0.8981228093164484, 'recall': 0.9015856084970686, 'f1-score': 0.899347583795191, 'support': 29334.0} {'precision': 0.92520819555273, 'recall': 0.9252744255812367, 'f1-score': 0.9247994265504382, 'support': 29334.0}
No log 6.0 486 0.2924 {'precision': 0.8355481727574751, 'recall': 0.8879082082965578, 'f1-score': 0.8609328198545143, 'support': 1133.0} {'precision': 0.9304343225942971, 'recall': 0.9593628975072274, 'f1-score': 0.9446771941132237, 'support': 18333.0} {'precision': 0.9198005852389726, 'recall': 0.8600526955816782, 'f1-score': 0.8889238020424195, 'support': 9868.0} 0.9232 {'precision': 0.8952610268635816, 'recall': 0.9024412671284878, 'f1-score': 0.8981779386700525, 'support': 29334.0} {'precision': 0.923192223733335, 'recall': 0.9231949273880139, 'f1-score': 0.9226871194902669, 'support': 29334.0}
0.1596 7.0 567 0.3490 {'precision': 0.8356729975227085, 'recall': 0.8932038834951457, 'f1-score': 0.863481228668942, 'support': 1133.0} {'precision': 0.93515484621076, 'recall': 0.9651993672612229, 'f1-score': 0.949939605422091, 'support': 18333.0} {'precision': 0.930659710900989, 'recall': 0.8677543575192541, 'f1-score': 0.8981068750327758, 'support': 9868.0} 0.9296 {'precision': 0.9004958515448193, 'recall': 0.9087192027585408, 'f1-score': 0.9038425697079363, 'support': 29334.0} {'precision': 0.9298002771168626, 'recall': 0.9296379627735734, 'f1-score': 0.9291636210918572, 'support': 29334.0}
0.1596 8.0 648 0.3490 {'precision': 0.8596491228070176, 'recall': 0.8649602824360106, 'f1-score': 0.8622965244170699, 'support': 1133.0} {'precision': 0.9429824561403509, 'recall': 0.9499263622974963, 'f1-score': 0.946441672780631, 'support': 18333.0} {'precision': 0.9021180341353074, 'recall': 0.8891366031617349, 'f1-score': 0.8955802796774524, 'support': 9868.0} 0.9262 {'precision': 0.9015832043608919, 'recall': 0.9013410826317473, 'f1-score': 0.9014394922917178, 'support': 29334.0} {'precision': 0.9260169286632788, 'recall': 0.9261948592077452, 'f1-score': 0.926081794133393, 'support': 29334.0}
0.1596 9.0 729 0.4179 {'precision': 0.8520408163265306, 'recall': 0.884377758164166, 'f1-score': 0.8679081853616285, 'support': 1133.0} {'precision': 0.9287558623596985, 'recall': 0.9613811160202913, 'f1-score': 0.9447869203966764, 'support': 18333.0} {'precision': 0.9209236466615837, 'recall': 0.8568098905553304, 'f1-score': 0.887710640978529, 'support': 9868.0} 0.9232 {'precision': 0.9005734417826042, 'recall': 0.9008562549132626, 'f1-score': 0.900135248912278, 'support': 29334.0} {'precision': 0.9231580423670424, 'recall': 0.923229017522329, 'f1-score': 0.9226170038461553, 'support': 29334.0}
0.1596 10.0 810 0.5158 {'precision': 0.822257806244996, 'recall': 0.9064430714916152, 'f1-score': 0.8623005877413936, 'support': 1133.0} {'precision': 0.9124053998772755, 'recall': 0.9732722413134784, 'f1-score': 0.9418564754942067, 'support': 18333.0} {'precision': 0.9440731621526557, 'recall': 0.8159708147547629, 'f1-score': 0.8753601130619123, 'support': 9868.0} 0.9178 {'precision': 0.8929121227583091, 'recall': 0.8985620425199521, 'f1-score': 0.8931723920991709, 'support': 29334.0} {'precision': 0.9195766092093843, 'recall': 0.9177745960319084, 'f1-score': 0.9164142267280712, 'support': 29334.0}
0.1596 11.0 891 0.4279 {'precision': 0.8556611927398444, 'recall': 0.8737864077669902, 'f1-score': 0.8646288209606986, 'support': 1133.0} {'precision': 0.9373558594797533, 'recall': 0.9533082419680358, 'f1-score': 0.9452647520147115, 'support': 18333.0} {'precision': 0.9077843054972723, 'recall': 0.8768747466558573, 'f1-score': 0.8920618556701031, 'support': 9868.0} 0.9245 {'precision': 0.9002671192389567, 'recall': 0.9013231321302945, 'f1-score': 0.9006518095485044, 'support': 29334.0} {'precision': 0.9242525611871427, 'recall': 0.924524442626304, 'f1-score': 0.9242527287307136, 'support': 29334.0}
0.1596 12.0 972 0.4510 {'precision': 0.842237061769616, 'recall': 0.8905560458958517, 'f1-score': 0.8657228657228657, 'support': 1133.0} {'precision': 0.9381618860092598, 'recall': 0.9615993018054874, 'f1-score': 0.9497360198254499, 'support': 18333.0} {'precision': 0.9247726056714821, 'recall': 0.8757600324280502, 'f1-score': 0.8995992296882319, 'support': 9868.0} 0.9300 {'precision': 0.9017238511501193, 'recall': 0.9093051267097964, 'f1-score': 0.9050193717455158, 'support': 29334.0} {'precision': 0.9299527006190401, 'recall': 0.9299788641167246, 'f1-score': 0.9296249968257807, 'support': 29334.0}
0.0211 13.0 1053 0.4814 {'precision': 0.856898029134533, 'recall': 0.8826125330979699, 'f1-score': 0.8695652173913043, 'support': 1133.0} {'precision': 0.9383210509452099, 'recall': 0.958435607920144, 'f1-score': 0.9482716748967862, 'support': 18333.0} {'precision': 0.9175934752674505, 'recall': 0.877888123226591, 'f1-score': 0.8973017763737118, 'support': 9868.0} 0.9284 {'precision': 0.9042708517823977, 'recall': 0.9063120880815684, 'f1-score': 0.9050462228872674, 'support': 29334.0} {'precision': 0.9282033717845217, 'recall': 0.9284107179382287, 'f1-score': 0.9280853595296557, 'support': 29334.0}
0.0211 14.0 1134 0.4911 {'precision': 0.8470688190314358, 'recall': 0.8799646954986761, 'f1-score': 0.8632034632034632, 'support': 1133.0} {'precision': 0.9397603195739015, 'recall': 0.9624174984999727, 'f1-score': 0.9509539721892853, 'support': 18333.0} {'precision': 0.925708804092944, 'recall': 0.8801175516822051, 'f1-score': 0.9023376623376623, 'support': 9868.0} 0.9315 {'precision': 0.9041793142327604, 'recall': 0.9074999152269513, 'f1-score': 0.905498365910137, 'support': 29334.0} {'precision': 0.9314532416138313, 'recall': 0.9315470102952206, 'f1-score': 0.9312100889037889, 'support': 29334.0}
0.0211 15.0 1215 0.4775 {'precision': 0.8397009966777409, 'recall': 0.8923212709620476, 'f1-score': 0.865211810012837, 'support': 1133.0} {'precision': 0.9259123897039628, 'recall': 0.9673266786668848, 'f1-score': 0.9461665688523716, 'support': 18333.0} {'precision': 0.9330511306672608, 'recall': 0.8488042156465343, 'f1-score': 0.8889360573096311, 'support': 9868.0} 0.9246 {'precision': 0.8995548390163215, 'recall': 0.9028173884251555, 'f1-score': 0.9001048120582799, 'support': 29334.0} {'precision': 0.9249840331050372, 'recall': 0.9245585327606191, 'f1-score': 0.9237873355507777, 'support': 29334.0}
0.0211 16.0 1296 0.5006 {'precision': 0.8545611015490534, 'recall': 0.8764342453662842, 'f1-score': 0.865359477124183, 'support': 1133.0} {'precision': 0.9472161572052402, 'recall': 0.9465444826269569, 'f1-score': 0.9468802008021172, 'support': 18333.0} {'precision': 0.8979902557856273, 'recall': 0.8965342521280908, 'f1-score': 0.897261663286004, 'support': 9868.0} 0.9270 {'precision': 0.8999225048466403, 'recall': 0.9065043267071107, 'f1-score': 0.9031671137374347, 'support': 29334.0} {'precision': 0.9270777726253262, 'recall': 0.9270130224313083, 'f1-score': 0.9270397866705257, 'support': 29334.0}
0.0211 17.0 1377 0.5324 {'precision': 0.8460891505466779, 'recall': 0.8879082082965578, 'f1-score': 0.8664944013781224, 'support': 1133.0} {'precision': 0.9300636741567121, 'recall': 0.9640538918889434, 'f1-score': 0.9467538032997642, 'support': 18333.0} {'precision': 0.9267118792386786, 'recall': 0.8585326307255776, 'f1-score': 0.8913203577064702, 'support': 9868.0} 0.9256 {'precision': 0.9009549013140229, 'recall': 0.9034982436370264, 'f1-score': 0.901522854128119, 'support': 29334.0} {'precision': 0.9256926832416877, 'recall': 0.9256153269243881, 'f1-score': 0.9250059631316369, 'support': 29334.0}
0.0211 18.0 1458 0.5886 {'precision': 0.8499142367066895, 'recall': 0.8746690203000883, 'f1-score': 0.8621139625924314, 'support': 1133.0} {'precision': 0.9357597135374913, 'recall': 0.9550537282496045, 'f1-score': 0.945308282042976, 'support': 18333.0} {'precision': 0.910013746431215, 'recall': 0.872111876773409, 'f1-score': 0.8906597671410089, 'support': 9868.0} 0.9240 {'precision': 0.8985625655584654, 'recall': 0.9006115417743672, 'f1-score': 0.8993606705921388, 'support': 29334.0} {'precision': 0.9237830268035296, 'recall': 0.9240471807458921, 'f1-score': 0.9237111350807452, 'support': 29334.0}
0.0054 19.0 1539 0.5662 {'precision': 0.8524871355060034, 'recall': 0.8773168578993822, 'f1-score': 0.8647237929534581, 'support': 1133.0} {'precision': 0.9394004397490213, 'recall': 0.9554900998199968, 'f1-score': 0.9473769605191995, 'support': 18333.0} {'precision': 0.9122991282428317, 'recall': 0.8802188893392785, 'f1-score': 0.8959719428541957, 'support': 9868.0} 0.9271 {'precision': 0.9013955678326188, 'recall': 0.9043419490195524, 'f1-score': 0.9026908987756178, 'support': 29334.0} {'precision': 0.9269265693034491, 'recall': 0.9271493829685689, 'f1-score': 0.9268918322322205, 'support': 29334.0}
0.0054 20.0 1620 0.5481 {'precision': 0.8527397260273972, 'recall': 0.8790820829655781, 'f1-score': 0.8657105606258149, 'support': 1133.0} {'precision': 0.9360140418062869, 'recall': 0.9599083619702177, 'f1-score': 0.9478106317660365, 'support': 18333.0} {'precision': 0.9194874532835025, 'recall': 0.8726185650587759, 'f1-score': 0.8954401289450424, 'support': 9868.0} 0.9274 {'precision': 0.9027470737057288, 'recall': 0.9038696699981905, 'f1-score': 0.902987107112298, 'support': 29334.0} {'precision': 0.9272380761923127, 'recall': 0.9274221040430899, 'f1-score': 0.9270220757409653, 'support': 29334.0}
0.0054 21.0 1701 0.5435 {'precision': 0.851027397260274, 'recall': 0.8773168578993822, 'f1-score': 0.8639721860060844, 'support': 1133.0} {'precision': 0.9310981074384522, 'recall': 0.9633993345333551, 'f1-score': 0.9469733526352474, 'support': 18333.0} {'precision': 0.9250842666086767, 'recall': 0.8621807863802189, 'f1-score': 0.8925255704169944, 'support': 9868.0} 0.9260 {'precision': 0.9024032571024675, 'recall': 0.9009656596043186, 'f1-score': 0.9011570363527754, 'support': 29334.0} {'precision': 0.925982381797895, 'recall': 0.9260244085361696, 'f1-score': 0.9254511927961336, 'support': 29334.0}
0.0054 22.0 1782 0.5495 {'precision': 0.8664323374340949, 'recall': 0.8702559576345984, 'f1-score': 0.8683399383531484, 'support': 1133.0} {'precision': 0.954357075758413, 'recall': 0.9420716740304369, 'f1-score': 0.9481745813889652, 'support': 18333.0} {'precision': 0.8916724428161205, 'recall': 0.912545601945683, 'f1-score': 0.9019882806630942, 'support': 9868.0} 0.9294 {'precision': 0.9041539520028761, 'recall': 0.9082910778702393, 'f1-score': 0.9061676001350693, 'support': 29334.0} {'precision': 0.9298738587952988, 'recall': 0.9293652416990523, 'f1-score': 0.9295539000593656, 'support': 29334.0}
0.0054 23.0 1863 0.5612 {'precision': 0.8410981697171381, 'recall': 0.8923212709620476, 'f1-score': 0.8659528907922912, 'support': 1133.0} {'precision': 0.9308765464595946, 'recall': 0.9644902634593356, 'f1-score': 0.9473853407629661, 'support': 18333.0} {'precision': 0.9287512312575243, 'recall': 0.8599513579246048, 'f1-score': 0.893028150486714, 'support': 9868.0} 0.9265 {'precision': 0.9002419824780857, 'recall': 0.905587630781996, 'f1-score': 0.9021221273473238, 'support': 29334.0} {'precision': 0.9266939763613048, 'recall': 0.9265357605508966, 'f1-score': 0.9259542464879668, 'support': 29334.0}
0.0054 24.0 1944 0.5436 {'precision': 0.8559102674719585, 'recall': 0.8755516328331863, 'f1-score': 0.8656195462478184, 'support': 1133.0} {'precision': 0.9425299715069082, 'recall': 0.9563082965144821, 'f1-score': 0.9493691449612822, 'support': 18333.0} {'precision': 0.9138291205347817, 'recall': 0.8866031617349007, 'f1-score': 0.9000102870075095, 'support': 9868.0} 0.9297 {'precision': 0.9040897865045494, 'recall': 0.9061543636941897, 'f1-score': 0.9049996594055368, 'support': 29334.0} {'precision': 0.9295293537232939, 'recall': 0.9297402331765187, 'f1-score': 0.9295299990681146, 'support': 29334.0}
0.003 25.0 2025 0.5901 {'precision': 0.8486897717666948, 'recall': 0.8861429832303619, 'f1-score': 0.8670120898100172, 'support': 1133.0} {'precision': 0.9339209373515596, 'recall': 0.9651993672612229, 'f1-score': 0.9493025751072961, 'support': 18333.0} {'precision': 0.9293785310734464, 'recall': 0.8668423186055938, 'f1-score': 0.8970218120805369, 'support': 9868.0} 0.9291 {'precision': 0.9039964133972336, 'recall': 0.9060615563657262, 'f1-score': 0.9044454923326167, 'support': 29334.0} {'precision': 0.9291008863608976, 'recall': 0.9290584304902161, 'f1-score': 0.9285368530990505, 'support': 29334.0}
0.003 26.0 2106 0.5823 {'precision': 0.8599487617421008, 'recall': 0.8887908208296558, 'f1-score': 0.8741319444444444, 'support': 1133.0} {'precision': 0.9412236174191825, 'recall': 0.960835651557301, 'f1-score': 0.9509285251565537, 'support': 18333.0} {'precision': 0.9222057578323455, 'recall': 0.8829550060802595, 'f1-score': 0.9021536550010354, 'support': 9868.0} 0.9319 {'precision': 0.9077927123312096, 'recall': 0.9108604928224054, 'f1-score': 0.9090713748673446, 'support': 29334.0} {'precision': 0.931686812009588, 'recall': 0.9318538215040567, 'f1-score': 0.9315543878196246, 'support': 29334.0}
0.003 27.0 2187 0.5752 {'precision': 0.8514767932489451, 'recall': 0.8905560458958517, 'f1-score': 0.8705780845556514, 'support': 1133.0} {'precision': 0.9362391165852623, 'recall': 0.9619265804832815, 'f1-score': 0.9489090371008098, 'support': 18333.0} {'precision': 0.9241919896918286, 'recall': 0.8722132144304824, 'f1-score': 0.8974506021583858, 'support': 9868.0} 0.9290 {'precision': 0.903969299842012, 'recall': 0.9082319469365384, 'f1-score': 0.9056459079382823, 'support': 29334.0} {'precision': 0.9289125753524113, 'recall': 0.9289902502215859, 'f1-score': 0.9285728809255351, 'support': 29334.0}
0.003 28.0 2268 0.5861 {'precision': 0.8589965397923875, 'recall': 0.8764342453662842, 'f1-score': 0.8676277850589778, 'support': 1133.0} {'precision': 0.941451361658699, 'recall': 0.956035564282987, 'f1-score': 0.9486874154262517, 'support': 18333.0} {'precision': 0.9131889969668445, 'recall': 0.8847790839075801, 'f1-score': 0.8987595861855989, 'support': 9868.0} 0.9290 {'precision': 0.9045456328059771, 'recall': 0.9057496311856171, 'f1-score': 0.9050249288902762, 'support': 29334.0} {'precision': 0.9287591162113087, 'recall': 0.9289902502215859, 'f1-score': 0.928760764435835, 'support': 29334.0}
0.003 29.0 2349 0.6105 {'precision': 0.8523890784982935, 'recall': 0.881729920564872, 'f1-score': 0.8668112798264641, 'support': 1133.0} {'precision': 0.9377168169931153, 'recall': 0.9583810614738449, 'f1-score': 0.9479363366603722, 'support': 18333.0} {'precision': 0.9173474801061008, 'recall': 0.8761653830563437, 'f1-score': 0.8962836261856633, 'support': 9868.0} 0.9278 {'precision': 0.9024844585325033, 'recall': 0.9054254550316868, 'f1-score': 0.9036770808908332, 'support': 29334.0} {'precision': 0.9275688336251569, 'recall': 0.9277630053862412, 'f1-score': 0.9274269060897973, 'support': 29334.0}
0.003 30.0 2430 0.6004 {'precision': 0.8579982891360137, 'recall': 0.8852603706972639, 'f1-score': 0.8714161598609904, 'support': 1133.0} {'precision': 0.9349632216753982, 'recall': 0.9637266132111493, 'f1-score': 0.9491270480795058, 'support': 18333.0} {'precision': 0.9265213638325421, 'recall': 0.870186461289015, 'f1-score': 0.8974707357859533, 'support': 9868.0} 0.9292 {'precision': 0.9064942915479847, 'recall': 0.9063911483991428, 'f1-score': 0.9060046479088165, 'support': 29334.0} {'precision': 0.9291506655371141, 'recall': 0.9292288811617918, 'f1-score': 0.9287482751176065, 'support': 29334.0}
0.0018 31.0 2511 0.6522 {'precision': 0.8560477001703578, 'recall': 0.8870255957634599, 'f1-score': 0.8712613784135241, 'support': 1133.0} {'precision': 0.9333439052753991, 'recall': 0.96312660230186, 'f1-score': 0.9480013959356794, 'support': 18333.0} {'precision': 0.9252326336290846, 'recall': 0.8665383056343737, 'f1-score': 0.8949241234955522, 'support': 9868.0} 0.9277 {'precision': 0.9048747463582805, 'recall': 0.9055635012332311, 'f1-score': 0.9047289659482519, 'support': 29334.0} {'precision': 0.9276297636994175, 'recall': 0.9276948251176109, 'f1-score': 0.927182108954982, 'support': 29334.0}
0.0018 32.0 2592 0.6375 {'precision': 0.8494533221194281, 'recall': 0.8914386584289496, 'f1-score': 0.8699397071490095, 'support': 1133.0} {'precision': 0.9368443474093402, 'recall': 0.9596356297387225, 'f1-score': 0.9481030394481569, 'support': 18333.0} {'precision': 0.9201366645312834, 'recall': 0.8733279286582895, 'f1-score': 0.896121451596132, 'support': 9868.0} 0.9280 {'precision': 0.9021447780200171, 'recall': 0.9081340722753205, 'f1-score': 0.9047213993977662, 'support': 29334.0} {'precision': 0.9278484571013653, 'recall': 0.927967546192132, 'f1-score': 0.9275973680627775, 'support': 29334.0}
0.0018 33.0 2673 0.6827 {'precision': 0.851602023608769, 'recall': 0.8914386584289496, 'f1-score': 0.8710651142733937, 'support': 1133.0} {'precision': 0.9285340314136126, 'recall': 0.9673812251131839, 'f1-score': 0.9475596398899366, 'support': 18333.0} {'precision': 0.9329133510167993, 'recall': 0.8553911633563032, 'f1-score': 0.8924719813914147, 'support': 9868.0} 0.9268 {'precision': 0.9043498020130603, 'recall': 0.9047370156328123, 'f1-score': 0.9036989118515817, 'support': 29334.0} {'precision': 0.927035809589155, 'recall': 0.9267743914911025, 'f1-score': 0.926073538042696, 'support': 29334.0}
0.0018 34.0 2754 0.6228 {'precision': 0.8595744680851064, 'recall': 0.8914386584289496, 'f1-score': 0.8752166377816292, 'support': 1133.0} {'precision': 0.9350964071225372, 'recall': 0.9681994218076693, 'f1-score': 0.9513600428781992, 'support': 18333.0} {'precision': 0.93461915658712, 'recall': 0.8691730847182814, 'f1-score': 0.9007088474665266, 'support': 9868.0} 0.9319 {'precision': 0.909763343931588, 'recall': 0.9096037216516334, 'f1-score': 0.9090951760421183, 'support': 29334.0} {'precision': 0.9320188907520146, 'recall': 0.931922001772687, 'f1-score': 0.9313799353477976, 'support': 29334.0}
0.0018 35.0 2835 0.6088 {'precision': 0.8614200171086399, 'recall': 0.8887908208296558, 'f1-score': 0.8748913987836664, 'support': 1133.0} {'precision': 0.9379079764368731, 'recall': 0.9639993454426444, 'f1-score': 0.9507746933505488, 'support': 18333.0} {'precision': 0.9270542801973826, 'recall': 0.8757600324280502, 'f1-score': 0.9006774361646691, 'support': 9868.0} 0.9314 {'precision': 0.9087940912476319, 'recall': 0.9095167329001167, 'f1-score': 0.908781176099628, 'support': 29334.0} {'precision': 0.9313024970474211, 'recall': 0.9314106497579601, 'f1-score': 0.9309909779808571, 'support': 29334.0}
0.0018 36.0 2916 0.6024 {'precision': 0.8583617747440273, 'recall': 0.8879082082965578, 'f1-score': 0.8728850325379609, 'support': 1133.0} {'precision': 0.9392336059002726, 'recall': 0.9585992472590411, 'f1-score': 0.9488176222870102, 'support': 18333.0} {'precision': 0.9182097132578563, 'recall': 0.8794081880826915, 'f1-score': 0.8983901858274238, 'support': 9868.0} 0.9292 {'precision': 0.9052683646340521, 'recall': 0.9086385478794301, 'f1-score': 0.9066976135507984, 'support': 29334.0} {'precision': 0.9290375345395514, 'recall': 0.9292288811617918, 'f1-score': 0.9289209301492564, 'support': 29334.0}
0.0018 37.0 2997 0.6063 {'precision': 0.8619499568593615, 'recall': 0.881729920564872, 'f1-score': 0.8717277486910995, 'support': 1133.0} {'precision': 0.9392710390095522, 'recall': 0.9600720013091147, 'f1-score': 0.9495576176089771, 'support': 18333.0} {'precision': 0.9199872827469266, 'recall': 0.8797122010539117, 'f1-score': 0.8993990882718607, 'support': 9868.0} 0.9300 {'precision': 0.9070694262052802, 'recall': 0.9071713743092995, 'f1-score': 0.9068948181906458, 'support': 29334.0} {'precision': 0.9297974966056608, 'recall': 0.9300129542510398, 'f1-score': 0.9296781054734817, 'support': 29334.0}
0.0016 38.0 3078 0.6193 {'precision': 0.8541315345699831, 'recall': 0.8940864960282436, 'f1-score': 0.873652436394998, 'support': 1133.0} {'precision': 0.9372875955819882, 'recall': 0.9627993236240658, 'f1-score': 0.9498721915780978, 'support': 18333.0} {'precision': 0.9259338772005152, 'recall': 0.8741386299148763, 'f1-score': 0.8992910758965804, 'support': 9868.0} 0.9303 {'precision': 0.9057843357841623, 'recall': 0.9103414831890619, 'f1-score': 0.9076052346232254, 'support': 29334.0} {'precision': 0.9302563584470943, 'recall': 0.9303197654598759, 'f1-score': 0.9299127100151448, 'support': 29334.0}
0.0016 39.0 3159 0.6373 {'precision': 0.8519764507989908, 'recall': 0.8940864960282436, 'f1-score': 0.8725236864771748, 'support': 1133.0} {'precision': 0.9361533167451956, 'recall': 0.9645448099056346, 'f1-score': 0.9501370157433776, 'support': 18333.0} {'precision': 0.9292350907519447, 'recall': 0.8716051884880421, 'f1-score': 0.8994980129679984, 'support': 9868.0} 0.9306 {'precision': 0.9057882860987103, 'recall': 0.9100788314739735, 'f1-score': 0.9073862383961835, 'support': 29334.0} {'precision': 0.9305747579663571, 'recall': 0.9305583964000819, 'f1-score': 0.9301042353027269, 'support': 29334.0}
0.0016 40.0 3240 0.6333 {'precision': 0.8584825234441603, 'recall': 0.8887908208296558, 'f1-score': 0.8733738074588032, 'support': 1133.0} {'precision': 0.9395264505119454, 'recall': 0.9609992908961981, 'f1-score': 0.9501415666711609, 'support': 18333.0} {'precision': 0.922414709320863, 'recall': 0.8795095257397649, 'f1-score': 0.9004513150386471, 'support': 9868.0} 0.9308 {'precision': 0.9068078944256562, 'recall': 0.909766545821873, 'f1-score': 0.907988896389537, 'support': 29334.0} {'precision': 0.930639785500648, 'recall': 0.9307970273402877, 'f1-score': 0.9304606068873861, 'support': 29334.0}
0.0016 41.0 3321 0.6439 {'precision': 0.8614200171086399, 'recall': 0.8887908208296558, 'f1-score': 0.8748913987836664, 'support': 1133.0} {'precision': 0.9370962617812136, 'recall': 0.96536300660012, 'f1-score': 0.9510196405061931, 'support': 18333.0} {'precision': 0.9296260372885009, 'recall': 0.8741386299148763, 'f1-score': 0.9010288818091607, 'support': 9868.0} 0.9317 {'precision': 0.9093807720594516, 'recall': 0.909430819114884, 'f1-score': 0.9089799736996733, 'support': 29334.0} {'precision': 0.931660338943956, 'recall': 0.9317174609667962, 'f1-score': 0.9312622905132177, 'support': 29334.0}
0.0016 42.0 3402 0.6369 {'precision': 0.8612068965517241, 'recall': 0.881729920564872, 'f1-score': 0.8713475795900567, 'support': 1133.0} {'precision': 0.9372546939641455, 'recall': 0.9638902525500463, 'f1-score': 0.9503858875413451, 'support': 18333.0} {'precision': 0.9261802575107296, 'recall': 0.8747466558573166, 'f1-score': 0.8997289972899729, 'support': 9868.0} 0.9307 {'precision': 0.9082139493421998, 'recall': 0.9067889429907449, 'f1-score': 0.907154154807125, 'support': 29334.0} {'precision': 0.9305919581152813, 'recall': 0.9307288470716575, 'f1-score': 0.93029205117708, 'support': 29334.0}
0.0016 43.0 3483 0.6516 {'precision': 0.8535139712108383, 'recall': 0.8896734333627537, 'f1-score': 0.8712186689714779, 'support': 1133.0} {'precision': 0.9362006788290199, 'recall': 0.9629084165166639, 'f1-score': 0.949366748232004, 'support': 18333.0} {'precision': 0.92567494890825, 'recall': 0.872111876773409, 'f1-score': 0.898095486564049, 'support': 9868.0} 0.9295 {'precision': 0.905129866316036, 'recall': 0.9082312422176089, 'f1-score': 0.9062269679225103, 'support': 29334.0} {'precision': 0.9294661065719273, 'recall': 0.9295356923706279, 'f1-score': 0.929100620736894, 'support': 29334.0}
0.0014 44.0 3564 0.6528 {'precision': 0.8609442060085837, 'recall': 0.8852603706972639, 'f1-score': 0.8729329852045257, 'support': 1133.0} {'precision': 0.9381273567369484, 'recall': 0.9635084274259532, 'f1-score': 0.9506485119207794, 'support': 18333.0} {'precision': 0.9262312633832976, 'recall': 0.8766720713417105, 'f1-score': 0.9007705122865473, 'support': 9868.0} 0.9313 {'precision': 0.9084342753762765, 'recall': 0.9084802898216425, 'f1-score': 0.9081173364706174, 'support': 29334.0} {'precision': 0.931144362294013, 'recall': 0.9312742892206995, 'f1-score': 0.9308677867499838, 'support': 29334.0}
0.0014 45.0 3645 0.6566 {'precision': 0.8540084388185654, 'recall': 0.8932038834951457, 'f1-score': 0.8731665228645384, 'support': 1133.0} {'precision': 0.9349078036667196, 'recall': 0.9651993672612229, 'f1-score': 0.9498121309715513, 'support': 18333.0} {'precision': 0.9299501192799826, 'recall': 0.8690717470612079, 'f1-score': 0.8984808800419066, 'support': 9868.0} 0.9301 {'precision': 0.9062887872550892, 'recall': 0.9091583326058589, 'f1-score': 0.9071531779593321, 'support': 29334.0} {'precision': 0.9301153645209747, 'recall': 0.93008113451967, 'f1-score': 0.9295838546315028, 'support': 29334.0}
0.0014 46.0 3726 0.6471 {'precision': 0.8521959459459459, 'recall': 0.8905560458958517, 'f1-score': 0.870953819594303, 'support': 1133.0} {'precision': 0.9352380952380952, 'recall': 0.9641629847815415, 'f1-score': 0.9494802997341067, 'support': 18333.0} {'precision': 0.9281081081081081, 'recall': 0.8699837859748683, 'f1-score': 0.8981064964954492, 'support': 9868.0} 0.9296 {'precision': 0.9051807164307165, 'recall': 0.9082342722174205, 'f1-score': 0.9061802052746196, 'support': 29334.0} {'precision': 0.9296321271414592, 'recall': 0.9296379627735734, 'f1-score': 0.9291650617046028, 'support': 29334.0}
0.0014 47.0 3807 0.6518 {'precision': 0.8537616229923922, 'recall': 0.8914386584289496, 'f1-score': 0.8721934369602763, 'support': 1133.0} {'precision': 0.936179227795138, 'recall': 0.9641629847815415, 'f1-score': 0.9499650669103026, 'support': 18333.0} {'precision': 0.9281553398058252, 'recall': 0.8719092014592622, 'f1-score': 0.8991535165639043, 'support': 9868.0} 0.9303 {'precision': 0.9060320635311184, 'recall': 0.9091702815565844, 'f1-score': 0.9071040068114944, 'support': 29334.0} {'precision': 0.9302966726400262, 'recall': 0.9303197654598759, 'f1-score': 0.929868126992404, 'support': 29334.0}
0.0014 48.0 3888 0.6532 {'precision': 0.8524451939291737, 'recall': 0.8923212709620476, 'f1-score': 0.871927554980595, 'support': 1133.0} {'precision': 0.9361364117771659, 'recall': 0.9642720776741396, 'f1-score': 0.9499959695837924, 'support': 18333.0} {'precision': 0.9285405872193437, 'recall': 0.8717065261451156, 'f1-score': 0.8992264269287059, 'support': 9868.0} 0.9304 {'precision': 0.9057073976418945, 'recall': 0.9094332915937676, 'f1-score': 0.9070499838310311, 'support': 29334.0} {'precision': 0.9303486655932715, 'recall': 0.930353855594191, 'f1-score': 0.929901698067265, 'support': 29334.0}
0.0014 49.0 3969 0.6541 {'precision': 0.8511354079058032, 'recall': 0.8932038834951457, 'f1-score': 0.8716623600344531, 'support': 1133.0} {'precision': 0.9361330297092623, 'recall': 0.9642175312278405, 'f1-score': 0.9499677558039552, 'support': 18333.0} {'precision': 0.9287410926365796, 'recall': 0.8717065261451156, 'f1-score': 0.8993204391008887, 'support': 9868.0} 0.9304 {'precision': 0.9053365100838816, 'recall': 0.9097093136227006, 'f1-score': 0.906983518313099, 'support': 29334.0} {'precision': 0.9303634128640809, 'recall': 0.930353855594191, 'f1-score': 0.9299054480848339, 'support': 29334.0}
0.0013 50.0 4050 0.6554 {'precision': 0.8511354079058032, 'recall': 0.8932038834951457, 'f1-score': 0.8716623600344531, 'support': 1133.0} {'precision': 0.9360508205399682, 'recall': 0.9644902634593356, 'f1-score': 0.9500577599871047, 'support': 18333.0} {'precision': 0.9292274446245273, 'recall': 0.8715038508309688, 'f1-score': 0.8994404643622863, 'support': 9868.0} 0.9305 {'precision': 0.9054712243567663, 'recall': 0.9097326659284835, 'f1-score': 0.907053528127948, 'support': 29334.0} {'precision': 0.9304756437468926, 'recall': 0.9304561259971365, 'f1-score': 0.9300020750695325, 'support': 29334.0}

Framework versions

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