metadata
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
model-index:
- name: binary_paragraph
results: []
binary_paragraph
This model is a fine-tuned version of answerdotai/ModernBERT-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4687
- Classification Report: {'0': {'precision': 0.9499083689676237, 'recall': 0.9767587939698492, 'f1-score': 0.9631464849798699, 'support': 1592.0}, '1': {'precision': 0.827906976744186, 'recall': 0.6846153846153846, 'f1-score': 0.7494736842105263, 'support': 260.0}, 'accuracy': 0.9357451403887689, 'macro avg': {'precision': 0.8889076728559049, 'recall': 0.8306870892926169, 'f1-score': 0.8563100845951981, 'support': 1852.0}, 'weighted avg': {'precision': 0.9327807437094736, 'recall': 0.9357451403887689, 'f1-score': 0.9331492235327697, 'support': 1852.0}}
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: 5e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 32
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Classification Report |
|---|---|---|---|---|
| No log | 1.0 | 98 | 0.2419 | {'0': {'precision': 0.9059233449477352, 'recall': 0.9798994974874372, 'f1-score': 0.9414604707302353, 'support': 1592.0}, '1': {'precision': 0.7538461538461538, 'recall': 0.3769230769230769, 'f1-score': 0.5025641025641026, 'support': 260.0}, 'accuracy': 0.8952483801295896, 'macro avg': {'precision': 0.8298847493969446, 'recall': 0.678411287205257, 'f1-score': 0.722012286647169, 'support': 1852.0}, 'weighted avg': {'precision': 0.8845734153114441, 'recall': 0.8952483801295896, 'f1-score': 0.8798443499293744, 'support': 1852.0}} |
| No log | 2.0 | 196 | 0.2600 | {'0': {'precision': 0.8985260770975056, 'recall': 0.9956030150753769, 'f1-score': 0.9445768772348033, 'support': 1592.0}, '1': {'precision': 0.9204545454545454, 'recall': 0.31153846153846154, 'f1-score': 0.46551724137931033, 'support': 260.0}, 'accuracy': 0.8995680345572354, 'macro avg': {'precision': 0.9094903112760255, 'recall': 0.6535707383069191, 'f1-score': 0.7050470593070568, 'support': 1852.0}, 'weighted avg': {'precision': 0.9016045877739799, 'recall': 0.8995680345572354, 'f1-score': 0.8773222847280927, 'support': 1852.0}} |
| No log | 3.0 | 294 | 0.2403 | {'0': {'precision': 0.968813559322034, 'recall': 0.8976130653266332, 'f1-score': 0.931855233126834, 'support': 1592.0}, '1': {'precision': 0.5676392572944297, 'recall': 0.823076923076923, 'f1-score': 0.6718995290423861, 'support': 260.0}, 'accuracy': 0.8871490280777538, 'macro avg': {'precision': 0.7682264083082317, 'recall': 0.8603449942017781, 'f1-score': 0.80187738108461, 'support': 1852.0}, 'weighted avg': {'precision': 0.9124931929466683, 'recall': 0.8871490280777538, 'f1-score': 0.8953603718622787, 'support': 1852.0}} |
| No log | 4.0 | 392 | 0.2540 | {'0': {'precision': 0.91874637260592, 'recall': 0.9943467336683417, 'f1-score': 0.955052790346908, 'support': 1592.0}, '1': {'precision': 0.9302325581395349, 'recall': 0.46153846153846156, 'f1-score': 0.6169665809768637, 'support': 260.0}, 'accuracy': 0.9195464362850972, 'macro avg': {'precision': 0.9244894653727274, 'recall': 0.7279425976034016, 'f1-score': 0.7860096856618859, 'support': 1852.0}, 'weighted avg': {'precision': 0.9203589040523238, 'recall': 0.9195464362850972, 'f1-score': 0.907589283631891, 'support': 1852.0}} |
| No log | 5.0 | 490 | 0.1908 | {'0': {'precision': 0.9294947121034077, 'recall': 0.9937185929648241, 'f1-score': 0.9605343047965998, 'support': 1592.0}, '1': {'precision': 0.9333333333333333, 'recall': 0.5384615384615384, 'f1-score': 0.6829268292682927, 'support': 260.0}, 'accuracy': 0.9298056155507559, 'macro avg': {'precision': 0.9314140227183705, 'recall': 0.7660900657131813, 'f1-score': 0.8217305670324463, 'support': 1852.0}, 'weighted avg': {'precision': 0.9300336114121447, 'recall': 0.9298056155507559, 'f1-score': 0.9215613330701636, 'support': 1852.0}} |
| 0.2079 | 6.0 | 588 | 0.2416 | {'0': {'precision': 0.928697701826753, 'recall': 0.9899497487437185, 'f1-score': 0.9583460018242627, 'support': 1592.0}, '1': {'precision': 0.896774193548387, 'recall': 0.5346153846153846, 'f1-score': 0.6698795180722892, 'support': 260.0}, 'accuracy': 0.9260259179265659, 'macro avg': {'precision': 0.91273594768757, 'recall': 0.7622825666795516, 'f1-score': 0.8141127599482759, 'support': 1852.0}, 'weighted avg': {'precision': 0.9242159998006326, 'recall': 0.9260259179265659, 'f1-score': 0.9178485473018474, 'support': 1852.0}} |
| 0.2079 | 7.0 | 686 | 0.2724 | {'0': {'precision': 0.9342027267338471, 'recall': 0.9899497487437185, 'f1-score': 0.9612686794754498, 'support': 1592.0}, '1': {'precision': 0.9030303030303031, 'recall': 0.573076923076923, 'f1-score': 0.7011764705882353, 'support': 260.0}, 'accuracy': 0.9314254859611231, 'macro avg': {'precision': 0.9186165148820751, 'recall': 0.7815133359103208, 'f1-score': 0.8312225750318425, 'support': 1852.0}, 'weighted avg': {'precision': 0.9298264685465244, 'recall': 0.9314254859611231, 'f1-score': 0.9247546544696854, 'support': 1852.0}} |
| 0.2079 | 8.0 | 784 | 0.3374 | {'0': {'precision': 0.9718120805369127, 'recall': 0.9095477386934674, 'f1-score': 0.9396495781959766, 'support': 1592.0}, '1': {'precision': 0.6022099447513812, 'recall': 0.8384615384615385, 'f1-score': 0.7009646302250804, 'support': 260.0}, 'accuracy': 0.8995680345572354, 'macro avg': {'precision': 0.787011012644147, 'recall': 0.8740046385775029, 'f1-score': 0.8203071042105285, 'support': 1852.0}, 'weighted avg': {'precision': 0.9199240917117302, 'recall': 0.8995680345572354, 'f1-score': 0.9061408921957428, 'support': 1852.0}} |
| 0.2079 | 9.0 | 882 | 0.3082 | {'0': {'precision': 0.953125, 'recall': 0.9579145728643216, 'f1-score': 0.9555137844611529, 'support': 1592.0}, '1': {'precision': 0.7341269841269841, 'recall': 0.7115384615384616, 'f1-score': 0.72265625, 'support': 260.0}, 'accuracy': 0.9233261339092873, 'macro avg': {'precision': 0.8436259920634921, 'recall': 0.8347265172013916, 'f1-score': 0.8390850172305764, 'support': 1852.0}, 'weighted avg': {'precision': 0.9223801381603758, 'recall': 0.9233261339092873, 'f1-score': 0.9228232018694144, 'support': 1852.0}} |
| 0.2079 | 10.0 | 980 | 0.3587 | {'0': {'precision': 0.9505867819641755, 'recall': 0.9667085427135679, 'f1-score': 0.9585798816568047, 'support': 1592.0}, '1': {'precision': 0.7725321888412017, 'recall': 0.6923076923076923, 'f1-score': 0.7302231237322515, 'support': 260.0}, 'accuracy': 0.9281857451403888, 'macro avg': {'precision': 0.8615594854026886, 'recall': 0.82950811751063, 'f1-score': 0.8444015026945282, 'support': 1852.0}, 'weighted avg': {'precision': 0.92558991683892, 'recall': 0.9281857451403888, 'f1-score': 0.9265211575421266, 'support': 1852.0}} |
| 0.0384 | 11.0 | 1078 | 0.4151 | {'0': {'precision': 0.9414957780458384, 'recall': 0.9805276381909548, 'f1-score': 0.9606153846153846, 'support': 1592.0}, '1': {'precision': 0.8402061855670103, 'recall': 0.6269230769230769, 'f1-score': 0.7180616740088106, 'support': 260.0}, 'accuracy': 0.9308855291576674, 'macro avg': {'precision': 0.8908509818064243, 'recall': 0.8037253575570158, 'f1-score': 0.8393385293120976, 'support': 1852.0}, 'weighted avg': {'precision': 0.9272758568555062, 'recall': 0.9308855291576674, 'f1-score': 0.9265635677915676, 'support': 1852.0}} |
| 0.0384 | 12.0 | 1176 | 0.3982 | {'0': {'precision': 0.9519704433497537, 'recall': 0.9711055276381909, 'f1-score': 0.9614427860696517, 'support': 1592.0}, '1': {'precision': 0.7982456140350878, 'recall': 0.7, 'f1-score': 0.7459016393442623, 'support': 260.0}, 'accuracy': 0.9330453563714903, 'macro avg': {'precision': 0.8751080286924207, 'recall': 0.8355527638190954, 'f1-score': 0.853672212706957, 'support': 1852.0}, 'weighted avg': {'precision': 0.9303892038131375, 'recall': 0.9330453563714903, 'f1-score': 0.931183229833906, 'support': 1852.0}} |
| 0.0384 | 13.0 | 1274 | 0.4471 | {'0': {'precision': 0.9434756464221287, 'recall': 0.9855527638190955, 'f1-score': 0.9640552995391705, 'support': 1592.0}, '1': {'precision': 0.8783068783068783, 'recall': 0.6384615384615384, 'f1-score': 0.7394209354120267, 'support': 260.0}, 'accuracy': 0.9368250539956804, 'macro avg': {'precision': 0.9108912623645035, 'recall': 0.812007151140317, 'f1-score': 0.8517381174755986, 'support': 1852.0}, 'weighted avg': {'precision': 0.9343266832957976, 'recall': 0.9368250539956804, 'f1-score': 0.9325191577070661, 'support': 1852.0}} |
| 0.0384 | 14.0 | 1372 | 0.4715 | {'0': {'precision': 0.9402173913043478, 'recall': 0.9780150753768844, 'f1-score': 0.958743842364532, 'support': 1592.0}, '1': {'precision': 0.8214285714285714, 'recall': 0.6192307692307693, 'f1-score': 0.706140350877193, 'support': 260.0}, 'accuracy': 0.927645788336933, 'macro avg': {'precision': 0.8808229813664596, 'recall': 0.7986229223038268, 'f1-score': 0.8324420966208625, 'support': 1852.0}, 'weighted avg': {'precision': 0.9235407751230834, 'recall': 0.927645788336933, 'f1-score': 0.9232811491751647, 'support': 1852.0}} |
| 0.0384 | 15.0 | 1470 | 0.4425 | {'0': {'precision': 0.9442761962447002, 'recall': 0.9792713567839196, 'f1-score': 0.9614554424915202, 'support': 1592.0}, '1': {'precision': 0.835820895522388, 'recall': 0.6461538461538462, 'f1-score': 0.7288503253796096, 'support': 260.0}, 'accuracy': 0.9325053995680346, 'macro avg': {'precision': 0.8900485458835441, 'recall': 0.8127126014688829, 'f1-score': 0.8451528839355649, 'support': 1852.0}, 'weighted avg': {'precision': 0.9290502900957794, 'recall': 0.9325053995680346, 'f1-score': 0.9288002964606904, 'support': 1852.0}} |
| 0.0036 | 16.0 | 1568 | 0.4174 | {'0': {'precision': 0.9501845018450185, 'recall': 0.9704773869346733, 'f1-score': 0.9602237414543194, 'support': 1592.0}, '1': {'precision': 0.7920353982300885, 'recall': 0.6884615384615385, 'f1-score': 0.7366255144032922, 'support': 260.0}, 'accuracy': 0.9308855291576674, 'macro avg': {'precision': 0.8711099500375534, 'recall': 0.8294694626981058, 'f1-score': 0.8484246279288058, 'support': 1852.0}, 'weighted avg': {'precision': 0.9279821438861189, 'recall': 0.9308855291576674, 'f1-score': 0.9288330616307411, 'support': 1852.0}} |
| 0.0036 | 17.0 | 1666 | 0.4366 | {'0': {'precision': 0.9503067484662576, 'recall': 0.9729899497487438, 'f1-score': 0.9615145872129113, 'support': 1592.0}, '1': {'precision': 0.8063063063063063, 'recall': 0.6884615384615385, 'f1-score': 0.7427385892116183, 'support': 260.0}, 'accuracy': 0.9330453563714903, 'macro avg': {'precision': 0.878306527386282, 'recall': 0.8307257441051411, 'f1-score': 0.8521265882122648, 'support': 1852.0}, 'weighted avg': {'precision': 0.9300907036705841, 'recall': 0.9330453563714903, 'f1-score': 0.9308008941889717, 'support': 1852.0}} |
| 0.0036 | 18.0 | 1764 | 0.4639 | {'0': {'precision': 0.944140862173649, 'recall': 0.9767587939698492, 'f1-score': 0.9601728928681692, 'support': 1592.0}, '1': {'precision': 0.8195121951219512, 'recall': 0.6461538461538462, 'f1-score': 0.7225806451612903, 'support': 260.0}, 'accuracy': 0.9303455723542117, 'macro avg': {'precision': 0.8818265286478001, 'recall': 0.8114563200618476, 'f1-score': 0.8413767690147298, 'support': 1852.0}, 'weighted avg': {'precision': 0.9266443970368016, 'recall': 0.9303455723542117, 'f1-score': 0.9268176097127757, 'support': 1852.0}} |
| 0.0036 | 19.0 | 1862 | 0.4535 | {'0': {'precision': 0.9465695203400122, 'recall': 0.9792713567839196, 'f1-score': 0.9626427909848718, 'support': 1592.0}, '1': {'precision': 0.8390243902439024, 'recall': 0.6615384615384615, 'f1-score': 0.7397849462365591, 'support': 260.0}, 'accuracy': 0.9346652267818575, 'macro avg': {'precision': 0.8927969552919572, 'recall': 0.8204049091611906, 'f1-score': 0.8512138686107155, 'support': 1852.0}, 'weighted avg': {'precision': 0.9314713919247916, 'recall': 0.9346652267818575, 'f1-score': 0.9313560525212858, 'support': 1852.0}} |
| 0.0036 | 20.0 | 1960 | 0.4700 | {'0': {'precision': 0.9454214675560946, 'recall': 0.9792713567839196, 'f1-score': 0.9620487503856834, 'support': 1592.0}, '1': {'precision': 0.8374384236453202, 'recall': 0.6538461538461539, 'f1-score': 0.734341252699784, 'support': 260.0}, 'accuracy': 0.933585313174946, 'macro avg': {'precision': 0.8914299456007073, 'recall': 0.8165587553150367, 'f1-score': 0.8481950015427338, 'support': 1852.0}, 'weighted avg': {'precision': 0.9302618609595495, 'recall': 0.933585313174946, 'f1-score': 0.9300811751166047, 'support': 1852.0}} |
| 0.0013 | 21.0 | 2058 | 0.4619 | {'0': {'precision': 0.9457978075517661, 'recall': 0.9755025125628141, 'f1-score': 0.9604205318491033, 'support': 1592.0}, '1': {'precision': 0.8142857142857143, 'recall': 0.6576923076923077, 'f1-score': 0.7276595744680852, 'support': 260.0}, 'accuracy': 0.9308855291576674, 'macro avg': {'precision': 0.8800417609187402, 'recall': 0.8165974101275608, 'f1-score': 0.8440400531585942, 'support': 1852.0}, 'weighted avg': {'precision': 0.927334986682882, 'recall': 0.9308855291576674, 'f1-score': 0.9277435075947487, 'support': 1852.0}} |
| 0.0013 | 22.0 | 2156 | 0.4610 | {'0': {'precision': 0.9470158343483557, 'recall': 0.9767587939698492, 'f1-score': 0.9616573902288188, 'support': 1592.0}, '1': {'precision': 0.8238095238095238, 'recall': 0.6653846153846154, 'f1-score': 0.7361702127659574, 'support': 260.0}, 'accuracy': 0.9330453563714903, 'macro avg': {'precision': 0.8854126790789397, 'recall': 0.8210717046772322, 'f1-score': 0.848913801497388, 'support': 1852.0}, 'weighted avg': {'precision': 0.9297190520912842, 'recall': 0.9330453563714903, 'f1-score': 0.9300015229824128, 'support': 1852.0}} |
| 0.0013 | 23.0 | 2254 | 0.4548 | {'0': {'precision': 0.9480757483200978, 'recall': 0.9748743718592965, 'f1-score': 0.9612883245586868, 'support': 1592.0}, '1': {'precision': 0.813953488372093, 'recall': 0.6730769230769231, 'f1-score': 0.7368421052631579, 'support': 260.0}, 'accuracy': 0.9325053995680346, 'macro avg': {'precision': 0.8810146183460954, 'recall': 0.8239756474681098, 'f1-score': 0.8490652149109224, 'support': 1852.0}, 'weighted avg': {'precision': 0.9292464893641145, 'recall': 0.9325053995680346, 'f1-score': 0.9297785961478674, 'support': 1852.0}} |
| 0.0013 | 24.0 | 2352 | 0.4452 | {'0': {'precision': 0.9480757483200978, 'recall': 0.9748743718592965, 'f1-score': 0.9612883245586868, 'support': 1592.0}, '1': {'precision': 0.813953488372093, 'recall': 0.6730769230769231, 'f1-score': 0.7368421052631579, 'support': 260.0}, 'accuracy': 0.9325053995680346, 'macro avg': {'precision': 0.8810146183460954, 'recall': 0.8239756474681098, 'f1-score': 0.8490652149109224, 'support': 1852.0}, 'weighted avg': {'precision': 0.9292464893641145, 'recall': 0.9325053995680346, 'f1-score': 0.9297785961478674, 'support': 1852.0}} |
| 0.0013 | 25.0 | 2450 | 0.4680 | {'0': {'precision': 0.9465045592705167, 'recall': 0.9780150753768844, 'f1-score': 0.9620018535681186, 'support': 1592.0}, '1': {'precision': 0.8309178743961353, 'recall': 0.6615384615384615, 'f1-score': 0.7366167023554604, 'support': 260.0}, 'accuracy': 0.933585313174946, 'macro avg': {'precision': 0.888711216833326, 'recall': 0.8197767684576729, 'f1-score': 0.8493092779617895, 'support': 1852.0}, 'weighted avg': {'precision': 0.9302774868799447, 'recall': 0.933585313174946, 'f1-score': 0.930360309661374, 'support': 1852.0}} |
| 0.001 | 26.0 | 2548 | 0.4563 | {'0': {'precision': 0.9481391092129348, 'recall': 0.9761306532663316, 'f1-score': 0.9619312906220984, 'support': 1592.0}, '1': {'precision': 0.8215962441314554, 'recall': 0.6730769230769231, 'f1-score': 0.7399577167019028, 'support': 260.0}, 'accuracy': 0.933585313174946, 'macro avg': {'precision': 0.884867676672195, 'recall': 0.8246037881716274, 'f1-score': 0.8509445036620006, 'support': 1852.0}, 'weighted avg': {'precision': 0.9303739121712584, 'recall': 0.933585313174946, 'f1-score': 0.9307686938514446, 'support': 1852.0}} |
| 0.001 | 27.0 | 2646 | 0.4720 | {'0': {'precision': 0.9465370595382746, 'recall': 0.9786432160804021, 'f1-score': 0.9623224212476837, 'support': 1592.0}, '1': {'precision': 0.8349514563106796, 'recall': 0.6615384615384615, 'f1-score': 0.7381974248927039, 'support': 260.0}, 'accuracy': 0.9341252699784017, 'macro avg': {'precision': 0.8907442579244771, 'recall': 0.8200908388094318, 'f1-score': 0.8502599230701938, 'support': 1852.0}, 'weighted avg': {'precision': 0.9308716940743574, 'recall': 0.9341252699784017, 'f1-score': 0.93085778893003, 'support': 1852.0}} |
| 0.001 | 28.0 | 2744 | 0.4285 | {'0': {'precision': 0.9519112207151664, 'recall': 0.9698492462311558, 'f1-score': 0.9607965152457997, 'support': 1592.0}, '1': {'precision': 0.7913043478260869, 'recall': 0.7, 'f1-score': 0.7428571428571429, 'support': 260.0}, 'accuracy': 0.9319654427645788, 'macro avg': {'precision': 0.8716077842706267, 'recall': 0.8349246231155778, 'f1-score': 0.8518268290514712, 'support': 1852.0}, 'weighted avg': {'precision': 0.9293638195536326, 'recall': 0.9319654427645788, 'f1-score': 0.9302002750616469, 'support': 1852.0}} |
| 0.001 | 29.0 | 2842 | 0.4649 | {'0': {'precision': 0.947592931139549, 'recall': 0.9767587939698492, 'f1-score': 0.9619548407052273, 'support': 1592.0}, '1': {'precision': 0.8246445497630331, 'recall': 0.6692307692307692, 'f1-score': 0.7388535031847133, 'support': 260.0}, 'accuracy': 0.933585313174946, 'macro avg': {'precision': 0.8861187404512911, 'recall': 0.8229947816003091, 'f1-score': 0.8504041719449703, 'support': 1852.0}, 'weighted avg': {'precision': 0.9303323592400381, 'recall': 0.933585313174946, 'f1-score': 0.9306339185911163, 'support': 1852.0}} |
| 0.001 | 30.0 | 2940 | 0.4715 | {'0': {'precision': 0.9465045592705167, 'recall': 0.9780150753768844, 'f1-score': 0.9620018535681186, 'support': 1592.0}, '1': {'precision': 0.8309178743961353, 'recall': 0.6615384615384615, 'f1-score': 0.7366167023554604, 'support': 260.0}, 'accuracy': 0.933585313174946, 'macro avg': {'precision': 0.888711216833326, 'recall': 0.8197767684576729, 'f1-score': 0.8493092779617895, 'support': 1852.0}, 'weighted avg': {'precision': 0.9302774868799447, 'recall': 0.933585313174946, 'f1-score': 0.930360309661374, 'support': 1852.0}} |
| 0.001 | 31.0 | 3038 | 0.4358 | {'0': {'precision': 0.9519408502772643, 'recall': 0.9704773869346733, 'f1-score': 0.9611197511664075, 'support': 1592.0}, '1': {'precision': 0.7947598253275109, 'recall': 0.7, 'f1-score': 0.7443762781186094, 'support': 260.0}, 'accuracy': 0.9325053995680346, 'macro avg': {'precision': 0.8733503378023876, 'recall': 0.8352386934673366, 'f1-score': 0.8527480146425084, 'support': 1852.0}, 'weighted avg': {'precision': 0.9298743996903658, 'recall': 0.9325053995680346, 'f1-score': 0.9306914018184445, 'support': 1852.0}} |
| 0.001 | 32.0 | 3136 | 0.4559 | {'0': {'precision': 0.9486552567237164, 'recall': 0.9748743718592965, 'f1-score': 0.9615861214374225, 'support': 1592.0}, '1': {'precision': 0.8148148148148148, 'recall': 0.676923076923077, 'f1-score': 0.7394957983193278, 'support': 260.0}, 'accuracy': 0.9330453563714903, 'macro avg': {'precision': 0.8817350357692656, 'recall': 0.8258987243911867, 'f1-score': 0.8505409598783751, 'support': 1852.0}, 'weighted avg': {'precision': 0.9298655618552961, 'recall': 0.9330453563714903, 'f1-score': 0.9304071343906056, 'support': 1852.0}} |
| 0.001 | 33.0 | 3234 | 0.4588 | {'0': {'precision': 0.9469512195121951, 'recall': 0.9755025125628141, 'f1-score': 0.9610148514851485, 'support': 1592.0}, '1': {'precision': 0.8160377358490566, 'recall': 0.6653846153846154, 'f1-score': 0.7330508474576272, 'support': 260.0}, 'accuracy': 0.9319654427645788, 'macro avg': {'precision': 0.8814944776806258, 'recall': 0.8204435639737147, 'f1-score': 0.8470328494713879, 'support': 1852.0}, 'weighted avg': {'precision': 0.9285724367085147, 'recall': 0.9319654427645788, 'f1-score': 0.9290112656065548, 'support': 1852.0}} |
| 0.001 | 34.0 | 3332 | 0.4686 | {'0': {'precision': 0.9470158343483557, 'recall': 0.9767587939698492, 'f1-score': 0.9616573902288188, 'support': 1592.0}, '1': {'precision': 0.8238095238095238, 'recall': 0.6653846153846154, 'f1-score': 0.7361702127659574, 'support': 260.0}, 'accuracy': 0.9330453563714903, 'macro avg': {'precision': 0.8854126790789397, 'recall': 0.8210717046772322, 'f1-score': 0.848913801497388, 'support': 1852.0}, 'weighted avg': {'precision': 0.9297190520912842, 'recall': 0.9330453563714903, 'f1-score': 0.9300015229824128, 'support': 1852.0}} |
| 0.001 | 35.0 | 3430 | 0.4755 | {'0': {'precision': 0.9464720194647201, 'recall': 0.9773869346733668, 'f1-score': 0.9616810877626699, 'support': 1592.0}, '1': {'precision': 0.8269230769230769, 'recall': 0.6615384615384615, 'f1-score': 0.7350427350427351, 'support': 260.0}, 'accuracy': 0.9330453563714903, 'macro avg': {'precision': 0.8866975481938986, 'recall': 0.8194626981059141, 'f1-score': 0.8483619114027026, 'support': 1852.0}, 'weighted avg': {'precision': 0.9296886905981827, 'recall': 0.9330453563714903, 'f1-score': 0.929863608439137, 'support': 1852.0}} |
| 0.001 | 36.0 | 3528 | 0.4484 | {'0': {'precision': 0.9502762430939227, 'recall': 0.9723618090452262, 'f1-score': 0.9611921763427507, 'support': 1592.0}, '1': {'precision': 0.8026905829596412, 'recall': 0.6884615384615385, 'f1-score': 0.7412008281573499, 'support': 260.0}, 'accuracy': 0.9325053995680346, 'macro avg': {'precision': 0.876483413026782, 'recall': 0.8304116737533823, 'f1-score': 0.8511965022500503, 'support': 1852.0}, 'weighted avg': {'precision': 0.9295568739606002, 'recall': 0.9325053995680346, 'f1-score': 0.9303078618026835, 'support': 1852.0}} |
| 0.001 | 37.0 | 3626 | 0.4880 | {'0': {'precision': 0.9460932768019382, 'recall': 0.9811557788944724, 'f1-score': 0.9633055812519272, 'support': 1592.0}, '1': {'precision': 0.8507462686567164, 'recall': 0.6576923076923077, 'f1-score': 0.7418655097613883, 'support': 260.0}, 'accuracy': 0.9357451403887689, 'macro avg': {'precision': 0.8984197727293273, 'recall': 0.81942404329339, 'f1-score': 0.8525855455066578, 'support': 1852.0}, 'weighted avg': {'precision': 0.9327076277102765, 'recall': 0.9357451403887689, 'f1-score': 0.9322178822305773, 'support': 1852.0}} |
| 0.001 | 38.0 | 3724 | 0.4990 | {'0': {'precision': 0.9439083232810616, 'recall': 0.9830402010050251, 'f1-score': 0.963076923076923, 'support': 1592.0}, '1': {'precision': 0.8608247422680413, 'recall': 0.6423076923076924, 'f1-score': 0.73568281938326, 'support': 260.0}, 'accuracy': 0.9352051835853131, 'macro avg': {'precision': 0.9023665327745514, 'recall': 0.8126739466563587, 'f1-score': 0.8493798712300915, 'support': 1852.0}, 'weighted avg': {'precision': 0.9322443216269659, 'recall': 0.9352051835853131, 'f1-score': 0.9311533448045946, 'support': 1852.0}} |
| 0.001 | 39.0 | 3822 | 0.4625 | {'0': {'precision': 0.9481391092129348, 'recall': 0.9761306532663316, 'f1-score': 0.9619312906220984, 'support': 1592.0}, '1': {'precision': 0.8215962441314554, 'recall': 0.6730769230769231, 'f1-score': 0.7399577167019028, 'support': 260.0}, 'accuracy': 0.933585313174946, 'macro avg': {'precision': 0.884867676672195, 'recall': 0.8246037881716274, 'f1-score': 0.8509445036620006, 'support': 1852.0}, 'weighted avg': {'precision': 0.9303739121712584, 'recall': 0.933585313174946, 'f1-score': 0.9307686938514446, 'support': 1852.0}} |
| 0.001 | 40.0 | 3920 | 0.4582 | {'0': {'precision': 0.9486866218692731, 'recall': 0.9755025125628141, 'f1-score': 0.9619077113657479, 'support': 1592.0}, '1': {'precision': 0.8186046511627907, 'recall': 0.676923076923077, 'f1-score': 0.7410526315789474, 'support': 260.0}, 'accuracy': 0.933585313174946, 'macro avg': {'precision': 0.8836456365160319, 'recall': 0.8262127947429455, 'f1-score': 0.8514801714723477, 'support': 1852.0}, 'weighted avg': {'precision': 0.9304245741459009, 'recall': 0.933585313174946, 'f1-score': 0.9309021386095017, 'support': 1852.0}} |
| 0.001 | 41.0 | 4018 | 0.4695 | {'0': {'precision': 0.9465045592705167, 'recall': 0.9780150753768844, 'f1-score': 0.9620018535681186, 'support': 1592.0}, '1': {'precision': 0.8309178743961353, 'recall': 0.6615384615384615, 'f1-score': 0.7366167023554604, 'support': 260.0}, 'accuracy': 0.933585313174946, 'macro avg': {'precision': 0.888711216833326, 'recall': 0.8197767684576729, 'f1-score': 0.8493092779617895, 'support': 1852.0}, 'weighted avg': {'precision': 0.9302774868799447, 'recall': 0.933585313174946, 'f1-score': 0.930360309661374, 'support': 1852.0}} |
| 0.001 | 42.0 | 4116 | 0.4682 | {'0': {'precision': 0.9480440097799511, 'recall': 0.9742462311557789, 'f1-score': 0.9609665427509294, 'support': 1592.0}, '1': {'precision': 0.8101851851851852, 'recall': 0.6730769230769231, 'f1-score': 0.7352941176470589, 'support': 260.0}, 'accuracy': 0.9319654427645788, 'macro avg': {'precision': 0.8791145974825681, 'recall': 0.823661577116351, 'f1-score': 0.8481303301989942, 'support': 1852.0}, 'weighted avg': {'precision': 0.9286901791132993, 'recall': 0.9319654427645788, 'f1-score': 0.9292846688162608, 'support': 1852.0}} |
| 0.001 | 43.0 | 4214 | 0.4735 | {'0': {'precision': 0.9464394400486914, 'recall': 0.9767587939698492, 'f1-score': 0.9613601236476044, 'support': 1592.0}, '1': {'precision': 0.8229665071770335, 'recall': 0.6615384615384615, 'f1-score': 0.7334754797441365, 'support': 260.0}, 'accuracy': 0.9325053995680346, 'macro avg': {'precision': 0.8847029736128624, 'recall': 0.8191486277541553, 'f1-score': 0.8474178016958704, 'support': 1852.0}, 'weighted avg': {'precision': 0.9291052270105536, 'recall': 0.9325053995680346, 'f1-score': 0.9293676790391261, 'support': 1852.0}} |
| 0.001 | 44.0 | 4312 | 0.4685 | {'0': {'precision': 0.9476567255021302, 'recall': 0.9780150753768844, 'f1-score': 0.962596599690881, 'support': 1592.0}, '1': {'precision': 0.8325358851674641, 'recall': 0.6692307692307692, 'f1-score': 0.7420042643923241, 'support': 260.0}, 'accuracy': 0.9346652267818575, 'macro avg': {'precision': 0.8900963053347972, 'recall': 0.8236229223038267, 'f1-score': 0.8523004320416026, 'support': 1852.0}, 'weighted avg': {'precision': 0.931495052452987, 'recall': 0.9346652267818575, 'f1-score': 0.931627913309874, 'support': 1852.0}} |
| 0.001 | 45.0 | 4410 | 0.4780 | {'0': {'precision': 0.9482023156611822, 'recall': 0.9773869346733668, 'f1-score': 0.9625734611815651, 'support': 1592.0}, '1': {'precision': 0.8293838862559242, 'recall': 0.6730769230769231, 'f1-score': 0.7430997876857749, 'support': 260.0}, 'accuracy': 0.9346652267818575, 'macro avg': {'precision': 0.8887931009585532, 'recall': 0.825231928875145, 'f1-score': 0.85283662443367, 'support': 1852.0}, 'weighted avg': {'precision': 0.9315215426345261, 'recall': 0.9346652267818575, 'f1-score': 0.9317618223538624, 'support': 1852.0}} |
| 0.0009 | 46.0 | 4508 | 0.4769 | {'0': {'precision': 0.9464720194647201, 'recall': 0.9773869346733668, 'f1-score': 0.9616810877626699, 'support': 1592.0}, '1': {'precision': 0.8269230769230769, 'recall': 0.6615384615384615, 'f1-score': 0.7350427350427351, 'support': 260.0}, 'accuracy': 0.9330453563714903, 'macro avg': {'precision': 0.8866975481938986, 'recall': 0.8194626981059141, 'f1-score': 0.8483619114027026, 'support': 1852.0}, 'weighted avg': {'precision': 0.9296886905981827, 'recall': 0.9330453563714903, 'f1-score': 0.929863608439137, 'support': 1852.0}} |
| 0.0009 | 47.0 | 4606 | 0.4778 | {'0': {'precision': 0.9464394400486914, 'recall': 0.9767587939698492, 'f1-score': 0.9613601236476044, 'support': 1592.0}, '1': {'precision': 0.8229665071770335, 'recall': 0.6615384615384615, 'f1-score': 0.7334754797441365, 'support': 260.0}, 'accuracy': 0.9325053995680346, 'macro avg': {'precision': 0.8847029736128624, 'recall': 0.8191486277541553, 'f1-score': 0.8474178016958704, 'support': 1852.0}, 'weighted avg': {'precision': 0.9291052270105536, 'recall': 0.9325053995680346, 'f1-score': 0.9293676790391261, 'support': 1852.0}} |
| 0.0009 | 48.0 | 4704 | 0.4644 | {'0': {'precision': 0.9476567255021302, 'recall': 0.9780150753768844, 'f1-score': 0.962596599690881, 'support': 1592.0}, '1': {'precision': 0.8325358851674641, 'recall': 0.6692307692307692, 'f1-score': 0.7420042643923241, 'support': 260.0}, 'accuracy': 0.9346652267818575, 'macro avg': {'precision': 0.8900963053347972, 'recall': 0.8236229223038267, 'f1-score': 0.8523004320416026, 'support': 1852.0}, 'weighted avg': {'precision': 0.931495052452987, 'recall': 0.9346652267818575, 'f1-score': 0.931627913309874, 'support': 1852.0}} |
| 0.0009 | 49.0 | 4802 | 0.4673 | {'0': {'precision': 0.946983546617916, 'recall': 0.9761306532663316, 'f1-score': 0.9613362202288895, 'support': 1592.0}, '1': {'precision': 0.8199052132701422, 'recall': 0.6653846153846154, 'f1-score': 0.7346072186836518, 'support': 260.0}, 'accuracy': 0.9325053995680346, 'macro avg': {'precision': 0.883444379944029, 'recall': 0.8207576343254734, 'f1-score': 0.8479717194562706, 'support': 1852.0}, 'weighted avg': {'precision': 0.9291431758455503, 'recall': 0.9325053995680346, 'f1-score': 0.9295060148283701, 'support': 1852.0}} |
| 0.0009 | 50.0 | 4900 | 0.4687 | {'0': {'precision': 0.9499083689676237, 'recall': 0.9767587939698492, 'f1-score': 0.9631464849798699, 'support': 1592.0}, '1': {'precision': 0.827906976744186, 'recall': 0.6846153846153846, 'f1-score': 0.7494736842105263, 'support': 260.0}, 'accuracy': 0.9357451403887689, 'macro avg': {'precision': 0.8889076728559049, 'recall': 0.8306870892926169, 'f1-score': 0.8563100845951981, 'support': 1852.0}, 'weighted avg': {'precision': 0.9327807437094736, 'recall': 0.9357451403887689, 'f1-score': 0.9331492235327697, 'support': 1852.0}} |
Framework versions
- Transformers 4.53.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1