Theoreticallyhugo
/

longformer-sep_tok_full_labels

@@ -17,12 +17,12 @@ model-index:
       name: essays_su_g
       type: essays_su_g
       config: sep_tok_full_labels
-      split: train[80%:100%]
       args: sep_tok_full_labels
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9049991583908433
 ---
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,17 +32,17 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the essays_su_g dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8387
-- B-claim: {'precision': 0.6836363636363636, 'recall': 0.6937269372693727, 'f1-score': 0.6886446886446888, 'support': 271.0}
-- B-majorclaim: {'precision': 0.8958333333333334, 'recall': 0.9280575539568345, 'f1-score': 0.9116607773851589, 'support': 139.0}
-- B-premise: {'precision': 0.8878205128205128, 'recall': 0.8751974723538705, 'f1-score': 0.8814638027048528, 'support': 633.0}
-- I-claim: {'precision': 0.677737415672029, 'recall': 0.6528367908022994, 'f1-score': 0.6650541056651814, 'support': 4001.0}
-- I-majorclaim: {'precision': 0.9105447276361819, 'recall': 0.905116741182315, 'f1-score': 0.9078226208271052, 'support': 2013.0}
-- I-premise: {'precision': 0.8930839495432796, 'recall': 0.9056104446012703, 'f1-score': 0.8993035784678727, 'support': 11336.0}
-- O: {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}
-- Accuracy: 0.9050
-- Macro avg: {'precision': 0.8498080432345286, 'recall': 0.8515065628808518, 'f1-score': 0.8505642248135514, 'support': 29705.0}
-- Weighted avg: {'precision': 0.903966681075651, 'recall': 0.9049991583908433, 'f1-score': 0.9044317092676175, 'support': 29705.0}
 ## Model description
@@ -67,62 +67,32 @@ The following hyperparameters were used during training:
 - 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-claim                                                                                                           | B-majorclaim                                                                                                      | B-premise                                                                                                         | I-claim                                                                                                            | I-majorclaim                                                                                                       | I-premise                                                                                                           | O                                                                                                                   | Accuracy | Macro avg                                                                                                           | Weighted avg                                                                                                        |
-|:-------------:|:-----:|:----:|:---------------:|:-----------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:--------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
-| No log        | 1.0   | 81   | 0.3171          | {'precision': 0.42788461538461536, 'recall': 0.3284132841328413, 'f1-score': 0.37160751565762, 'support': 271.0}  | {'precision': 0.6666666666666666, 'recall': 0.2446043165467626, 'f1-score': 0.3578947368421052, 'support': 139.0} | {'precision': 0.7895424836601307, 'recall': 0.9541864139020537, 'f1-score': 0.8640915593705293, 'support': 633.0} | {'precision': 0.5493126120741183, 'recall': 0.4593851537115721, 'f1-score': 0.5003402749421533, 'support': 4001.0} | {'precision': 0.6502211636611093, 'recall': 0.9493293591654247, 'f1-score': 0.7718093699515347, 'support': 2013.0} | {'precision': 0.8846812731043188, 'recall': 0.865561044460127, 'f1-score': 0.875016720916752, 'support': 11336.0}   | {'precision': 0.9995577178239717, 'recall': 0.998939179632249, 'f1-score': 0.9992483530087988, 'support': 11312.0}  | 0.8614   | {'precision': 0.7096952189107044, 'recall': 0.685774107364433, 'f1-score': 0.6771440758127848, 'support': 29705.0}  | {'precision': 0.8601529227027923, 'recall': 0.8614038040733883, 'f1-score': 0.8576207231627551, 'support': 29705.0} |
-| No log        | 2.0   | 162  | 0.2966          | {'precision': 0.6392405063291139, 'recall': 0.3726937269372694, 'f1-score': 0.4708624708624709, 'support': 271.0} | {'precision': 0.8717948717948718, 'recall': 0.7338129496402878, 'f1-score': 0.796875, 'support': 139.0}           | {'precision': 0.796875, 'recall': 0.966824644549763, 'f1-score': 0.8736616702355461, 'support': 633.0}            | {'precision': 0.6459770114942529, 'recall': 0.4213946513371657, 'f1-score': 0.5100589925881107, 'support': 4001.0} | {'precision': 0.9077277970011534, 'recall': 0.7819175360158966, 'f1-score': 0.8401387776888176, 'support': 2013.0} | {'precision': 0.8338584492430646, 'recall': 0.9572159491884262, 'f1-score': 0.8912891699864469, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9993811881188119, 'f1-score': 0.9996904982977407, 'support': 11312.0}                | 0.8830   | {'precision': 0.8136390908374939, 'recall': 0.7476058065410885, 'f1-score': 0.7689395113798762, 'support': 29705.0} | {'precision': 0.874440834821272, 'recall': 0.8830499915839084, 'f1-score': 0.8731020208182413, 'support': 29705.0}  |
-| No log        | 3.0   | 243  | 0.2553          | {'precision': 0.6756756756756757, 'recall': 0.5535055350553506, 'f1-score': 0.6085192697768763, 'support': 271.0} | {'precision': 0.851063829787234, 'recall': 0.8633093525179856, 'f1-score': 0.8571428571428571, 'support': 139.0}  | {'precision': 0.8529411764705882, 'recall': 0.9162717219589257, 'f1-score': 0.8834729626808834, 'support': 633.0} | {'precision': 0.6584269662921348, 'recall': 0.5126218445388653, 'f1-score': 0.5764474423833614, 'support': 4001.0} | {'precision': 0.9070282235749861, 'recall': 0.8142076502732241, 'f1-score': 0.8581151832460733, 'support': 2013.0} | {'precision': 0.8563158317922328, 'recall': 0.939484827099506, 'f1-score': 0.8959744247675935, 'support': 11336.0}  | {'precision': 1.0, 'recall': 0.9992043847241867, 'f1-score': 0.9996020340481981, 'support': 11312.0}                | 0.8919   | {'precision': 0.8287788147989789, 'recall': 0.7998007594525776, 'f1-score': 0.811324882006549, 'support': 29705.0}  | {'precision': 0.886070631898416, 'recall': 0.8918700555462044, 'f1-score': 0.8867633844066056, 'support': 29705.0}  |
-| No log        | 4.0   | 324  | 0.2947          | {'precision': 0.6146788990825688, 'recall': 0.7416974169741697, 'f1-score': 0.6722408026755852, 'support': 271.0} | {'precision': 0.8695652173913043, 'recall': 0.8633093525179856, 'f1-score': 0.8664259927797834, 'support': 139.0} | {'precision': 0.9100346020761245, 'recall': 0.8309636650868878, 'f1-score': 0.8687035507844755, 'support': 633.0} | {'precision': 0.6171222046532641, 'recall': 0.6828292926768308, 'f1-score': 0.6483151400094921, 'support': 4001.0} | {'precision': 0.9009584664536742, 'recall': 0.8405365126676602, 'f1-score': 0.8696993060909791, 'support': 2013.0} | {'precision': 0.9020175517958925, 'recall': 0.879498941425547, 'f1-score': 0.8906159274643798, 'support': 11336.0}  | {'precision': 0.9999115357395613, 'recall': 0.9992043847241867, 'f1-score': 0.999557835160948, 'support': 11312.0}  | 0.8936   | {'precision': 0.8306126395989127, 'recall': 0.8340056522961811, 'f1-score': 0.8307940792808061, 'support': 29705.0} | {'precision': 0.8982496227307208, 'recall': 0.8935869382258879, 'f1-score': 0.8954766464091573, 'support': 29705.0} |
-| No log        | 5.0   | 405  | 0.3177          | {'precision': 0.6653543307086615, 'recall': 0.6236162361623616, 'f1-score': 0.6438095238095239, 'support': 271.0} | {'precision': 0.8723404255319149, 'recall': 0.8848920863309353, 'f1-score': 0.8785714285714286, 'support': 139.0} | {'precision': 0.8674884437596302, 'recall': 0.8894154818325435, 'f1-score': 0.8783151326053042, 'support': 633.0} | {'precision': 0.6748923959827834, 'recall': 0.5878530367408148, 'f1-score': 0.6283729628640129, 'support': 4001.0} | {'precision': 0.8896690070210632, 'recall': 0.8812717337307501, 'f1-score': 0.885450461692039, 'support': 2013.0}  | {'precision': 0.878494442573257, 'recall': 0.9203422724064926, 'f1-score': 0.8989315871101154, 'support': 11336.0}  | {'precision': 1.0, 'recall': 0.9994695898161244, 'f1-score': 0.9997347245556637, 'support': 11312.0}                | 0.8995   | {'precision': 0.8354627207967587, 'recall': 0.8266943481457174, 'f1-score': 0.830455117315441, 'support': 29705.0}  | {'precision': 0.8958911872123141, 'recall': 0.8995118666891095, 'f1-score': 0.8971010593476484, 'support': 29705.0} |
-| No log        | 6.0   | 486  | 0.4107          | {'precision': 0.6863636363636364, 'recall': 0.5571955719557196, 'f1-score': 0.6150712830957231, 'support': 271.0} | {'precision': 0.8814814814814815, 'recall': 0.8561151079136691, 'f1-score': 0.8686131386861314, 'support': 139.0} | {'precision': 0.8447024673439768, 'recall': 0.919431279620853, 'f1-score': 0.8804841149773072, 'support': 633.0}  | {'precision': 0.6739276139410187, 'recall': 0.5026243439140214, 'f1-score': 0.5758052970651396, 'support': 4001.0} | {'precision': 0.8992456896551724, 'recall': 0.829110779930452, 'f1-score': 0.8627552339105711, 'support': 2013.0}  | {'precision': 0.8521864257734432, 'recall': 0.9403669724770642, 'f1-score': 0.894107779408681, 'support': 11336.0}  | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.8922   | {'precision': 0.8339867592226755, 'recall': 0.8006920079731114, 'f1-score': 0.8138338353062219, 'support': 29705.0} | {'precision': 0.8861194550557427, 'recall': 0.8922403635751557, 'f1-score': 0.8864802913843919, 'support': 29705.0} |
-| 0.2363        | 7.0   | 567  | 0.3521          | {'precision': 0.6795774647887324, 'recall': 0.7121771217712177, 'f1-score': 0.6954954954954955, 'support': 271.0} | {'precision': 0.8920863309352518, 'recall': 0.8920863309352518, 'f1-score': 0.8920863309352518, 'support': 139.0} | {'precision': 0.8954983922829582, 'recall': 0.8799368088467614, 'f1-score': 0.8876494023904382, 'support': 633.0} | {'precision': 0.6898572884811417, 'recall': 0.6765808547863035, 'f1-score': 0.6831545741324923, 'support': 4001.0} | {'precision': 0.9068825910931174, 'recall': 0.8902136115250869, 'f1-score': 0.8984707946853848, 'support': 2013.0} | {'precision': 0.9024198479951079, 'recall': 0.9112561750176429, 'f1-score': 0.9068164859763859, 'support': 11336.0} | {'precision': 0.9999116061168567, 'recall': 1.0, 'f1-score': 0.9999558011049724, 'support': 11312.0}                | 0.9094   | {'precision': 0.8523190745275951, 'recall': 0.8517501289831806, 'f1-score': 0.8519469835314888, 'support': 29705.0} | {'precision': 0.908989097041669, 'recall': 0.9094428547382596, 'f1-score': 0.9091888981291354, 'support': 29705.0}  |
-| 0.2363        | 8.0   | 648  | 0.4632          | {'precision': 0.658273381294964, 'recall': 0.6752767527675276, 'f1-score': 0.6666666666666667, 'support': 271.0}  | {'precision': 0.8523489932885906, 'recall': 0.9136690647482014, 'f1-score': 0.8819444444444444, 'support': 139.0} | {'precision': 0.887987012987013, 'recall': 0.8641390205371248, 'f1-score': 0.8759007205764612, 'support': 633.0}  | {'precision': 0.6353631694790902, 'recall': 0.6493376655836041, 'f1-score': 0.642274412855377, 'support': 4001.0}  | {'precision': 0.862914862914863, 'recall': 0.8912071535022354, 'f1-score': 0.87683284457478, 'support': 2013.0}    | {'precision': 0.8972547616918537, 'recall': 0.8851446718419196, 'f1-score': 0.8911585772014743, 'support': 11336.0} | {'precision': 0.9999115904871364, 'recall': 0.9998231966053748, 'f1-score': 0.9998673915926268, 'support': 11312.0} | 0.8952   | {'precision': 0.827721967449073, 'recall': 0.8397996465122839, 'f1-score': 0.8335207225588329, 'support': 29705.0}  | {'precision': 0.8961582200263131, 'recall': 0.8952364921730348, 'f1-score': 0.8956465277692122, 'support': 29705.0} |
-| 0.2363        | 9.0   | 729  | 0.5578          | {'precision': 0.6717557251908397, 'recall': 0.6494464944649446, 'f1-score': 0.6604127579737337, 'support': 271.0} | {'precision': 0.9565217391304348, 'recall': 0.7913669064748201, 'f1-score': 0.8661417322834645, 'support': 139.0} | {'precision': 0.8633633633633634, 'recall': 0.9083728278041074, 'f1-score': 0.8852963818321786, 'support': 633.0} | {'precision': 0.6512017887087759, 'recall': 0.5823544113971507, 'f1-score': 0.6148568412719356, 'support': 4001.0} | {'precision': 0.957089552238806, 'recall': 0.7645305514157973, 'f1-score': 0.8500414250207126, 'support': 2013.0}  | {'precision': 0.8677183468901487, 'recall': 0.9316337332392378, 'f1-score': 0.8985408601693112, 'support': 11336.0} | {'precision': 0.9998230871295887, 'recall': 0.9992043847241867, 'f1-score': 0.9995136401821638, 'support': 11312.0} | 0.8953   | {'precision': 0.8524962289502797, 'recall': 0.8038441870743206, 'f1-score': 0.8249719483905, 'support': 29705.0}    | {'precision': 0.8934537922744324, 'recall': 0.8952701565393032, 'f1-score': 0.8928897918536849, 'support': 29705.0} |
-| 0.2363        | 10.0  | 810  | 0.6302          | {'precision': 0.6690647482014388, 'recall': 0.6863468634686347, 'f1-score': 0.6775956284153005, 'support': 271.0} | {'precision': 0.8962962962962963, 'recall': 0.8705035971223022, 'f1-score': 0.8832116788321168, 'support': 139.0} | {'precision': 0.8841269841269841, 'recall': 0.8799368088467614, 'f1-score': 0.8820269200316706, 'support': 633.0} | {'precision': 0.6542031291434632, 'recall': 0.6165958510372407, 'f1-score': 0.6348430262480701, 'support': 4001.0} | {'precision': 0.896797153024911, 'recall': 0.8763040238450075, 'f1-score': 0.8864321608040201, 'support': 2013.0}  | {'precision': 0.8828797795384086, 'recall': 0.9043754410726887, 'f1-score': 0.8934983440822729, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.8975   | {'precision': 0.8404811557616432, 'recall': 0.8334375121989479, 'f1-score': 0.8368011083447787, 'support': 29705.0} | {'precision': 0.895761611933671, 'recall': 0.897458340346743, 'f1-score': 0.8964756773362035, 'support': 29705.0}   |
-| 0.2363        | 11.0  | 891  | 0.5968          | {'precision': 0.6932773109243697, 'recall': 0.6088560885608856, 'f1-score': 0.6483300589390962, 'support': 271.0} | {'precision': 0.9147286821705426, 'recall': 0.8489208633093526, 'f1-score': 0.8805970149253732, 'support': 139.0} | {'precision': 0.855457227138643, 'recall': 0.9162717219589257, 'f1-score': 0.8848207475209764, 'support': 633.0}  | {'precision': 0.6995936230071897, 'recall': 0.55936015996001, 'f1-score': 0.6216666666666667, 'support': 4001.0}   | {'precision': 0.9381499726327313, 'recall': 0.851465474416294, 'f1-score': 0.8927083333333333, 'support': 2013.0}  | {'precision': 0.8655250770978737, 'recall': 0.9408080451658434, 'f1-score': 0.9015977681968045, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9019   | {'precision': 0.8523902704244785, 'recall': 0.8179546219101873, 'f1-score': 0.8328172270831785, 'support': 29705.0} | {'precision': 0.8977509549706758, 'recall': 0.9019357010604275, 'f1-score': 0.8979974574260295, 'support': 29705.0} |
-| 0.2363        | 12.0  | 972  | 0.6402          | {'precision': 0.5916230366492147, 'recall': 0.8339483394833949, 'f1-score': 0.6921898928024502, 'support': 271.0} | {'precision': 0.9111111111111111, 'recall': 0.8848920863309353, 'f1-score': 0.8978102189781022, 'support': 139.0} | {'precision': 0.9335863377609108, 'recall': 0.7772511848341233, 'f1-score': 0.8482758620689655, 'support': 633.0} | {'precision': 0.5854598861758766, 'recall': 0.7970507373156711, 'f1-score': 0.6750635055038103, 'support': 4001.0} | {'precision': 0.9157566302652106, 'recall': 0.8748137108792846, 'f1-score': 0.8948170731707318, 'support': 2013.0} | {'precision': 0.9336606874436316, 'recall': 0.821894848270995, 'f1-score': 0.8742200328407225, 'support': 11336.0}  | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.8894   | {'precision': 0.8387425270579937, 'recall': 0.8556929867306292, 'f1-score': 0.8403395121949689, 'support': 29705.0} | {'precision': 0.9075830699664568, 'recall': 0.8894125568086181, 'f1-score': 0.8945864954779644, 'support': 29705.0} |
-| 0.0272        | 13.0  | 1053 | 0.6060          | {'precision': 0.7203065134099617, 'recall': 0.6937269372693727, 'f1-score': 0.706766917293233, 'support': 271.0}  | {'precision': 0.8657718120805369, 'recall': 0.9280575539568345, 'f1-score': 0.8958333333333333, 'support': 139.0} | {'precision': 0.8957345971563981, 'recall': 0.8957345971563981, 'f1-score': 0.8957345971563981, 'support': 633.0} | {'precision': 0.7096169300830432, 'recall': 0.6620844788802799, 'f1-score': 0.6850271528316524, 'support': 4001.0} | {'precision': 0.8861553304389773, 'recall': 0.912568306010929, 'f1-score': 0.8991678903573177, 'support': 2013.0}  | {'precision': 0.9007362494586401, 'recall': 0.9173429781227946, 'f1-score': 0.9089637690660374, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9999115983026874, 'f1-score': 0.9999557971975424, 'support': 11312.0}                | 0.9116   | {'precision': 0.8540459189467938, 'recall': 0.8584894928141853, 'f1-score': 0.855921351033645, 'support': 29705.0}  | {'precision': 0.9098905735839876, 'recall': 0.9116310385456994, 'f1-score': 0.9106004556040976, 'support': 29705.0} |
-| 0.0272        | 14.0  | 1134 | 0.6457          | {'precision': 0.6597938144329897, 'recall': 0.7084870848708487, 'f1-score': 0.6832740213523131, 'support': 271.0} | {'precision': 0.924812030075188, 'recall': 0.8848920863309353, 'f1-score': 0.9044117647058822, 'support': 139.0}  | {'precision': 0.8852988691437803, 'recall': 0.8657187993680885, 'f1-score': 0.8753993610223643, 'support': 633.0} | {'precision': 0.6453178068898593, 'recall': 0.664833791552112, 'f1-score': 0.6549304444170873, 'support': 4001.0}  | {'precision': 0.9214248297537978, 'recall': 0.8738201689021361, 'f1-score': 0.8969913309535952, 'support': 2013.0} | {'precision': 0.8927467090732397, 'recall': 0.891407904022583, 'f1-score': 0.8920768042374753, 'support': 11336.0}  | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.8988   | {'precision': 0.8470562941955507, 'recall': 0.8413085478638147, 'f1-score': 0.8438691038126739, 'support': 29705.0} | {'precision': 0.900073004604436, 'recall': 0.8988049149974752, 'f1-score': 0.8993641205442222, 'support': 29705.0}  |
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-| 0.0031        | 34.0  | 2754 | 0.8031          | {'precision': 0.6808510638297872, 'recall': 0.7084870848708487, 'f1-score': 0.6943942133815552, 'support': 271.0} | {'precision': 0.8992805755395683, 'recall': 0.8992805755395683, 'f1-score': 0.8992805755395683, 'support': 139.0} | {'precision': 0.8922829581993569, 'recall': 0.8767772511848341, 'f1-score': 0.8844621513944222, 'support': 633.0} | {'precision': 0.6755521706016756, 'recall': 0.665083729067733, 'f1-score': 0.6702770780856424, 'support': 4001.0}  | {'precision': 0.9096509240246407, 'recall': 0.8802781917536016, 'f1-score': 0.8947235546579146, 'support': 2013.0} | {'precision': 0.8967111576376167, 'recall': 0.9067572335920959, 'f1-score': 0.9017062151848765, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9054   | {'precision': 0.8506184071189493, 'recall': 0.8480948665726687, 'f1-score': 0.8492633983205684, 'support': 29705.0} | {'precision': 0.9050818036848003, 'recall': 0.9054367951523312, 'f1-score': 0.905222828949398, 'support': 29705.0}  |
-| 0.0031        | 35.0  | 2835 | 0.7647          | {'precision': 0.6786885245901639, 'recall': 0.7638376383763837, 'f1-score': 0.7187499999999999, 'support': 271.0} | {'precision': 0.9191176470588235, 'recall': 0.8992805755395683, 'f1-score': 0.909090909090909, 'support': 139.0}  | {'precision': 0.9086378737541528, 'recall': 0.8641390205371248, 'f1-score': 0.88582995951417, 'support': 633.0}   | {'precision': 0.667352067626228, 'recall': 0.7300674831292177, 'f1-score': 0.697302458820721, 'support': 4001.0}   | {'precision': 0.92, 'recall': 0.8912071535022354, 'f1-score': 0.9053747161241484, 'support': 2013.0}               | {'precision': 0.9148144788170189, 'recall': 0.8895553987297107, 'f1-score': 0.9020081398989221, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9086   | {'precision': 0.858372941692341, 'recall': 0.8625838956877485, 'f1-score': 0.8597651690641243, 'support': 29705.0}  | {'precision': 0.9120088292083405, 'recall': 0.908601245581552, 'f1-score': 0.9099971710462852, 'support': 29705.0}  |
-| 0.0031        | 36.0  | 2916 | 0.7716          | {'precision': 0.6842105263157895, 'recall': 0.7195571955719557, 'f1-score': 0.7014388489208633, 'support': 271.0} | {'precision': 0.9124087591240876, 'recall': 0.8992805755395683, 'f1-score': 0.9057971014492754, 'support': 139.0} | {'precision': 0.893719806763285, 'recall': 0.8767772511848341, 'f1-score': 0.8851674641148325, 'support': 633.0}  | {'precision': 0.6749757986447241, 'recall': 0.6970757310672332, 'f1-score': 0.6858477806467478, 'support': 4001.0} | {'precision': 0.9278567667193259, 'recall': 0.8753104818678589, 'f1-score': 0.9008179959100204, 'support': 2013.0} | {'precision': 0.9037017404364344, 'recall': 0.9023465067043048, 'f1-score': 0.9030236150960054, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9078   | {'precision': 0.8566961997148067, 'recall': 0.8529068202765364, 'f1-score': 0.8545846865911064, 'support': 29705.0} | {'precision': 0.9090283547955545, 'recall': 0.9078269651573809, 'f1-score': 0.9083455992865349, 'support': 29705.0} |
-| 0.0031        | 37.0  | 2997 | 0.8116          | {'precision': 0.6801346801346801, 'recall': 0.7453874538745388, 'f1-score': 0.7112676056338029, 'support': 271.0} | {'precision': 0.9027777777777778, 'recall': 0.935251798561151, 'f1-score': 0.9187279151943463, 'support': 139.0}  | {'precision': 0.9053156146179402, 'recall': 0.8609794628751974, 'f1-score': 0.8825910931174089, 'support': 633.0} | {'precision': 0.6671418389166073, 'recall': 0.701824543864034, 'f1-score': 0.6840438489646773, 'support': 4001.0}  | {'precision': 0.9099409448818898, 'recall': 0.9185295578738202, 'f1-score': 0.9142150803461063, 'support': 2013.0} | {'precision': 0.9075524349626429, 'recall': 0.889378969654199, 'f1-score': 0.8983738026286477, 'support': 11336.0}  | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9065   | {'precision': 0.8532661844702197, 'recall': 0.8644788266718487, 'f1-score': 0.8584599065549984, 'support': 29705.0} | {'precision': 0.9083934494452071, 'recall': 0.906514054872917, 'f1-score': 0.907331314133137, 'support': 29705.0}   |
-| 0.0017        | 38.0  | 3078 | 0.8268          | {'precision': 0.7061224489795919, 'recall': 0.6383763837638377, 'f1-score': 0.6705426356589148, 'support': 271.0} | {'precision': 0.9, 'recall': 0.9064748201438849, 'f1-score': 0.903225806451613, 'support': 139.0}                 | {'precision': 0.8693009118541033, 'recall': 0.9036334913112164, 'f1-score': 0.8861347792408986, 'support': 633.0} | {'precision': 0.6944764096662831, 'recall': 0.6033491627093227, 'f1-score': 0.6457135214658286, 'support': 4001.0} | {'precision': 0.9197530864197531, 'recall': 0.8882265275707899, 'f1-score': 0.9037149355572404, 'support': 2013.0} | {'precision': 0.8787929589270747, 'recall': 0.9248412138320395, 'f1-score': 0.9012292615834264, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9045   | {'precision': 0.8526351165495436, 'recall': 0.8378430856187273, 'f1-score': 0.8443658485654174, 'support': 29705.0} | {'precision': 0.9012215694769297, 'recall': 0.904527857263087, 'f1-score': 0.902178139390374, 'support': 29705.0}   |
-| 0.0017        | 39.0  | 3159 | 0.8176          | {'precision': 0.6813559322033899, 'recall': 0.7416974169741697, 'f1-score': 0.7102473498233215, 'support': 271.0} | {'precision': 0.924812030075188, 'recall': 0.8848920863309353, 'f1-score': 0.9044117647058822, 'support': 139.0}  | {'precision': 0.8991869918699187, 'recall': 0.8736176935229067, 'f1-score': 0.8862179487179487, 'support': 633.0} | {'precision': 0.6646820671588474, 'recall': 0.6975756060984754, 'f1-score': 0.6807317073170731, 'support': 4001.0} | {'precision': 0.9273115980758952, 'recall': 0.8618976651763537, 'f1-score': 0.8934088568486096, 'support': 2013.0} | {'precision': 0.9034574468085106, 'recall': 0.8989943542695836, 'f1-score': 0.9012203749557836, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9058   | {'precision': 0.8572580094559642, 'recall': 0.8512392603389178, 'f1-score': 0.8537482860526598, 'support': 29705.0} | {'precision': 0.907660209066212, 'recall': 0.9057734388150143, 'f1-score': 0.9065625311881947, 'support': 29705.0}  |
-| 0.0017        | 40.0  | 3240 | 0.8003          | {'precision': 0.6824324324324325, 'recall': 0.7453874538745388, 'f1-score': 0.7125220458553791, 'support': 271.0} | {'precision': 0.9014084507042254, 'recall': 0.920863309352518, 'f1-score': 0.911032028469751, 'support': 139.0}   | {'precision': 0.9057851239669421, 'recall': 0.8657187993680885, 'f1-score': 0.8852988691437802, 'support': 633.0} | {'precision': 0.6692142345354669, 'recall': 0.7003249187703074, 'f1-score': 0.6844162188568637, 'support': 4001.0} | {'precision': 0.9120603015075377, 'recall': 0.9016393442622951, 'f1-score': 0.9068198850861853, 'support': 2013.0} | {'precision': 0.9068289626778842, 'recall': 0.8937896965419901, 'f1-score': 0.9002621173752722, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9069   | {'precision': 0.8539613579749269, 'recall': 0.8611033603099626, 'f1-score': 0.857193023541033, 'support': 29705.0}  | {'precision': 0.9085646728677234, 'recall': 0.9068843629018684, 'f1-score': 0.9076340748507997, 'support': 29705.0} |
-| 0.0017        | 41.0  | 3321 | 0.8058          | {'precision': 0.6851211072664359, 'recall': 0.7306273062730627, 'f1-score': 0.7071428571428571, 'support': 271.0} | {'precision': 0.900709219858156, 'recall': 0.9136690647482014, 'f1-score': 0.9071428571428571, 'support': 139.0}  | {'precision': 0.9004893964110929, 'recall': 0.8720379146919431, 'f1-score': 0.8860353130016052, 'support': 633.0} | {'precision': 0.6773488710852149, 'recall': 0.6973256685828543, 'f1-score': 0.6871921182266011, 'support': 4001.0} | {'precision': 0.9128256513026052, 'recall': 0.905116741182315, 'f1-score': 0.9089548515839362, 'support': 2013.0}  | {'precision': 0.906186025812194, 'recall': 0.8981122088920254, 'f1-score': 0.9021310531212617, 'support': 11336.0}  | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9083   | {'precision': 0.854668610247957, 'recall': 0.8595555577672004, 'f1-score': 0.856942721459874, 'support': 29705.0}   | {'precision': 0.9093752515552543, 'recall': 0.9083319306514055, 'f1-score': 0.9088142845986974, 'support': 29705.0} |
-| 0.0017        | 42.0  | 3402 | 0.8090          | {'precision': 0.6890459363957597, 'recall': 0.7195571955719557, 'f1-score': 0.703971119133574, 'support': 271.0}  | {'precision': 0.9014084507042254, 'recall': 0.920863309352518, 'f1-score': 0.911032028469751, 'support': 139.0}   | {'precision': 0.8964401294498382, 'recall': 0.8751974723538705, 'f1-score': 0.8856914468425259, 'support': 633.0} | {'precision': 0.6821686147724446, 'recall': 0.6855786053486629, 'f1-score': 0.6838693592620294, 'support': 4001.0} | {'precision': 0.9121485943775101, 'recall': 0.9026328862394436, 'f1-score': 0.9073657927590512, 'support': 2013.0} | {'precision': 0.9029725676986857, 'recall': 0.9030522230063515, 'f1-score': 0.9030123935959069, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9085   | {'precision': 0.8548834704854948, 'recall': 0.858125955981829, 'f1-score': 0.8564203057232626, 'support': 29705.0}  | {'precision': 0.9087050193897211, 'recall': 0.9084665881164787, 'f1-score': 0.9085773254377499, 'support': 29705.0} |
-| 0.0017        | 43.0  | 3483 | 0.8238          | {'precision': 0.6967509025270758, 'recall': 0.7121771217712177, 'f1-score': 0.7043795620437956, 'support': 271.0} | {'precision': 0.8951048951048951, 'recall': 0.920863309352518, 'f1-score': 0.9078014184397164, 'support': 139.0}  | {'precision': 0.8956661316211878, 'recall': 0.8815165876777251, 'f1-score': 0.8885350318471338, 'support': 633.0} | {'precision': 0.6917954182205648, 'recall': 0.649087728067983, 'f1-score': 0.6697614442295293, 'support': 4001.0}  | {'precision': 0.9102564102564102, 'recall': 0.9170392449080974, 'f1-score': 0.9136352388022766, 'support': 2013.0} | {'precision': 0.8928941908713693, 'recall': 0.9111679604798871, 'f1-score': 0.9019385260216556, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9077   | {'precision': 0.8546382783716434, 'recall': 0.8559788503224899, 'f1-score': 0.855150174483444, 'support': 29705.0}  | {'precision': 0.9060516379796367, 'recall': 0.9076923076923077, 'f1-score': 0.9067413680757126, 'support': 29705.0} |
-| 0.0007        | 44.0  | 3564 | 0.8489          | {'precision': 0.6810035842293907, 'recall': 0.7011070110701108, 'f1-score': 0.6909090909090909, 'support': 271.0} | {'precision': 0.9191176470588235, 'recall': 0.8992805755395683, 'f1-score': 0.909090909090909, 'support': 139.0}  | {'precision': 0.8869426751592356, 'recall': 0.8799368088467614, 'f1-score': 0.8834258524980174, 'support': 633.0} | {'precision': 0.6790486370924639, 'recall': 0.6350912271932017, 'f1-score': 0.6563347539713289, 'support': 4001.0} | {'precision': 0.9198355601233299, 'recall': 0.8892200695479384, 'f1-score': 0.9042687547360444, 'support': 2013.0} | {'precision': 0.8868976161893328, 'recall': 0.9124029640084685, 'f1-score': 0.8994695190886163, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9042   | {'precision': 0.8532636742646538, 'recall': 0.8452912366008641, 'f1-score': 0.8490712686134296, 'support': 29705.0} | {'precision': 0.9024783031240742, 'recall': 0.9041575492341357, 'f1-score': 0.9031302267949082, 'support': 29705.0} |
-| 0.0007        | 45.0  | 3645 | 0.8230          | {'precision': 0.6802721088435374, 'recall': 0.7380073800738007, 'f1-score': 0.7079646017699115, 'support': 271.0} | {'precision': 0.9191176470588235, 'recall': 0.8992805755395683, 'f1-score': 0.909090909090909, 'support': 139.0}  | {'precision': 0.9004893964110929, 'recall': 0.8720379146919431, 'f1-score': 0.8860353130016052, 'support': 633.0} | {'precision': 0.6757232704402516, 'recall': 0.6713321669582605, 'f1-score': 0.6735205616850551, 'support': 4001.0} | {'precision': 0.9140823589222166, 'recall': 0.8931942374565326, 'f1-score': 0.9035175879396985, 'support': 2013.0} | {'precision': 0.8982293127629734, 'recall': 0.9039343683839096, 'f1-score': 0.9010728104115371, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9062   | {'precision': 0.8554162992055565, 'recall': 0.8539695204434308, 'f1-score': 0.8544573976998165, 'support': 29705.0} | {'precision': 0.9062469269614183, 'recall': 0.9062447399427705, 'f1-score': 0.9062171502179094, 'support': 29705.0} |
-| 0.0007        | 46.0  | 3726 | 0.8292          | {'precision': 0.6906474820143885, 'recall': 0.7084870848708487, 'f1-score': 0.6994535519125684, 'support': 271.0} | {'precision': 0.9014084507042254, 'recall': 0.920863309352518, 'f1-score': 0.911032028469751, 'support': 139.0}   | {'precision': 0.8924558587479936, 'recall': 0.8783570300157978, 'f1-score': 0.8853503184713376, 'support': 633.0} | {'precision': 0.6758923952405587, 'recall': 0.6530867283179205, 'f1-score': 0.6642938858522944, 'support': 4001.0} | {'precision': 0.9075, 'recall': 0.9016393442622951, 'f1-score': 0.9045601794168949, 'support': 2013.0}             | {'precision': 0.8936781609195402, 'recall': 0.9053458009880028, 'f1-score': 0.8994741454864154, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9049   | {'precision': 0.8516546210895294, 'recall': 0.852539899686769, 'f1-score': 0.8520234442298945, 'support': 29705.0}  | {'precision': 0.9039274333076133, 'recall': 0.9048645009257701, 'f1-score': 0.9043518097227135, 'support': 29705.0} |
-| 0.0007        | 47.0  | 3807 | 0.8382          | {'precision': 0.6897810218978102, 'recall': 0.6974169741697417, 'f1-score': 0.6935779816513761, 'support': 271.0} | {'precision': 0.9148936170212766, 'recall': 0.9280575539568345, 'f1-score': 0.9214285714285715, 'support': 139.0} | {'precision': 0.8853503184713376, 'recall': 0.8783570300157978, 'f1-score': 0.8818398096748612, 'support': 633.0} | {'precision': 0.6771135106663155, 'recall': 0.6425893526618346, 'f1-score': 0.6593998461143883, 'support': 4001.0} | {'precision': 0.9121485943775101, 'recall': 0.9026328862394436, 'f1-score': 0.9073657927590512, 'support': 2013.0} | {'precision': 0.8901479110803564, 'recall': 0.9078158080451658, 'f1-score': 0.8988950517535048, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9044   | {'precision': 0.8527764247878009, 'recall': 0.8509813721555455, 'f1-score': 0.8517867219116791, 'support': 29705.0} | {'precision': 0.902963494965743, 'recall': 0.9043931997980138, 'f1-score': 0.9035819975016209, 'support': 29705.0}  |
-| 0.0007        | 48.0  | 3888 | 0.8516          | {'precision': 0.6992481203007519, 'recall': 0.6863468634686347, 'f1-score': 0.6927374301675978, 'support': 271.0} | {'precision': 0.9148936170212766, 'recall': 0.9280575539568345, 'f1-score': 0.9214285714285715, 'support': 139.0} | {'precision': 0.8820754716981132, 'recall': 0.8862559241706162, 'f1-score': 0.8841607565011821, 'support': 633.0} | {'precision': 0.6937745372966909, 'recall': 0.6183454136465883, 'f1-score': 0.6538918990352848, 'support': 4001.0} | {'precision': 0.9121044701155199, 'recall': 0.9021361152508693, 'f1-score': 0.9070929070929071, 'support': 2013.0} | {'precision': 0.884083778512677, 'recall': 0.9197247706422018, 'f1-score': 0.9015521639500194, 'support': 11336.0}  | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9057   | {'precision': 0.8551685707064328, 'recall': 0.8486952344479636, 'f1-score': 0.8515519611679376, 'support': 29705.0} | {'precision': 0.9029069908176629, 'recall': 0.9057061100824777, 'f1-score': 0.9038774285280207, 'support': 29705.0} |
-| 0.0007        | 49.0  | 3969 | 0.8406          | {'precision': 0.6897810218978102, 'recall': 0.6974169741697417, 'f1-score': 0.6935779816513761, 'support': 271.0} | {'precision': 0.9020979020979021, 'recall': 0.9280575539568345, 'f1-score': 0.9148936170212766, 'support': 139.0} | {'precision': 0.8881789137380192, 'recall': 0.8783570300157978, 'f1-score': 0.8832406671961874, 'support': 633.0} | {'precision': 0.6768388106416275, 'recall': 0.6485878530367408, 'f1-score': 0.6624122527121888, 'support': 4001.0} | {'precision': 0.9107769423558897, 'recall': 0.9026328862394436, 'f1-score': 0.906686626746507, 'support': 2013.0}  | {'precision': 0.8918496658276192, 'recall': 0.9064043754410727, 'f1-score': 0.8990681191757448, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9047   | {'precision': 0.8513604652226955, 'recall': 0.8516366675513759, 'f1-score': 0.8514113235004687, 'support': 29705.0} | {'precision': 0.9034833662980484, 'recall': 0.9046625147281603, 'f1-score': 0.904007035510759, 'support': 29705.0}  |
-| 0.0004        | 50.0  | 4050 | 0.8387          | {'precision': 0.6836363636363636, 'recall': 0.6937269372693727, 'f1-score': 0.6886446886446888, 'support': 271.0} | {'precision': 0.8958333333333334, 'recall': 0.9280575539568345, 'f1-score': 0.9116607773851589, 'support': 139.0} | {'precision': 0.8878205128205128, 'recall': 0.8751974723538705, 'f1-score': 0.8814638027048528, 'support': 633.0} | {'precision': 0.677737415672029, 'recall': 0.6528367908022994, 'f1-score': 0.6650541056651814, 'support': 4001.0}  | {'precision': 0.9105447276361819, 'recall': 0.905116741182315, 'f1-score': 0.9078226208271052, 'support': 2013.0}  | {'precision': 0.8930839495432796, 'recall': 0.9056104446012703, 'f1-score': 0.8993035784678727, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.9050   | {'precision': 0.8498080432345286, 'recall': 0.8515065628808518, 'f1-score': 0.8505642248135514, 'support': 29705.0} | {'precision': 0.903966681075651, 'recall': 0.9049991583908433, 'f1-score': 0.9044317092676175, 'support': 29705.0}  |
 ### Framework versions

       name: essays_su_g
       type: essays_su_g
       config: sep_tok_full_labels
+      split: train[0%:20%]
       args: sep_tok_full_labels
     metrics:
     - name: Accuracy
       type: accuracy
+      value: 0.9077215189873418
 ---
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/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
 - 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

meta_data/README_s42_e20.md ADDED Viewed

	@@ -0,0 +1,103 @@

+---
+license: apache-2.0
+base_model: allenai/longformer-base-4096
+tags:
+- generated_from_trainer
+datasets:
+- essays_su_g
+metrics:
+- accuracy
+model-index:
+- name: longformer-sep_tok_full_labels
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: essays_su_g
+      type: essays_su_g
+      config: sep_tok_full_labels
+      split: train[0%:20%]
+      args: sep_tok_full_labels
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9077215189873418
+---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+# longformer-sep_tok_full_labels
+This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/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

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