trainer: training complete at 2024-03-02 11:03:45.270654.

Browse files

Files changed (3) hide show

README.md +31 -31
meta_data/README_s42_e16.md +31 -31
model.safetensors +1 -1

README.md CHANGED Viewed

@@ -17,12 +17,12 @@ model-index:
       name: essays_su_g
       type: essays_su_g
       config: full_labels
-      split: train[0%:20%]
       args: full_labels
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8346287584373082
 ---
 <!-- 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: 0.7711
-- B-claim: {'precision': 0.5466666666666666, 'recall': 0.5774647887323944, 'f1-score': 0.5616438356164384, 'support': 284.0}
-- B-majorclaim: {'precision': 0.7299270072992701, 'recall': 0.7092198581560284, 'f1-score': 0.7194244604316545, 'support': 141.0}
-- B-premise: {'precision': 0.754863813229572, 'recall': 0.8220338983050848, 'f1-score': 0.7870182555780934, 'support': 708.0}
-- I-claim: {'precision': 0.5857645875251509, 'recall': 0.5712533725778759, 'f1-score': 0.5784179808766918, 'support': 4077.0}
-- I-majorclaim: {'precision': 0.7987048030221263, 'recall': 0.7312252964426877, 'f1-score': 0.7634769151405727, 'support': 2024.0}
-- I-premise: {'precision': 0.8739856801909308, 'recall': 0.8981360366252452, 'f1-score': 0.8858962986855898, 'support': 12232.0}
-- O: {'precision': 0.9090161406394571, 'recall': 0.896027563842724, 'f1-score': 0.9024751212043889, 'support': 9868.0}
-- Accuracy: 0.8346
-- Macro avg: {'precision': 0.7427040997961676, 'recall': 0.7436229735260057, 'f1-score': 0.7426218382190614, 'support': 29334.0}
-- Weighted avg: {'precision': 0.8337806464072924, 'recall': 0.8346287584373082, 'f1-score': 0.8339657063145517, 'support': 29334.0}
 ## Model description
@@ -71,24 +71,24 @@ The following hyperparameters were used during training:
 ### 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   | 41   | 0.7399          | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 284.0}                                                  | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 141.0}                                               | {'precision': 0.7625, 'recall': 0.08615819209039548, 'f1-score': 0.1548223350253807, 'support': 708.0}            | {'precision': 0.31821471652593486, 'recall': 0.3235221976943831, 'f1-score': 0.320846509365118, 'support': 4077.0}   | {'precision': 0.5556978233034571, 'recall': 0.21442687747035574, 'f1-score': 0.30944741532976827, 'support': 2024.0} | {'precision': 0.758950201884253, 'recall': 0.9220078482668411, 'f1-score': 0.8325705005167576, 'support': 12232.0}  | {'precision': 0.8602661596958175, 'recall': 0.8253952168625861, 'f1-score': 0.8424700041373604, 'support': 9868.0} | 0.7240   | {'precision': 0.4650898430584946, 'recall': 0.33878719034065163, 'f1-score': 0.35145096633919787, 'support': 29334.0} | {'precision': 0.70684288289933, 'recall': 0.7239721824503988, 'f1-score': 0.7002632905043792, 'support': 29334.0}   |
-| No log        | 2.0   | 82   | 0.5718          | {'precision': 0.5714285714285714, 'recall': 0.014084507042253521, 'f1-score': 0.027491408934707903, 'support': 284.0} | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 141.0}                                               | {'precision': 0.5743440233236151, 'recall': 0.8347457627118644, 'f1-score': 0.6804835924006908, 'support': 708.0} | {'precision': 0.5182818601348953, 'recall': 0.35810645082168263, 'f1-score': 0.42355671598491446, 'support': 4077.0} | {'precision': 0.6059907834101382, 'recall': 0.5197628458498024, 'f1-score': 0.5595744680851064, 'support': 2024.0}   | {'precision': 0.8156160458452723, 'recall': 0.9308371484630478, 'f1-score': 0.8694257788637754, 'support': 12232.0} | {'precision': 0.8745017884517118, 'recall': 0.867146331576814, 'f1-score': 0.8708085279601078, 'support': 9868.0}  | 0.7858   | {'precision': 0.5657375817991721, 'recall': 0.5035261494950664, 'f1-score': 0.4901914988899004, 'support': 29334.0}   | {'precision': 0.767528495718681, 'recall': 0.7857775959637281, 'f1-score': 0.7696517378810916, 'support': 29334.0}  |
-| No log        | 3.0   | 123  | 0.5305          | {'precision': 0.48412698412698413, 'recall': 0.4295774647887324, 'f1-score': 0.45522388059701496, 'support': 284.0}   | {'precision': 0.5714285714285714, 'recall': 0.0851063829787234, 'f1-score': 0.14814814814814814, 'support': 141.0} | {'precision': 0.6682080924855491, 'recall': 0.8163841807909604, 'f1-score': 0.7349014621741894, 'support': 708.0} | {'precision': 0.504127358490566, 'recall': 0.6291390728476821, 'f1-score': 0.5597381342062193, 'support': 4077.0}    | {'precision': 0.6824953445065177, 'recall': 0.724308300395257, 'f1-score': 0.7027804410354747, 'support': 2024.0}    | {'precision': 0.8977404661963025, 'recall': 0.8217789404839765, 'f1-score': 0.8580818643561399, 'support': 12232.0} | {'precision': 0.8986991703369865, 'recall': 0.8891366031617349, 'f1-score': 0.8938923131781367, 'support': 9868.0} | 0.8035   | {'precision': 0.6724037125102111, 'recall': 0.6279187064924381, 'f1-score': 0.6218237490993319, 'support': 29334.0}   | {'precision': 0.8173920172765067, 'recall': 0.8034703756732802, 'f1-score': 0.8076617373443268, 'support': 29334.0} |
-| No log        | 4.0   | 164  | 0.5264          | {'precision': 0.4874551971326165, 'recall': 0.4788732394366197, 'f1-score': 0.48312611012433393, 'support': 284.0}    | {'precision': 0.7037037037037037, 'recall': 0.5390070921985816, 'f1-score': 0.6104417670682731, 'support': 141.0}  | {'precision': 0.6842105263157895, 'recall': 0.844632768361582, 'f1-score': 0.7560050568900126, 'support': 708.0}  | {'precision': 0.5624033006704486, 'recall': 0.5349521707137601, 'f1-score': 0.5483343808925204, 'support': 4077.0}   | {'precision': 0.8264199106573069, 'recall': 0.6398221343873518, 'f1-score': 0.7212475633528265, 'support': 2024.0}   | {'precision': 0.8531785686832193, 'recall': 0.9073741007194245, 'f1-score': 0.8794421774097699, 'support': 12232.0} | {'precision': 0.9048757667117164, 'recall': 0.8820429671665991, 'f1-score': 0.8933134910453123, 'support': 9868.0} | 0.8212   | {'precision': 0.7174638534106857, 'recall': 0.6895292104262741, 'f1-score': 0.6988443638261499, 'support': 29334.0}   | {'precision': 0.8199722855692243, 'recall': 0.8211972455171473, 'f1-score': 0.81906491673643, 'support': 29334.0}   |
-| No log        | 5.0   | 205  | 0.5401          | {'precision': 0.45901639344262296, 'recall': 0.5915492957746479, 'f1-score': 0.5169230769230769, 'support': 284.0}    | {'precision': 0.688, 'recall': 0.6099290780141844, 'f1-score': 0.6466165413533834, 'support': 141.0}               | {'precision': 0.6872770511296076, 'recall': 0.8163841807909604, 'f1-score': 0.7462879276952873, 'support': 708.0} | {'precision': 0.5301336839798378, 'recall': 0.5933284277655139, 'f1-score': 0.5599537037037038, 'support': 4077.0}   | {'precision': 0.7659817351598174, 'recall': 0.6630434782608695, 'f1-score': 0.7108050847457628, 'support': 2024.0}   | {'precision': 0.864308426073132, 'recall': 0.8888979725310661, 'f1-score': 0.8764307593100111, 'support': 12232.0}  | {'precision': 0.9209399363127265, 'recall': 0.8499189298743413, 'f1-score': 0.8840052700922265, 'support': 9868.0} | 0.8132   | {'precision': 0.702236746585392, 'recall': 0.7161501947159407, 'f1-score': 0.7058603376890645, 'support': 29334.0}    | {'precision': 0.8210853899484308, 'recall': 0.8131519738187768, 'f1-score': 0.8158388468555539, 'support': 29334.0} |
-| No log        | 6.0   | 246  | 0.5609          | {'precision': 0.517799352750809, 'recall': 0.5633802816901409, 'f1-score': 0.5396290050590219, 'support': 284.0}      | {'precision': 0.6879432624113475, 'recall': 0.6879432624113475, 'f1-score': 0.6879432624113475, 'support': 141.0}  | {'precision': 0.7184466019417476, 'recall': 0.8361581920903954, 'f1-score': 0.7728459530026109, 'support': 708.0} | {'precision': 0.5675146771037182, 'recall': 0.5690458670591121, 'f1-score': 0.5682792406613595, 'support': 4077.0}   | {'precision': 0.7700845665961945, 'recall': 0.7198616600790514, 'f1-score': 0.744126659856997, 'support': 2024.0}    | {'precision': 0.8614670964698482, 'recall': 0.8957652060170046, 'f1-score': 0.8782814316059476, 'support': 12232.0} | {'precision': 0.915500480717872, 'recall': 0.8684637211187677, 'f1-score': 0.891362005304488, 'support': 9868.0}   | 0.8234   | {'precision': 0.7198222911416482, 'recall': 0.7343740272094027, 'f1-score': 0.7260667939859674, 'support': 29334.0}   | {'precision': 0.8248703886084983, 'recall': 0.8233790141133156, 'f1-score': 0.8236011159623022, 'support': 29334.0} |
-| No log        | 7.0   | 287  | 0.5639          | {'precision': 0.513595166163142, 'recall': 0.5985915492957746, 'f1-score': 0.5528455284552846, 'support': 284.0}      | {'precision': 0.6602564102564102, 'recall': 0.7304964539007093, 'f1-score': 0.6936026936026936, 'support': 141.0}  | {'precision': 0.7506666666666667, 'recall': 0.7951977401129944, 'f1-score': 0.7722908093278464, 'support': 708.0} | {'precision': 0.5732484076433121, 'recall': 0.5739514348785872, 'f1-score': 0.5735997058463046, 'support': 4077.0}   | {'precision': 0.7798969072164949, 'recall': 0.7475296442687747, 'f1-score': 0.7633703329969728, 'support': 2024.0}   | {'precision': 0.8836048129655398, 'recall': 0.8825212557226946, 'f1-score': 0.883062701951, 'support': 12232.0}     | {'precision': 0.9027186041793467, 'recall': 0.901803810295906, 'f1-score': 0.9022609753624656, 'support': 9868.0}  | 0.8312   | {'precision': 0.7234267107272733, 'recall': 0.74715598406792, 'f1-score': 0.7344332496489382, 'support': 29334.0}     | {'precision': 0.8318795778768913, 'recall': 0.8312197450057953, 'f1-score': 0.8314703017913034, 'support': 29334.0} |
-| No log        | 8.0   | 328  | 0.5766          | {'precision': 0.5232198142414861, 'recall': 0.5950704225352113, 'f1-score': 0.556836902800659, 'support': 284.0}      | {'precision': 0.6870748299319728, 'recall': 0.7163120567375887, 'f1-score': 0.7013888888888888, 'support': 141.0}  | {'precision': 0.7610146862483311, 'recall': 0.8050847457627118, 'f1-score': 0.7824296499656829, 'support': 708.0} | {'precision': 0.5692527367920038, 'recall': 0.5867059112092224, 'f1-score': 0.5778475661311753, 'support': 4077.0}   | {'precision': 0.7754259163655137, 'recall': 0.7420948616600791, 'f1-score': 0.7583943448624085, 'support': 2024.0}   | {'precision': 0.8839344262295082, 'recall': 0.881621975147155, 'f1-score': 0.8827766863130322, 'support': 12232.0}  | {'precision': 0.9100859247135843, 'recall': 0.9016011349817592, 'f1-score': 0.9058236611688048, 'support': 9868.0} | 0.8323   | {'precision': 0.7300011906460572, 'recall': 0.7469273011476754, 'f1-score': 0.7379282428758074, 'support': 29334.0}   | {'precision': 0.834103417381421, 'recall': 0.8323106293038794, 'f1-score': 0.8331173621878202, 'support': 29334.0}  |
-| No log        | 9.0   | 369  | 0.6424          | {'precision': 0.538961038961039, 'recall': 0.5845070422535211, 'f1-score': 0.5608108108108107, 'support': 284.0}      | {'precision': 0.6604938271604939, 'recall': 0.7588652482269503, 'f1-score': 0.7062706270627063, 'support': 141.0}  | {'precision': 0.7619047619047619, 'recall': 0.8135593220338984, 'f1-score': 0.7868852459016393, 'support': 708.0} | {'precision': 0.5726765348216453, 'recall': 0.5788570026980623, 'f1-score': 0.5757501829714565, 'support': 4077.0}   | {'precision': 0.7521697203471552, 'recall': 0.7707509881422925, 'f1-score': 0.7613469985358712, 'support': 2024.0}   | {'precision': 0.8750705702072747, 'recall': 0.8870176586003924, 'f1-score': 0.881003613332792, 'support': 12232.0}  | {'precision': 0.914336766869876, 'recall': 0.8815362788812323, 'f1-score': 0.8976369827675162, 'support': 9868.0}  | 0.8290   | {'precision': 0.725087602896035, 'recall': 0.75358479154805, 'f1-score': 0.7385292087689704, 'support': 29334.0}      | {'precision': 0.8307545957871735, 'recall': 0.829003886275312, 'f1-score': 0.8297056980988704, 'support': 29334.0}  |
-| No log        | 10.0  | 410  | 0.6875          | {'precision': 0.5598455598455598, 'recall': 0.5105633802816901, 'f1-score': 0.5340699815837938, 'support': 284.0}     | {'precision': 0.6688741721854304, 'recall': 0.7163120567375887, 'f1-score': 0.6917808219178082, 'support': 141.0}  | {'precision': 0.7392373923739237, 'recall': 0.8488700564971752, 'f1-score': 0.7902695595003287, 'support': 708.0} | {'precision': 0.6084390675715551, 'recall': 0.5057640421878833, 'f1-score': 0.5523707473881597, 'support': 4077.0}   | {'precision': 0.7721649484536083, 'recall': 0.7401185770750988, 'f1-score': 0.7558022199798183, 'support': 2024.0}   | {'precision': 0.8521132047143608, 'recall': 0.92797580117724, 'f1-score': 0.8884279732321058, 'support': 12232.0}   | {'precision': 0.9175562836909418, 'recall': 0.8797122010539117, 'f1-score': 0.8982358114749858, 'support': 9868.0} | 0.8331   | {'precision': 0.7311758041193401, 'recall': 0.7327594450015126, 'f1-score': 0.7301367307252857, 'support': 29334.0}   | {'precision': 0.8283101361138144, 'recall': 0.8331287925274425, 'f1-score': 0.8291241905412626, 'support': 29334.0} |
-| No log        | 11.0  | 451  | 0.7223          | {'precision': 0.5514705882352942, 'recall': 0.528169014084507, 'f1-score': 0.539568345323741, 'support': 284.0}       | {'precision': 0.7050359712230215, 'recall': 0.6950354609929078, 'f1-score': 0.7, 'support': 141.0}                 | {'precision': 0.7415307402760352, 'recall': 0.8347457627118644, 'f1-score': 0.7853820598006644, 'support': 708.0} | {'precision': 0.5881745416989413, 'recall': 0.5587441746382144, 'f1-score': 0.5730817610062893, 'support': 4077.0}   | {'precision': 0.7887840670859538, 'recall': 0.7435770750988142, 'f1-score': 0.7655137334689724, 'support': 2024.0}   | {'precision': 0.8658698539176627, 'recall': 0.9061478090255068, 'f1-score': 0.8855510725841887, 'support': 12232.0} | {'precision': 0.9162824811399832, 'recall': 0.8861978111066072, 'f1-score': 0.9009890789202555, 'support': 9868.0} | 0.8335   | {'precision': 0.7367354633681273, 'recall': 0.7360881582369173, 'f1-score': 0.7357265787291587, 'support': 29334.0}   | {'precision': 0.8320963257113063, 'recall': 0.8335378741392241, 'f1-score': 0.8323741390608008, 'support': 29334.0} |
-| No log        | 12.0  | 492  | 0.7229          | {'precision': 0.4842105263157895, 'recall': 0.647887323943662, 'f1-score': 0.5542168674698795, 'support': 284.0}      | {'precision': 0.6688311688311688, 'recall': 0.7304964539007093, 'f1-score': 0.6983050847457627, 'support': 141.0}  | {'precision': 0.7662517289073306, 'recall': 0.7824858757062146, 'f1-score': 0.7742837176799442, 'support': 708.0} | {'precision': 0.5374846374436706, 'recall': 0.6436104979151337, 'f1-score': 0.5857796629088069, 'support': 4077.0}   | {'precision': 0.7547452547452548, 'recall': 0.7465415019762845, 'f1-score': 0.7506209637357178, 'support': 2024.0}   | {'precision': 0.8857740585774059, 'recall': 0.8653531720078482, 'f1-score': 0.8754445455297329, 'support': 12232.0} | {'precision': 0.9279454722492697, 'recall': 0.8691730847182814, 'f1-score': 0.8975982418502434, 'support': 9868.0} | 0.8229   | {'precision': 0.7178918352956986, 'recall': 0.755078272881162, 'f1-score': 0.7337498691314411, 'support': 29334.0}    | {'precision': 0.8346973026345582, 'recall': 0.8228676620985886, 'f1-score': 0.8276221833778615, 'support': 29334.0} |
-| 0.3184        | 13.0  | 533  | 0.7460          | {'precision': 0.5433333333333333, 'recall': 0.573943661971831, 'f1-score': 0.5582191780821917, 'support': 284.0}      | {'precision': 0.7299270072992701, 'recall': 0.7092198581560284, 'f1-score': 0.7194244604316545, 'support': 141.0}  | {'precision': 0.75, 'recall': 0.8220338983050848, 'f1-score': 0.784366576819407, 'support': 708.0}                | {'precision': 0.5741638390693166, 'recall': 0.5810645082168261, 'f1-score': 0.577593563330489, 'support': 4077.0}    | {'precision': 0.8051082731815657, 'recall': 0.7164031620553359, 'f1-score': 0.7581699346405228, 'support': 2024.0}   | {'precision': 0.873641304347826, 'recall': 0.8936396337475474, 'f1-score': 0.8835273197542839, 'support': 12232.0}  | {'precision': 0.9082834125180748, 'recall': 0.8911633563032023, 'f1-score': 0.8996419437340154, 'support': 9868.0} | 0.8314   | {'precision': 0.7406367385356267, 'recall': 0.7410668683936937, 'f1-score': 0.7401347109703663, 'support': 29334.0}   | {'precision': 0.8320703838894091, 'recall': 0.8314242858116861, 'f1-score': 0.8314468675699472, 'support': 29334.0} |
-| 0.3184        | 14.0  | 574  | 0.7719          | {'precision': 0.5286624203821656, 'recall': 0.5845070422535211, 'f1-score': 0.5551839464882944, 'support': 284.0}     | {'precision': 0.6917808219178082, 'recall': 0.7163120567375887, 'f1-score': 0.7038327526132405, 'support': 141.0}  | {'precision': 0.751937984496124, 'recall': 0.8220338983050848, 'f1-score': 0.7854251012145749, 'support': 708.0}  | {'precision': 0.5745517071972488, 'recall': 0.5737061564876135, 'f1-score': 0.5741286205203731, 'support': 4077.0}   | {'precision': 0.7785304846274101, 'recall': 0.7381422924901185, 'f1-score': 0.7577986304844027, 'support': 2024.0}   | {'precision': 0.8700618752974774, 'recall': 0.8966644865925442, 'f1-score': 0.8831628955632499, 'support': 12232.0} | {'precision': 0.9169823232323232, 'recall': 0.8831576813944062, 'f1-score': 0.8997522196985339, 'support': 9868.0} | 0.8306   | {'precision': 0.7303582310215082, 'recall': 0.7449319448944111, 'f1-score': 0.7370405952260956, 'support': 29334.0}   | {'precision': 0.8314455836819585, 'recall': 0.830606122588123, 'f1-score': 0.8307460246491396, 'support': 29334.0}  |
-| 0.3184        | 15.0  | 615  | 0.7737          | {'precision': 0.5240963855421686, 'recall': 0.6126760563380281, 'f1-score': 0.564935064935065, 'support': 284.0}      | {'precision': 0.696551724137931, 'recall': 0.7163120567375887, 'f1-score': 0.7062937062937064, 'support': 141.0}   | {'precision': 0.7532637075718016, 'recall': 0.8149717514124294, 'f1-score': 0.7829036635006784, 'support': 708.0} | {'precision': 0.5683770605990248, 'recall': 0.6004415011037527, 'f1-score': 0.583969465648855, 'support': 4077.0}    | {'precision': 0.789280084077772, 'recall': 0.7420948616600791, 'f1-score': 0.7649605296664119, 'support': 2024.0}    | {'precision': 0.8766526926797807, 'recall': 0.8889797253106606, 'f1-score': 0.8827731774638741, 'support': 12232.0} | {'precision': 0.9183285849952516, 'recall': 0.8819416295095257, 'f1-score': 0.8997673817523908, 'support': 9868.0} | 0.8311   | {'precision': 0.7323643199433901, 'recall': 0.7510596545817235, 'f1-score': 0.7408004270372831, 'support': 29334.0}   | {'precision': 0.8345410190013676, 'recall': 0.8310833844685348, 'f1-score': 0.8324958893486518, 'support': 29334.0} |
-| 0.3184        | 16.0  | 656  | 0.7711          | {'precision': 0.5466666666666666, 'recall': 0.5774647887323944, 'f1-score': 0.5616438356164384, 'support': 284.0}     | {'precision': 0.7299270072992701, 'recall': 0.7092198581560284, 'f1-score': 0.7194244604316545, 'support': 141.0}  | {'precision': 0.754863813229572, 'recall': 0.8220338983050848, 'f1-score': 0.7870182555780934, 'support': 708.0}  | {'precision': 0.5857645875251509, 'recall': 0.5712533725778759, 'f1-score': 0.5784179808766918, 'support': 4077.0}   | {'precision': 0.7987048030221263, 'recall': 0.7312252964426877, 'f1-score': 0.7634769151405727, 'support': 2024.0}   | {'precision': 0.8739856801909308, 'recall': 0.8981360366252452, 'f1-score': 0.8858962986855898, 'support': 12232.0} | {'precision': 0.9090161406394571, 'recall': 0.896027563842724, 'f1-score': 0.9024751212043889, 'support': 9868.0}  | 0.8346   | {'precision': 0.7427040997961676, 'recall': 0.7436229735260057, 'f1-score': 0.7426218382190614, 'support': 29334.0}   | {'precision': 0.8337806464072924, 'recall': 0.8346287584373082, 'f1-score': 0.8339657063145517, 'support': 29334.0} |
 ### Framework versions

       name: essays_su_g
       type: essays_su_g
       config: full_labels
+      split: train[20%:40%]
       args: full_labels
     metrics:
     - name: Accuracy
       type: accuracy
+      value: 0.8449945467164623
 ---
 <!-- 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: 0.6708
+- B-claim: {'precision': 0.5619047619047619, 'recall': 0.6, 'f1-score': 0.580327868852459, 'support': 295.0}
+- B-majorclaim: {'precision': 0.6789473684210526, 'recall': 0.8269230769230769, 'f1-score': 0.7456647398843931, 'support': 156.0}
+- B-premise: {'precision': 0.7630573248407644, 'recall': 0.8239339752407153, 'f1-score': 0.7923280423280424, 'support': 727.0}
+- I-claim: {'precision': 0.5966467065868264, 'recall': 0.6012551291334781, 'f1-score': 0.5989420533782159, 'support': 4143.0}
+- I-majorclaim: {'precision': 0.7935897435897435, 'recall': 0.8467852257181943, 'f1-score': 0.8193249503639972, 'support': 2193.0}
+- I-premise: {'precision': 0.8916157064692629, 'recall': 0.8820345458887209, 'f1-score': 0.8867992477291825, 'support': 12563.0}
+- O: {'precision': 0.9210893854748603, 'recall': 0.9069744597249508, 'f1-score': 0.9139774302118391, 'support': 10180.0}
+- Accuracy: 0.8450
+- Macro avg: {'precision': 0.7438358567553245, 'recall': 0.7839866303755908, 'f1-score': 0.7624806189640186, 'support': 30257.0}
+- Weighted avg: {'precision': 0.8466380687769368, 'recall': 0.8449945467164623, 'f1-score': 0.8456518702970672, 'support': 30257.0}
 ## Model description
 ### 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   | 41   | 0.6795          | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 295.0}                                                 | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 156.0}                                                 | {'precision': 0.8727272727272727, 'recall': 0.06602475928473177, 'f1-score': 0.1227621483375959, 'support': 727.0} | {'precision': 0.5111008325624422, 'recall': 0.26671494086410813, 'f1-score': 0.35051546391752586, 'support': 4143.0} | {'precision': 0.4952120383036936, 'recall': 0.16507067943456452, 'f1-score': 0.2476060191518468, 'support': 2193.0} | {'precision': 0.7927029242962558, 'recall': 0.9235055321181247, 'f1-score': 0.8531195999852935, 'support': 12563.0} | {'precision': 0.7493095557484416, 'recall': 0.9328094302554027, 'f1-score': 0.8310506279263117, 'support': 10180.0} | 0.7474   | {'precision': 0.48872180337687227, 'recall': 0.3363036202795617, 'f1-score': 0.34357912275979624, 'support': 30257.0} | {'precision': 0.7080894203665903, 'recall': 0.7473642462901147, 'f1-score': 0.7027223642713039, 'support': 30257.0} |
+| No log        | 2.0   | 82   | 0.5111          | {'precision': 0.6470588235294118, 'recall': 0.07457627118644068, 'f1-score': 0.1337386018237082, 'support': 295.0}   | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 156.0}                                                 | {'precision': 0.6562150055991042, 'recall': 0.8060522696011004, 'f1-score': 0.7234567901234568, 'support': 727.0}  | {'precision': 0.5315296566077004, 'recall': 0.6164615013275404, 'f1-score': 0.5708538220831472, 'support': 4143.0}   | {'precision': 0.5701344243132671, 'recall': 0.8896488828089375, 'f1-score': 0.6949243098842386, 'support': 2193.0}  | {'precision': 0.914638511095204, 'recall': 0.8136591578444639, 'f1-score': 0.861198871056068, 'support': 12563.0}   | {'precision': 0.9145764077767704, 'recall': 0.8918467583497053, 'f1-score': 0.9030685830805192, 'support': 10180.0} | 0.8069   | {'precision': 0.6048789755602082, 'recall': 0.5846064058740269, 'f1-score': 0.5553201397215911, 'support': 30257.0}   | {'precision': 0.8236564850419075, 'recall': 0.8068876623591235, 'f1-score': 0.8086360829977005, 'support': 30257.0} |
+| No log        | 3.0   | 123  | 0.4232          | {'precision': 0.46254071661237783, 'recall': 0.48135593220338985, 'f1-score': 0.47176079734219273, 'support': 295.0} | {'precision': 0.6666666666666666, 'recall': 0.038461538461538464, 'f1-score': 0.07272727272727274, 'support': 156.0} | {'precision': 0.7320341047503045, 'recall': 0.8266850068775791, 'f1-score': 0.7764857881136951, 'support': 727.0}  | {'precision': 0.5594361455922575, 'recall': 0.6418054549843109, 'f1-score': 0.597796762589928, 'support': 4143.0}    | {'precision': 0.7543689320388349, 'recall': 0.7086183310533516, 'f1-score': 0.730778274159417, 'support': 2193.0}   | {'precision': 0.8918637274549098, 'recall': 0.8856164928759054, 'f1-score': 0.8887291317197858, 'support': 12563.0} | {'precision': 0.934092758340114, 'recall': 0.9021611001964637, 'f1-score': 0.9178492904257447, 'support': 10180.0}  | 0.8352   | {'precision': 0.7144290073507807, 'recall': 0.6406719795217912, 'f1-score': 0.6365896167254336, 'support': 30257.0}   | {'precision': 0.841400720911604, 'recall': 0.835244736755131, 'f1-score': 0.836272553745959, 'support': 30257.0}    |
+| No log        | 4.0   | 164  | 0.4295          | {'precision': 0.523972602739726, 'recall': 0.5186440677966102, 'f1-score': 0.5212947189097104, 'support': 295.0}     | {'precision': 0.7076923076923077, 'recall': 0.5897435897435898, 'f1-score': 0.6433566433566433, 'support': 156.0}    | {'precision': 0.7304878048780488, 'recall': 0.8239339752407153, 'f1-score': 0.7744020685197156, 'support': 727.0}  | {'precision': 0.5975518361229079, 'recall': 0.5773594013999517, 'f1-score': 0.5872821016449792, 'support': 4143.0}   | {'precision': 0.7692971108236308, 'recall': 0.8134974920200638, 'f1-score': 0.7907801418439716, 'support': 2193.0}  | {'precision': 0.9042123485285631, 'recall': 0.873119477831728, 'f1-score': 0.8883939418482223, 'support': 12563.0}  | {'precision': 0.8958530581329294, 'recall': 0.9294695481335953, 'f1-score': 0.9123517500723171, 'support': 10180.0} | 0.8412   | {'precision': 0.7327238669883019, 'recall': 0.7322525074523221, 'f1-score': 0.7311230523136514, 'support': 30257.0}   | {'precision': 0.8407365647422267, 'recall': 0.8411607231384473, 'f1-score': 0.8405678153025818, 'support': 30257.0} |
+| No log        | 5.0   | 205  | 0.4565          | {'precision': 0.5276073619631901, 'recall': 0.5830508474576271, 'f1-score': 0.5539452495974235, 'support': 295.0}    | {'precision': 0.7123287671232876, 'recall': 0.6666666666666666, 'f1-score': 0.6887417218543046, 'support': 156.0}    | {'precision': 0.7634146341463415, 'recall': 0.8610729023383769, 'f1-score': 0.8093083387201035, 'support': 727.0}  | {'precision': 0.5808294015396076, 'recall': 0.5645667390779628, 'f1-score': 0.5725826193390453, 'support': 4143.0}   | {'precision': 0.7949438202247191, 'recall': 0.774281805745554, 'f1-score': 0.7844767844767844, 'support': 2193.0}   | {'precision': 0.8697251839615557, 'recall': 0.9219931545013134, 'f1-score': 0.8950967891503419, 'support': 12563.0} | {'precision': 0.9528679881906369, 'recall': 0.887721021611002, 'f1-score': 0.9191415785191211, 'support': 10180.0}  | 0.8447   | {'precision': 0.7431024510213342, 'recall': 0.7513361624855005, 'f1-score': 0.7461847259510178, 'support': 30257.0}   | {'precision': 0.8460194835144224, 'recall': 0.8447301450903923, 'f1-score': 0.8445567746699831, 'support': 30257.0} |
+| No log        | 6.0   | 246  | 0.4916          | {'precision': 0.5593869731800766, 'recall': 0.49491525423728816, 'f1-score': 0.5251798561151079, 'support': 295.0}   | {'precision': 0.6492146596858639, 'recall': 0.7948717948717948, 'f1-score': 0.7146974063400577, 'support': 156.0}    | {'precision': 0.7337278106508875, 'recall': 0.8528198074277854, 'f1-score': 0.7888040712468193, 'support': 727.0}  | {'precision': 0.6394230769230769, 'recall': 0.41733043688148685, 'f1-score': 0.5050387030816416, 'support': 4143.0}  | {'precision': 0.7733443027560675, 'recall': 0.8572731418148655, 'f1-score': 0.8131487889273357, 'support': 2193.0}  | {'precision': 0.8424233805020266, 'recall': 0.9430072434927963, 'f1-score': 0.8898820701569895, 'support': 12563.0} | {'precision': 0.9398688793280066, 'recall': 0.9012770137524558, 'f1-score': 0.9201684886169893, 'support': 10180.0} | 0.8435   | {'precision': 0.7339127261465722, 'recall': 0.7516420989254959, 'f1-score': 0.7367027692121344, 'support': 30257.0}   | {'precision': 0.8360386273187937, 'recall': 0.8434742373665598, 'f1-score': 0.8349273131912464, 'support': 30257.0} |
+| No log        | 7.0   | 287  | 0.5145          | {'precision': 0.5668789808917197, 'recall': 0.6033898305084746, 'f1-score': 0.5845648604269295, 'support': 295.0}    | {'precision': 0.6777777777777778, 'recall': 0.782051282051282, 'f1-score': 0.7261904761904762, 'support': 156.0}     | {'precision': 0.758873929008568, 'recall': 0.8528198074277854, 'f1-score': 0.8031088082901554, 'support': 727.0}   | {'precision': 0.6070287539936102, 'recall': 0.5503258508327299, 'f1-score': 0.5772882643372579, 'support': 4143.0}   | {'precision': 0.7948040510788199, 'recall': 0.8230734154126766, 'f1-score': 0.8086917562724014, 'support': 2193.0}  | {'precision': 0.8718995765275257, 'recall': 0.9177744169386293, 'f1-score': 0.8942490402140614, 'support': 12563.0} | {'precision': 0.9417225373904075, 'recall': 0.8968565815324165, 'f1-score': 0.9187421383647798, 'support': 10180.0} | 0.8482   | {'precision': 0.745569372381204, 'recall': 0.7751844549577135, 'f1-score': 0.7589764777280089, 'support': 30257.0}    | {'precision': 0.8468453317066018, 'recall': 0.8482334666358198, 'f1-score': 0.8468124537513947, 'support': 30257.0} |
+| No log        | 8.0   | 328  | 0.5386          | {'precision': 0.5384615384615384, 'recall': 0.6169491525423729, 'f1-score': 0.5750394944707741, 'support': 295.0}    | {'precision': 0.686046511627907, 'recall': 0.7564102564102564, 'f1-score': 0.7195121951219512, 'support': 156.0}     | {'precision': 0.7537688442211056, 'recall': 0.8253094910591472, 'f1-score': 0.7879185817465528, 'support': 727.0}  | {'precision': 0.5808619091751622, 'recall': 0.6051170649287956, 'f1-score': 0.5927414588012767, 'support': 4143.0}   | {'precision': 0.8207132388861749, 'recall': 0.7660738714090287, 'f1-score': 0.7924528301886793, 'support': 2193.0}  | {'precision': 0.8846666144323435, 'recall': 0.8987502984955823, 'f1-score': 0.8916528468767275, 'support': 12563.0} | {'precision': 0.9284478371501272, 'recall': 0.8960707269155206, 'f1-score': 0.9119720069982503, 'support': 10180.0} | 0.8428   | {'precision': 0.7418523562791942, 'recall': 0.7663829802515292, 'f1-score': 0.7530413448863159, 'support': 30257.0}   | {'precision': 0.8456178749149208, 'recall': 0.8427801830981261, 'f1-score': 0.8439033621710555, 'support': 30257.0} |
+| No log        | 9.0   | 369  | 0.5474          | {'precision': 0.5585284280936454, 'recall': 0.5661016949152542, 'f1-score': 0.5622895622895623, 'support': 295.0}    | {'precision': 0.6875, 'recall': 0.7756410256410257, 'f1-score': 0.7289156626506025, 'support': 156.0}                | {'precision': 0.7355769230769231, 'recall': 0.8418156808803301, 'f1-score': 0.7851186658114176, 'support': 727.0}  | {'precision': 0.604811876119785, 'recall': 0.570359642770939, 'f1-score': 0.587080745341615, 'support': 4143.0}      | {'precision': 0.8211678832116789, 'recall': 0.8207934336525308, 'f1-score': 0.8209806157354618, 'support': 2193.0}  | {'precision': 0.888625217528872, 'recall': 0.8942131656451484, 'f1-score': 0.8914104344376116, 'support': 12563.0}  | {'precision': 0.91595650896268, 'recall': 0.918565815324165, 'f1-score': 0.917259306488793, 'support': 10180.0}     | 0.8477   | {'precision': 0.7445952624276548, 'recall': 0.7696414941184847, 'f1-score': 0.7561507132507234, 'support': 30257.0}   | {'precision': 0.8461371897103921, 'recall': 0.8476716131804211, 'f1-score': 0.8467310896799954, 'support': 30257.0} |
+| No log        | 10.0  | 410  | 0.5962          | {'precision': 0.5531914893617021, 'recall': 0.6169491525423729, 'f1-score': 0.5833333333333334, 'support': 295.0}    | {'precision': 0.6582914572864321, 'recall': 0.8397435897435898, 'f1-score': 0.7380281690140845, 'support': 156.0}    | {'precision': 0.7450248756218906, 'recall': 0.8239339752407153, 'f1-score': 0.782495101241019, 'support': 727.0}   | {'precision': 0.6161803713527851, 'recall': 0.5607048032826454, 'f1-score': 0.5871350941488689, 'support': 4143.0}   | {'precision': 0.776742301458671, 'recall': 0.8741450068399452, 'f1-score': 0.8225702638918686, 'support': 2193.0}   | {'precision': 0.8831158622858041, 'recall': 0.8942927644670858, 'f1-score': 0.888669171445521, 'support': 12563.0}  | {'precision': 0.9232313095835424, 'recall': 0.9037328094302554, 'f1-score': 0.9133780094316207, 'support': 10180.0} | 0.8457   | {'precision': 0.7365396667072609, 'recall': 0.7876431573638013, 'f1-score': 0.7593727346437593, 'support': 30257.0}   | {'precision': 0.8446583764532496, 'recall': 0.8456555507816373, 'f1-score': 0.844598799846626, 'support': 30257.0}  |
+| No log        | 11.0  | 451  | 0.5957          | {'precision': 0.5545171339563862, 'recall': 0.6033898305084746, 'f1-score': 0.577922077922078, 'support': 295.0}     | {'precision': 0.6467661691542289, 'recall': 0.8333333333333334, 'f1-score': 0.7282913165266107, 'support': 156.0}    | {'precision': 0.7694300518134715, 'recall': 0.8170563961485557, 'f1-score': 0.7925283522348232, 'support': 727.0}  | {'precision': 0.6102831594634873, 'recall': 0.5930485155684286, 'f1-score': 0.6015424164524421, 'support': 4143.0}   | {'precision': 0.783003300330033, 'recall': 0.8654810761513908, 'f1-score': 0.8221789040502492, 'support': 2193.0}   | {'precision': 0.892235181338872, 'recall': 0.8890392422192152, 'f1-score': 0.8906343447230972, 'support': 12563.0}  | {'precision': 0.9259629814907454, 'recall': 0.9091355599214146, 'f1-score': 0.917472118959108, 'support': 10180.0}  | 0.8488   | {'precision': 0.7403139967924607, 'recall': 0.7872119934072589, 'f1-score': 0.7615099329812013, 'support': 30257.0}   | {'precision': 0.8495500818518233, 'recall': 0.8487622698879598, 'f1-score': 0.8488747259194414, 'support': 30257.0} |
+| No log        | 12.0  | 492  | 0.6363          | {'precision': 0.546583850931677, 'recall': 0.5966101694915255, 'f1-score': 0.5705024311183144, 'support': 295.0}     | {'precision': 0.6580310880829016, 'recall': 0.8141025641025641, 'f1-score': 0.7277936962750716, 'support': 156.0}    | {'precision': 0.7600502512562815, 'recall': 0.8321870701513068, 'f1-score': 0.7944845699277742, 'support': 727.0}  | {'precision': 0.6018252933507171, 'recall': 0.5570842384745354, 'f1-score': 0.5785911255953873, 'support': 4143.0}   | {'precision': 0.7675276752767528, 'recall': 0.853625170998632, 'f1-score': 0.8082901554404146, 'support': 2193.0}   | {'precision': 0.8818805551224076, 'recall': 0.9003422749343309, 'f1-score': 0.8910157942416007, 'support': 12563.0} | {'precision': 0.9259597806215722, 'recall': 0.8955795677799607, 'f1-score': 0.9105163287725957, 'support': 10180.0} | 0.8433   | {'precision': 0.73455121352033, 'recall': 0.7785044365618364, 'f1-score': 0.7544563001958797, 'support': 30257.0}     | {'precision': 0.8427252530453597, 'recall': 0.8433089863502661, 'f1-score': 0.8425156264772145, 'support': 30257.0} |
+| 0.3164        | 13.0  | 533  | 0.6392          | {'precision': 0.564935064935065, 'recall': 0.5898305084745763, 'f1-score': 0.5771144278606964, 'support': 295.0}     | {'precision': 0.6615384615384615, 'recall': 0.8269230769230769, 'f1-score': 0.7350427350427349, 'support': 156.0}    | {'precision': 0.7632911392405063, 'recall': 0.8294360385144429, 'f1-score': 0.7949901120632828, 'support': 727.0}  | {'precision': 0.6016421995521274, 'recall': 0.5836350470673425, 'f1-score': 0.5925018377848567, 'support': 4143.0}   | {'precision': 0.7977147693609818, 'recall': 0.8595531235750113, 'f1-score': 0.8274802458296752, 'support': 2193.0}  | {'precision': 0.8831720556997876, 'recall': 0.8935763750696489, 'f1-score': 0.8883437524728971, 'support': 12563.0} | {'precision': 0.9303008813696687, 'recall': 0.9020628683693517, 'f1-score': 0.9159642910578025, 'support': 10180.0} | 0.8467   | {'precision': 0.743227795956657, 'recall': 0.7835738625704929, 'f1-score': 0.7616339145874208, 'support': 30257.0}    | {'precision': 0.8471598021098077, 'recall': 0.8466801070826585, 'f1-score': 0.8466487613672259, 'support': 30257.0} |
+| 0.3164        | 14.0  | 574  | 0.6574          | {'precision': 0.5741935483870968, 'recall': 0.6033898305084746, 'f1-score': 0.5884297520661158, 'support': 295.0}    | {'precision': 0.673469387755102, 'recall': 0.8461538461538461, 'f1-score': 0.75, 'support': 156.0}                   | {'precision': 0.7689295039164491, 'recall': 0.8101788170563962, 'f1-score': 0.7890154052243804, 'support': 727.0}  | {'precision': 0.5957288303948348, 'recall': 0.5790489983104031, 'f1-score': 0.5872705018359853, 'support': 4143.0}   | {'precision': 0.7902335456475584, 'recall': 0.8486092111263109, 'f1-score': 0.8183817062445031, 'support': 2193.0}  | {'precision': 0.8890226287915263, 'recall': 0.8818753482448459, 'f1-score': 0.8854345654345654, 'support': 12563.0} | {'precision': 0.9146040824376295, 'recall': 0.9111001964636543, 'f1-score': 0.9128487771271099, 'support': 10180.0} | 0.8432   | {'precision': 0.7437402181900282, 'recall': 0.782908035409133, 'f1-score': 0.7616258154189514, 'support': 30257.0}    | {'precision': 0.8432431379603119, 'recall': 0.8432098357404898, 'f1-score': 0.8430607378149431, 'support': 30257.0} |
+| 0.3164        | 15.0  | 615  | 0.6657          | {'precision': 0.5636942675159236, 'recall': 0.6, 'f1-score': 0.5812807881773399, 'support': 295.0}                   | {'precision': 0.6717948717948717, 'recall': 0.8397435897435898, 'f1-score': 0.7464387464387464, 'support': 156.0}    | {'precision': 0.7634271099744245, 'recall': 0.8211829436038515, 'f1-score': 0.7912524850894631, 'support': 727.0}  | {'precision': 0.5987460815047022, 'recall': 0.5993241612358194, 'f1-score': 0.5990349819059108, 'support': 4143.0}   | {'precision': 0.793854033290653, 'recall': 0.8481532147742818, 'f1-score': 0.8201058201058201, 'support': 2193.0}   | {'precision': 0.8901107721945738, 'recall': 0.8826713364642204, 'f1-score': 0.8863754446265136, 'support': 12563.0} | {'precision': 0.9214414054701537, 'recall': 0.906777996070727, 'f1-score': 0.9140508961283296, 'support': 10180.0}  | 0.8450   | {'precision': 0.7432955059636147, 'recall': 0.7854076059846414, 'f1-score': 0.7626484517817319, 'support': 30257.0}   | {'precision': 0.8464277148202262, 'recall': 0.8450275969197211, 'f1-score': 0.8455573804598716, 'support': 30257.0} |
+| 0.3164        | 16.0  | 656  | 0.6708          | {'precision': 0.5619047619047619, 'recall': 0.6, 'f1-score': 0.580327868852459, 'support': 295.0}                    | {'precision': 0.6789473684210526, 'recall': 0.8269230769230769, 'f1-score': 0.7456647398843931, 'support': 156.0}    | {'precision': 0.7630573248407644, 'recall': 0.8239339752407153, 'f1-score': 0.7923280423280424, 'support': 727.0}  | {'precision': 0.5966467065868264, 'recall': 0.6012551291334781, 'f1-score': 0.5989420533782159, 'support': 4143.0}   | {'precision': 0.7935897435897435, 'recall': 0.8467852257181943, 'f1-score': 0.8193249503639972, 'support': 2193.0}  | {'precision': 0.8916157064692629, 'recall': 0.8820345458887209, 'f1-score': 0.8867992477291825, 'support': 12563.0} | {'precision': 0.9210893854748603, 'recall': 0.9069744597249508, 'f1-score': 0.9139774302118391, 'support': 10180.0} | 0.8450   | {'precision': 0.7438358567553245, 'recall': 0.7839866303755908, 'f1-score': 0.7624806189640186, 'support': 30257.0}   | {'precision': 0.8466380687769368, 'recall': 0.8449945467164623, 'f1-score': 0.8456518702970672, 'support': 30257.0} |
 ### Framework versions

meta_data/README_s42_e16.md CHANGED Viewed

@@ -17,12 +17,12 @@ model-index:
       name: essays_su_g
       type: essays_su_g
       config: full_labels
-      split: train[0%:20%]
       args: full_labels
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8346287584373082
 ---
 <!-- 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: 0.7711
-- B-claim: {'precision': 0.5466666666666666, 'recall': 0.5774647887323944, 'f1-score': 0.5616438356164384, 'support': 284.0}
-- B-majorclaim: {'precision': 0.7299270072992701, 'recall': 0.7092198581560284, 'f1-score': 0.7194244604316545, 'support': 141.0}
-- B-premise: {'precision': 0.754863813229572, 'recall': 0.8220338983050848, 'f1-score': 0.7870182555780934, 'support': 708.0}
-- I-claim: {'precision': 0.5857645875251509, 'recall': 0.5712533725778759, 'f1-score': 0.5784179808766918, 'support': 4077.0}
-- I-majorclaim: {'precision': 0.7987048030221263, 'recall': 0.7312252964426877, 'f1-score': 0.7634769151405727, 'support': 2024.0}
-- I-premise: {'precision': 0.8739856801909308, 'recall': 0.8981360366252452, 'f1-score': 0.8858962986855898, 'support': 12232.0}
-- O: {'precision': 0.9090161406394571, 'recall': 0.896027563842724, 'f1-score': 0.9024751212043889, 'support': 9868.0}
-- Accuracy: 0.8346
-- Macro avg: {'precision': 0.7427040997961676, 'recall': 0.7436229735260057, 'f1-score': 0.7426218382190614, 'support': 29334.0}
-- Weighted avg: {'precision': 0.8337806464072924, 'recall': 0.8346287584373082, 'f1-score': 0.8339657063145517, 'support': 29334.0}
 ## Model description
@@ -71,24 +71,24 @@ The following hyperparameters were used during training:
 ### 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   | 41   | 0.7399          | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 284.0}                                                  | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 141.0}                                               | {'precision': 0.7625, 'recall': 0.08615819209039548, 'f1-score': 0.1548223350253807, 'support': 708.0}            | {'precision': 0.31821471652593486, 'recall': 0.3235221976943831, 'f1-score': 0.320846509365118, 'support': 4077.0}   | {'precision': 0.5556978233034571, 'recall': 0.21442687747035574, 'f1-score': 0.30944741532976827, 'support': 2024.0} | {'precision': 0.758950201884253, 'recall': 0.9220078482668411, 'f1-score': 0.8325705005167576, 'support': 12232.0}  | {'precision': 0.8602661596958175, 'recall': 0.8253952168625861, 'f1-score': 0.8424700041373604, 'support': 9868.0} | 0.7240   | {'precision': 0.4650898430584946, 'recall': 0.33878719034065163, 'f1-score': 0.35145096633919787, 'support': 29334.0} | {'precision': 0.70684288289933, 'recall': 0.7239721824503988, 'f1-score': 0.7002632905043792, 'support': 29334.0}   |
-| No log        | 2.0   | 82   | 0.5718          | {'precision': 0.5714285714285714, 'recall': 0.014084507042253521, 'f1-score': 0.027491408934707903, 'support': 284.0} | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 141.0}                                               | {'precision': 0.5743440233236151, 'recall': 0.8347457627118644, 'f1-score': 0.6804835924006908, 'support': 708.0} | {'precision': 0.5182818601348953, 'recall': 0.35810645082168263, 'f1-score': 0.42355671598491446, 'support': 4077.0} | {'precision': 0.6059907834101382, 'recall': 0.5197628458498024, 'f1-score': 0.5595744680851064, 'support': 2024.0}   | {'precision': 0.8156160458452723, 'recall': 0.9308371484630478, 'f1-score': 0.8694257788637754, 'support': 12232.0} | {'precision': 0.8745017884517118, 'recall': 0.867146331576814, 'f1-score': 0.8708085279601078, 'support': 9868.0}  | 0.7858   | {'precision': 0.5657375817991721, 'recall': 0.5035261494950664, 'f1-score': 0.4901914988899004, 'support': 29334.0}   | {'precision': 0.767528495718681, 'recall': 0.7857775959637281, 'f1-score': 0.7696517378810916, 'support': 29334.0}  |
-| No log        | 3.0   | 123  | 0.5305          | {'precision': 0.48412698412698413, 'recall': 0.4295774647887324, 'f1-score': 0.45522388059701496, 'support': 284.0}   | {'precision': 0.5714285714285714, 'recall': 0.0851063829787234, 'f1-score': 0.14814814814814814, 'support': 141.0} | {'precision': 0.6682080924855491, 'recall': 0.8163841807909604, 'f1-score': 0.7349014621741894, 'support': 708.0} | {'precision': 0.504127358490566, 'recall': 0.6291390728476821, 'f1-score': 0.5597381342062193, 'support': 4077.0}    | {'precision': 0.6824953445065177, 'recall': 0.724308300395257, 'f1-score': 0.7027804410354747, 'support': 2024.0}    | {'precision': 0.8977404661963025, 'recall': 0.8217789404839765, 'f1-score': 0.8580818643561399, 'support': 12232.0} | {'precision': 0.8986991703369865, 'recall': 0.8891366031617349, 'f1-score': 0.8938923131781367, 'support': 9868.0} | 0.8035   | {'precision': 0.6724037125102111, 'recall': 0.6279187064924381, 'f1-score': 0.6218237490993319, 'support': 29334.0}   | {'precision': 0.8173920172765067, 'recall': 0.8034703756732802, 'f1-score': 0.8076617373443268, 'support': 29334.0} |
-| No log        | 4.0   | 164  | 0.5264          | {'precision': 0.4874551971326165, 'recall': 0.4788732394366197, 'f1-score': 0.48312611012433393, 'support': 284.0}    | {'precision': 0.7037037037037037, 'recall': 0.5390070921985816, 'f1-score': 0.6104417670682731, 'support': 141.0}  | {'precision': 0.6842105263157895, 'recall': 0.844632768361582, 'f1-score': 0.7560050568900126, 'support': 708.0}  | {'precision': 0.5624033006704486, 'recall': 0.5349521707137601, 'f1-score': 0.5483343808925204, 'support': 4077.0}   | {'precision': 0.8264199106573069, 'recall': 0.6398221343873518, 'f1-score': 0.7212475633528265, 'support': 2024.0}   | {'precision': 0.8531785686832193, 'recall': 0.9073741007194245, 'f1-score': 0.8794421774097699, 'support': 12232.0} | {'precision': 0.9048757667117164, 'recall': 0.8820429671665991, 'f1-score': 0.8933134910453123, 'support': 9868.0} | 0.8212   | {'precision': 0.7174638534106857, 'recall': 0.6895292104262741, 'f1-score': 0.6988443638261499, 'support': 29334.0}   | {'precision': 0.8199722855692243, 'recall': 0.8211972455171473, 'f1-score': 0.81906491673643, 'support': 29334.0}   |
-| No log        | 5.0   | 205  | 0.5401          | {'precision': 0.45901639344262296, 'recall': 0.5915492957746479, 'f1-score': 0.5169230769230769, 'support': 284.0}    | {'precision': 0.688, 'recall': 0.6099290780141844, 'f1-score': 0.6466165413533834, 'support': 141.0}               | {'precision': 0.6872770511296076, 'recall': 0.8163841807909604, 'f1-score': 0.7462879276952873, 'support': 708.0} | {'precision': 0.5301336839798378, 'recall': 0.5933284277655139, 'f1-score': 0.5599537037037038, 'support': 4077.0}   | {'precision': 0.7659817351598174, 'recall': 0.6630434782608695, 'f1-score': 0.7108050847457628, 'support': 2024.0}   | {'precision': 0.864308426073132, 'recall': 0.8888979725310661, 'f1-score': 0.8764307593100111, 'support': 12232.0}  | {'precision': 0.9209399363127265, 'recall': 0.8499189298743413, 'f1-score': 0.8840052700922265, 'support': 9868.0} | 0.8132   | {'precision': 0.702236746585392, 'recall': 0.7161501947159407, 'f1-score': 0.7058603376890645, 'support': 29334.0}    | {'precision': 0.8210853899484308, 'recall': 0.8131519738187768, 'f1-score': 0.8158388468555539, 'support': 29334.0} |
-| No log        | 6.0   | 246  | 0.5609          | {'precision': 0.517799352750809, 'recall': 0.5633802816901409, 'f1-score': 0.5396290050590219, 'support': 284.0}      | {'precision': 0.6879432624113475, 'recall': 0.6879432624113475, 'f1-score': 0.6879432624113475, 'support': 141.0}  | {'precision': 0.7184466019417476, 'recall': 0.8361581920903954, 'f1-score': 0.7728459530026109, 'support': 708.0} | {'precision': 0.5675146771037182, 'recall': 0.5690458670591121, 'f1-score': 0.5682792406613595, 'support': 4077.0}   | {'precision': 0.7700845665961945, 'recall': 0.7198616600790514, 'f1-score': 0.744126659856997, 'support': 2024.0}    | {'precision': 0.8614670964698482, 'recall': 0.8957652060170046, 'f1-score': 0.8782814316059476, 'support': 12232.0} | {'precision': 0.915500480717872, 'recall': 0.8684637211187677, 'f1-score': 0.891362005304488, 'support': 9868.0}   | 0.8234   | {'precision': 0.7198222911416482, 'recall': 0.7343740272094027, 'f1-score': 0.7260667939859674, 'support': 29334.0}   | {'precision': 0.8248703886084983, 'recall': 0.8233790141133156, 'f1-score': 0.8236011159623022, 'support': 29334.0} |
-| No log        | 7.0   | 287  | 0.5639          | {'precision': 0.513595166163142, 'recall': 0.5985915492957746, 'f1-score': 0.5528455284552846, 'support': 284.0}      | {'precision': 0.6602564102564102, 'recall': 0.7304964539007093, 'f1-score': 0.6936026936026936, 'support': 141.0}  | {'precision': 0.7506666666666667, 'recall': 0.7951977401129944, 'f1-score': 0.7722908093278464, 'support': 708.0} | {'precision': 0.5732484076433121, 'recall': 0.5739514348785872, 'f1-score': 0.5735997058463046, 'support': 4077.0}   | {'precision': 0.7798969072164949, 'recall': 0.7475296442687747, 'f1-score': 0.7633703329969728, 'support': 2024.0}   | {'precision': 0.8836048129655398, 'recall': 0.8825212557226946, 'f1-score': 0.883062701951, 'support': 12232.0}     | {'precision': 0.9027186041793467, 'recall': 0.901803810295906, 'f1-score': 0.9022609753624656, 'support': 9868.0}  | 0.8312   | {'precision': 0.7234267107272733, 'recall': 0.74715598406792, 'f1-score': 0.7344332496489382, 'support': 29334.0}     | {'precision': 0.8318795778768913, 'recall': 0.8312197450057953, 'f1-score': 0.8314703017913034, 'support': 29334.0} |
-| No log        | 8.0   | 328  | 0.5766          | {'precision': 0.5232198142414861, 'recall': 0.5950704225352113, 'f1-score': 0.556836902800659, 'support': 284.0}      | {'precision': 0.6870748299319728, 'recall': 0.7163120567375887, 'f1-score': 0.7013888888888888, 'support': 141.0}  | {'precision': 0.7610146862483311, 'recall': 0.8050847457627118, 'f1-score': 0.7824296499656829, 'support': 708.0} | {'precision': 0.5692527367920038, 'recall': 0.5867059112092224, 'f1-score': 0.5778475661311753, 'support': 4077.0}   | {'precision': 0.7754259163655137, 'recall': 0.7420948616600791, 'f1-score': 0.7583943448624085, 'support': 2024.0}   | {'precision': 0.8839344262295082, 'recall': 0.881621975147155, 'f1-score': 0.8827766863130322, 'support': 12232.0}  | {'precision': 0.9100859247135843, 'recall': 0.9016011349817592, 'f1-score': 0.9058236611688048, 'support': 9868.0} | 0.8323   | {'precision': 0.7300011906460572, 'recall': 0.7469273011476754, 'f1-score': 0.7379282428758074, 'support': 29334.0}   | {'precision': 0.834103417381421, 'recall': 0.8323106293038794, 'f1-score': 0.8331173621878202, 'support': 29334.0}  |
-| No log        | 9.0   | 369  | 0.6424          | {'precision': 0.538961038961039, 'recall': 0.5845070422535211, 'f1-score': 0.5608108108108107, 'support': 284.0}      | {'precision': 0.6604938271604939, 'recall': 0.7588652482269503, 'f1-score': 0.7062706270627063, 'support': 141.0}  | {'precision': 0.7619047619047619, 'recall': 0.8135593220338984, 'f1-score': 0.7868852459016393, 'support': 708.0} | {'precision': 0.5726765348216453, 'recall': 0.5788570026980623, 'f1-score': 0.5757501829714565, 'support': 4077.0}   | {'precision': 0.7521697203471552, 'recall': 0.7707509881422925, 'f1-score': 0.7613469985358712, 'support': 2024.0}   | {'precision': 0.8750705702072747, 'recall': 0.8870176586003924, 'f1-score': 0.881003613332792, 'support': 12232.0}  | {'precision': 0.914336766869876, 'recall': 0.8815362788812323, 'f1-score': 0.8976369827675162, 'support': 9868.0}  | 0.8290   | {'precision': 0.725087602896035, 'recall': 0.75358479154805, 'f1-score': 0.7385292087689704, 'support': 29334.0}      | {'precision': 0.8307545957871735, 'recall': 0.829003886275312, 'f1-score': 0.8297056980988704, 'support': 29334.0}  |
-| No log        | 10.0  | 410  | 0.6875          | {'precision': 0.5598455598455598, 'recall': 0.5105633802816901, 'f1-score': 0.5340699815837938, 'support': 284.0}     | {'precision': 0.6688741721854304, 'recall': 0.7163120567375887, 'f1-score': 0.6917808219178082, 'support': 141.0}  | {'precision': 0.7392373923739237, 'recall': 0.8488700564971752, 'f1-score': 0.7902695595003287, 'support': 708.0} | {'precision': 0.6084390675715551, 'recall': 0.5057640421878833, 'f1-score': 0.5523707473881597, 'support': 4077.0}   | {'precision': 0.7721649484536083, 'recall': 0.7401185770750988, 'f1-score': 0.7558022199798183, 'support': 2024.0}   | {'precision': 0.8521132047143608, 'recall': 0.92797580117724, 'f1-score': 0.8884279732321058, 'support': 12232.0}   | {'precision': 0.9175562836909418, 'recall': 0.8797122010539117, 'f1-score': 0.8982358114749858, 'support': 9868.0} | 0.8331   | {'precision': 0.7311758041193401, 'recall': 0.7327594450015126, 'f1-score': 0.7301367307252857, 'support': 29334.0}   | {'precision': 0.8283101361138144, 'recall': 0.8331287925274425, 'f1-score': 0.8291241905412626, 'support': 29334.0} |
-| No log        | 11.0  | 451  | 0.7223          | {'precision': 0.5514705882352942, 'recall': 0.528169014084507, 'f1-score': 0.539568345323741, 'support': 284.0}       | {'precision': 0.7050359712230215, 'recall': 0.6950354609929078, 'f1-score': 0.7, 'support': 141.0}                 | {'precision': 0.7415307402760352, 'recall': 0.8347457627118644, 'f1-score': 0.7853820598006644, 'support': 708.0} | {'precision': 0.5881745416989413, 'recall': 0.5587441746382144, 'f1-score': 0.5730817610062893, 'support': 4077.0}   | {'precision': 0.7887840670859538, 'recall': 0.7435770750988142, 'f1-score': 0.7655137334689724, 'support': 2024.0}   | {'precision': 0.8658698539176627, 'recall': 0.9061478090255068, 'f1-score': 0.8855510725841887, 'support': 12232.0} | {'precision': 0.9162824811399832, 'recall': 0.8861978111066072, 'f1-score': 0.9009890789202555, 'support': 9868.0} | 0.8335   | {'precision': 0.7367354633681273, 'recall': 0.7360881582369173, 'f1-score': 0.7357265787291587, 'support': 29334.0}   | {'precision': 0.8320963257113063, 'recall': 0.8335378741392241, 'f1-score': 0.8323741390608008, 'support': 29334.0} |
-| No log        | 12.0  | 492  | 0.7229          | {'precision': 0.4842105263157895, 'recall': 0.647887323943662, 'f1-score': 0.5542168674698795, 'support': 284.0}      | {'precision': 0.6688311688311688, 'recall': 0.7304964539007093, 'f1-score': 0.6983050847457627, 'support': 141.0}  | {'precision': 0.7662517289073306, 'recall': 0.7824858757062146, 'f1-score': 0.7742837176799442, 'support': 708.0} | {'precision': 0.5374846374436706, 'recall': 0.6436104979151337, 'f1-score': 0.5857796629088069, 'support': 4077.0}   | {'precision': 0.7547452547452548, 'recall': 0.7465415019762845, 'f1-score': 0.7506209637357178, 'support': 2024.0}   | {'precision': 0.8857740585774059, 'recall': 0.8653531720078482, 'f1-score': 0.8754445455297329, 'support': 12232.0} | {'precision': 0.9279454722492697, 'recall': 0.8691730847182814, 'f1-score': 0.8975982418502434, 'support': 9868.0} | 0.8229   | {'precision': 0.7178918352956986, 'recall': 0.755078272881162, 'f1-score': 0.7337498691314411, 'support': 29334.0}    | {'precision': 0.8346973026345582, 'recall': 0.8228676620985886, 'f1-score': 0.8276221833778615, 'support': 29334.0} |
-| 0.3184        | 13.0  | 533  | 0.7460          | {'precision': 0.5433333333333333, 'recall': 0.573943661971831, 'f1-score': 0.5582191780821917, 'support': 284.0}      | {'precision': 0.7299270072992701, 'recall': 0.7092198581560284, 'f1-score': 0.7194244604316545, 'support': 141.0}  | {'precision': 0.75, 'recall': 0.8220338983050848, 'f1-score': 0.784366576819407, 'support': 708.0}                | {'precision': 0.5741638390693166, 'recall': 0.5810645082168261, 'f1-score': 0.577593563330489, 'support': 4077.0}    | {'precision': 0.8051082731815657, 'recall': 0.7164031620553359, 'f1-score': 0.7581699346405228, 'support': 2024.0}   | {'precision': 0.873641304347826, 'recall': 0.8936396337475474, 'f1-score': 0.8835273197542839, 'support': 12232.0}  | {'precision': 0.9082834125180748, 'recall': 0.8911633563032023, 'f1-score': 0.8996419437340154, 'support': 9868.0} | 0.8314   | {'precision': 0.7406367385356267, 'recall': 0.7410668683936937, 'f1-score': 0.7401347109703663, 'support': 29334.0}   | {'precision': 0.8320703838894091, 'recall': 0.8314242858116861, 'f1-score': 0.8314468675699472, 'support': 29334.0} |
-| 0.3184        | 14.0  | 574  | 0.7719          | {'precision': 0.5286624203821656, 'recall': 0.5845070422535211, 'f1-score': 0.5551839464882944, 'support': 284.0}     | {'precision': 0.6917808219178082, 'recall': 0.7163120567375887, 'f1-score': 0.7038327526132405, 'support': 141.0}  | {'precision': 0.751937984496124, 'recall': 0.8220338983050848, 'f1-score': 0.7854251012145749, 'support': 708.0}  | {'precision': 0.5745517071972488, 'recall': 0.5737061564876135, 'f1-score': 0.5741286205203731, 'support': 4077.0}   | {'precision': 0.7785304846274101, 'recall': 0.7381422924901185, 'f1-score': 0.7577986304844027, 'support': 2024.0}   | {'precision': 0.8700618752974774, 'recall': 0.8966644865925442, 'f1-score': 0.8831628955632499, 'support': 12232.0} | {'precision': 0.9169823232323232, 'recall': 0.8831576813944062, 'f1-score': 0.8997522196985339, 'support': 9868.0} | 0.8306   | {'precision': 0.7303582310215082, 'recall': 0.7449319448944111, 'f1-score': 0.7370405952260956, 'support': 29334.0}   | {'precision': 0.8314455836819585, 'recall': 0.830606122588123, 'f1-score': 0.8307460246491396, 'support': 29334.0}  |
-| 0.3184        | 15.0  | 615  | 0.7737          | {'precision': 0.5240963855421686, 'recall': 0.6126760563380281, 'f1-score': 0.564935064935065, 'support': 284.0}      | {'precision': 0.696551724137931, 'recall': 0.7163120567375887, 'f1-score': 0.7062937062937064, 'support': 141.0}   | {'precision': 0.7532637075718016, 'recall': 0.8149717514124294, 'f1-score': 0.7829036635006784, 'support': 708.0} | {'precision': 0.5683770605990248, 'recall': 0.6004415011037527, 'f1-score': 0.583969465648855, 'support': 4077.0}    | {'precision': 0.789280084077772, 'recall': 0.7420948616600791, 'f1-score': 0.7649605296664119, 'support': 2024.0}    | {'precision': 0.8766526926797807, 'recall': 0.8889797253106606, 'f1-score': 0.8827731774638741, 'support': 12232.0} | {'precision': 0.9183285849952516, 'recall': 0.8819416295095257, 'f1-score': 0.8997673817523908, 'support': 9868.0} | 0.8311   | {'precision': 0.7323643199433901, 'recall': 0.7510596545817235, 'f1-score': 0.7408004270372831, 'support': 29334.0}   | {'precision': 0.8345410190013676, 'recall': 0.8310833844685348, 'f1-score': 0.8324958893486518, 'support': 29334.0} |
-| 0.3184        | 16.0  | 656  | 0.7711          | {'precision': 0.5466666666666666, 'recall': 0.5774647887323944, 'f1-score': 0.5616438356164384, 'support': 284.0}     | {'precision': 0.7299270072992701, 'recall': 0.7092198581560284, 'f1-score': 0.7194244604316545, 'support': 141.0}  | {'precision': 0.754863813229572, 'recall': 0.8220338983050848, 'f1-score': 0.7870182555780934, 'support': 708.0}  | {'precision': 0.5857645875251509, 'recall': 0.5712533725778759, 'f1-score': 0.5784179808766918, 'support': 4077.0}   | {'precision': 0.7987048030221263, 'recall': 0.7312252964426877, 'f1-score': 0.7634769151405727, 'support': 2024.0}   | {'precision': 0.8739856801909308, 'recall': 0.8981360366252452, 'f1-score': 0.8858962986855898, 'support': 12232.0} | {'precision': 0.9090161406394571, 'recall': 0.896027563842724, 'f1-score': 0.9024751212043889, 'support': 9868.0}  | 0.8346   | {'precision': 0.7427040997961676, 'recall': 0.7436229735260057, 'f1-score': 0.7426218382190614, 'support': 29334.0}   | {'precision': 0.8337806464072924, 'recall': 0.8346287584373082, 'f1-score': 0.8339657063145517, 'support': 29334.0} |
 ### Framework versions

       name: essays_su_g
       type: essays_su_g
       config: full_labels
+      split: train[20%:40%]
       args: full_labels
     metrics:
     - name: Accuracy
       type: accuracy
+      value: 0.8449945467164623
 ---
 <!-- 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: 0.6708
+- B-claim: {'precision': 0.5619047619047619, 'recall': 0.6, 'f1-score': 0.580327868852459, 'support': 295.0}
+- B-majorclaim: {'precision': 0.6789473684210526, 'recall': 0.8269230769230769, 'f1-score': 0.7456647398843931, 'support': 156.0}
+- B-premise: {'precision': 0.7630573248407644, 'recall': 0.8239339752407153, 'f1-score': 0.7923280423280424, 'support': 727.0}
+- I-claim: {'precision': 0.5966467065868264, 'recall': 0.6012551291334781, 'f1-score': 0.5989420533782159, 'support': 4143.0}
+- I-majorclaim: {'precision': 0.7935897435897435, 'recall': 0.8467852257181943, 'f1-score': 0.8193249503639972, 'support': 2193.0}
+- I-premise: {'precision': 0.8916157064692629, 'recall': 0.8820345458887209, 'f1-score': 0.8867992477291825, 'support': 12563.0}
+- O: {'precision': 0.9210893854748603, 'recall': 0.9069744597249508, 'f1-score': 0.9139774302118391, 'support': 10180.0}
+- Accuracy: 0.8450
+- Macro avg: {'precision': 0.7438358567553245, 'recall': 0.7839866303755908, 'f1-score': 0.7624806189640186, 'support': 30257.0}
+- Weighted avg: {'precision': 0.8466380687769368, 'recall': 0.8449945467164623, 'f1-score': 0.8456518702970672, 'support': 30257.0}
 ## Model description
 ### 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   | 41   | 0.6795          | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 295.0}                                                 | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 156.0}                                                 | {'precision': 0.8727272727272727, 'recall': 0.06602475928473177, 'f1-score': 0.1227621483375959, 'support': 727.0} | {'precision': 0.5111008325624422, 'recall': 0.26671494086410813, 'f1-score': 0.35051546391752586, 'support': 4143.0} | {'precision': 0.4952120383036936, 'recall': 0.16507067943456452, 'f1-score': 0.2476060191518468, 'support': 2193.0} | {'precision': 0.7927029242962558, 'recall': 0.9235055321181247, 'f1-score': 0.8531195999852935, 'support': 12563.0} | {'precision': 0.7493095557484416, 'recall': 0.9328094302554027, 'f1-score': 0.8310506279263117, 'support': 10180.0} | 0.7474   | {'precision': 0.48872180337687227, 'recall': 0.3363036202795617, 'f1-score': 0.34357912275979624, 'support': 30257.0} | {'precision': 0.7080894203665903, 'recall': 0.7473642462901147, 'f1-score': 0.7027223642713039, 'support': 30257.0} |
+| No log        | 2.0   | 82   | 0.5111          | {'precision': 0.6470588235294118, 'recall': 0.07457627118644068, 'f1-score': 0.1337386018237082, 'support': 295.0}   | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 156.0}                                                 | {'precision': 0.6562150055991042, 'recall': 0.8060522696011004, 'f1-score': 0.7234567901234568, 'support': 727.0}  | {'precision': 0.5315296566077004, 'recall': 0.6164615013275404, 'f1-score': 0.5708538220831472, 'support': 4143.0}   | {'precision': 0.5701344243132671, 'recall': 0.8896488828089375, 'f1-score': 0.6949243098842386, 'support': 2193.0}  | {'precision': 0.914638511095204, 'recall': 0.8136591578444639, 'f1-score': 0.861198871056068, 'support': 12563.0}   | {'precision': 0.9145764077767704, 'recall': 0.8918467583497053, 'f1-score': 0.9030685830805192, 'support': 10180.0} | 0.8069   | {'precision': 0.6048789755602082, 'recall': 0.5846064058740269, 'f1-score': 0.5553201397215911, 'support': 30257.0}   | {'precision': 0.8236564850419075, 'recall': 0.8068876623591235, 'f1-score': 0.8086360829977005, 'support': 30257.0} |
+| No log        | 3.0   | 123  | 0.4232          | {'precision': 0.46254071661237783, 'recall': 0.48135593220338985, 'f1-score': 0.47176079734219273, 'support': 295.0} | {'precision': 0.6666666666666666, 'recall': 0.038461538461538464, 'f1-score': 0.07272727272727274, 'support': 156.0} | {'precision': 0.7320341047503045, 'recall': 0.8266850068775791, 'f1-score': 0.7764857881136951, 'support': 727.0}  | {'precision': 0.5594361455922575, 'recall': 0.6418054549843109, 'f1-score': 0.597796762589928, 'support': 4143.0}    | {'precision': 0.7543689320388349, 'recall': 0.7086183310533516, 'f1-score': 0.730778274159417, 'support': 2193.0}   | {'precision': 0.8918637274549098, 'recall': 0.8856164928759054, 'f1-score': 0.8887291317197858, 'support': 12563.0} | {'precision': 0.934092758340114, 'recall': 0.9021611001964637, 'f1-score': 0.9178492904257447, 'support': 10180.0}  | 0.8352   | {'precision': 0.7144290073507807, 'recall': 0.6406719795217912, 'f1-score': 0.6365896167254336, 'support': 30257.0}   | {'precision': 0.841400720911604, 'recall': 0.835244736755131, 'f1-score': 0.836272553745959, 'support': 30257.0}    |
+| No log        | 4.0   | 164  | 0.4295          | {'precision': 0.523972602739726, 'recall': 0.5186440677966102, 'f1-score': 0.5212947189097104, 'support': 295.0}     | {'precision': 0.7076923076923077, 'recall': 0.5897435897435898, 'f1-score': 0.6433566433566433, 'support': 156.0}    | {'precision': 0.7304878048780488, 'recall': 0.8239339752407153, 'f1-score': 0.7744020685197156, 'support': 727.0}  | {'precision': 0.5975518361229079, 'recall': 0.5773594013999517, 'f1-score': 0.5872821016449792, 'support': 4143.0}   | {'precision': 0.7692971108236308, 'recall': 0.8134974920200638, 'f1-score': 0.7907801418439716, 'support': 2193.0}  | {'precision': 0.9042123485285631, 'recall': 0.873119477831728, 'f1-score': 0.8883939418482223, 'support': 12563.0}  | {'precision': 0.8958530581329294, 'recall': 0.9294695481335953, 'f1-score': 0.9123517500723171, 'support': 10180.0} | 0.8412   | {'precision': 0.7327238669883019, 'recall': 0.7322525074523221, 'f1-score': 0.7311230523136514, 'support': 30257.0}   | {'precision': 0.8407365647422267, 'recall': 0.8411607231384473, 'f1-score': 0.8405678153025818, 'support': 30257.0} |
+| No log        | 5.0   | 205  | 0.4565          | {'precision': 0.5276073619631901, 'recall': 0.5830508474576271, 'f1-score': 0.5539452495974235, 'support': 295.0}    | {'precision': 0.7123287671232876, 'recall': 0.6666666666666666, 'f1-score': 0.6887417218543046, 'support': 156.0}    | {'precision': 0.7634146341463415, 'recall': 0.8610729023383769, 'f1-score': 0.8093083387201035, 'support': 727.0}  | {'precision': 0.5808294015396076, 'recall': 0.5645667390779628, 'f1-score': 0.5725826193390453, 'support': 4143.0}   | {'precision': 0.7949438202247191, 'recall': 0.774281805745554, 'f1-score': 0.7844767844767844, 'support': 2193.0}   | {'precision': 0.8697251839615557, 'recall': 0.9219931545013134, 'f1-score': 0.8950967891503419, 'support': 12563.0} | {'precision': 0.9528679881906369, 'recall': 0.887721021611002, 'f1-score': 0.9191415785191211, 'support': 10180.0}  | 0.8447   | {'precision': 0.7431024510213342, 'recall': 0.7513361624855005, 'f1-score': 0.7461847259510178, 'support': 30257.0}   | {'precision': 0.8460194835144224, 'recall': 0.8447301450903923, 'f1-score': 0.8445567746699831, 'support': 30257.0} |
+| No log        | 6.0   | 246  | 0.4916          | {'precision': 0.5593869731800766, 'recall': 0.49491525423728816, 'f1-score': 0.5251798561151079, 'support': 295.0}   | {'precision': 0.6492146596858639, 'recall': 0.7948717948717948, 'f1-score': 0.7146974063400577, 'support': 156.0}    | {'precision': 0.7337278106508875, 'recall': 0.8528198074277854, 'f1-score': 0.7888040712468193, 'support': 727.0}  | {'precision': 0.6394230769230769, 'recall': 0.41733043688148685, 'f1-score': 0.5050387030816416, 'support': 4143.0}  | {'precision': 0.7733443027560675, 'recall': 0.8572731418148655, 'f1-score': 0.8131487889273357, 'support': 2193.0}  | {'precision': 0.8424233805020266, 'recall': 0.9430072434927963, 'f1-score': 0.8898820701569895, 'support': 12563.0} | {'precision': 0.9398688793280066, 'recall': 0.9012770137524558, 'f1-score': 0.9201684886169893, 'support': 10180.0} | 0.8435   | {'precision': 0.7339127261465722, 'recall': 0.7516420989254959, 'f1-score': 0.7367027692121344, 'support': 30257.0}   | {'precision': 0.8360386273187937, 'recall': 0.8434742373665598, 'f1-score': 0.8349273131912464, 'support': 30257.0} |
+| No log        | 7.0   | 287  | 0.5145          | {'precision': 0.5668789808917197, 'recall': 0.6033898305084746, 'f1-score': 0.5845648604269295, 'support': 295.0}    | {'precision': 0.6777777777777778, 'recall': 0.782051282051282, 'f1-score': 0.7261904761904762, 'support': 156.0}     | {'precision': 0.758873929008568, 'recall': 0.8528198074277854, 'f1-score': 0.8031088082901554, 'support': 727.0}   | {'precision': 0.6070287539936102, 'recall': 0.5503258508327299, 'f1-score': 0.5772882643372579, 'support': 4143.0}   | {'precision': 0.7948040510788199, 'recall': 0.8230734154126766, 'f1-score': 0.8086917562724014, 'support': 2193.0}  | {'precision': 0.8718995765275257, 'recall': 0.9177744169386293, 'f1-score': 0.8942490402140614, 'support': 12563.0} | {'precision': 0.9417225373904075, 'recall': 0.8968565815324165, 'f1-score': 0.9187421383647798, 'support': 10180.0} | 0.8482   | {'precision': 0.745569372381204, 'recall': 0.7751844549577135, 'f1-score': 0.7589764777280089, 'support': 30257.0}    | {'precision': 0.8468453317066018, 'recall': 0.8482334666358198, 'f1-score': 0.8468124537513947, 'support': 30257.0} |
+| No log        | 8.0   | 328  | 0.5386          | {'precision': 0.5384615384615384, 'recall': 0.6169491525423729, 'f1-score': 0.5750394944707741, 'support': 295.0}    | {'precision': 0.686046511627907, 'recall': 0.7564102564102564, 'f1-score': 0.7195121951219512, 'support': 156.0}     | {'precision': 0.7537688442211056, 'recall': 0.8253094910591472, 'f1-score': 0.7879185817465528, 'support': 727.0}  | {'precision': 0.5808619091751622, 'recall': 0.6051170649287956, 'f1-score': 0.5927414588012767, 'support': 4143.0}   | {'precision': 0.8207132388861749, 'recall': 0.7660738714090287, 'f1-score': 0.7924528301886793, 'support': 2193.0}  | {'precision': 0.8846666144323435, 'recall': 0.8987502984955823, 'f1-score': 0.8916528468767275, 'support': 12563.0} | {'precision': 0.9284478371501272, 'recall': 0.8960707269155206, 'f1-score': 0.9119720069982503, 'support': 10180.0} | 0.8428   | {'precision': 0.7418523562791942, 'recall': 0.7663829802515292, 'f1-score': 0.7530413448863159, 'support': 30257.0}   | {'precision': 0.8456178749149208, 'recall': 0.8427801830981261, 'f1-score': 0.8439033621710555, 'support': 30257.0} |
+| No log        | 9.0   | 369  | 0.5474          | {'precision': 0.5585284280936454, 'recall': 0.5661016949152542, 'f1-score': 0.5622895622895623, 'support': 295.0}    | {'precision': 0.6875, 'recall': 0.7756410256410257, 'f1-score': 0.7289156626506025, 'support': 156.0}                | {'precision': 0.7355769230769231, 'recall': 0.8418156808803301, 'f1-score': 0.7851186658114176, 'support': 727.0}  | {'precision': 0.604811876119785, 'recall': 0.570359642770939, 'f1-score': 0.587080745341615, 'support': 4143.0}      | {'precision': 0.8211678832116789, 'recall': 0.8207934336525308, 'f1-score': 0.8209806157354618, 'support': 2193.0}  | {'precision': 0.888625217528872, 'recall': 0.8942131656451484, 'f1-score': 0.8914104344376116, 'support': 12563.0}  | {'precision': 0.91595650896268, 'recall': 0.918565815324165, 'f1-score': 0.917259306488793, 'support': 10180.0}     | 0.8477   | {'precision': 0.7445952624276548, 'recall': 0.7696414941184847, 'f1-score': 0.7561507132507234, 'support': 30257.0}   | {'precision': 0.8461371897103921, 'recall': 0.8476716131804211, 'f1-score': 0.8467310896799954, 'support': 30257.0} |
+| No log        | 10.0  | 410  | 0.5962          | {'precision': 0.5531914893617021, 'recall': 0.6169491525423729, 'f1-score': 0.5833333333333334, 'support': 295.0}    | {'precision': 0.6582914572864321, 'recall': 0.8397435897435898, 'f1-score': 0.7380281690140845, 'support': 156.0}    | {'precision': 0.7450248756218906, 'recall': 0.8239339752407153, 'f1-score': 0.782495101241019, 'support': 727.0}   | {'precision': 0.6161803713527851, 'recall': 0.5607048032826454, 'f1-score': 0.5871350941488689, 'support': 4143.0}   | {'precision': 0.776742301458671, 'recall': 0.8741450068399452, 'f1-score': 0.8225702638918686, 'support': 2193.0}   | {'precision': 0.8831158622858041, 'recall': 0.8942927644670858, 'f1-score': 0.888669171445521, 'support': 12563.0}  | {'precision': 0.9232313095835424, 'recall': 0.9037328094302554, 'f1-score': 0.9133780094316207, 'support': 10180.0} | 0.8457   | {'precision': 0.7365396667072609, 'recall': 0.7876431573638013, 'f1-score': 0.7593727346437593, 'support': 30257.0}   | {'precision': 0.8446583764532496, 'recall': 0.8456555507816373, 'f1-score': 0.844598799846626, 'support': 30257.0}  |
+| No log        | 11.0  | 451  | 0.5957          | {'precision': 0.5545171339563862, 'recall': 0.6033898305084746, 'f1-score': 0.577922077922078, 'support': 295.0}     | {'precision': 0.6467661691542289, 'recall': 0.8333333333333334, 'f1-score': 0.7282913165266107, 'support': 156.0}    | {'precision': 0.7694300518134715, 'recall': 0.8170563961485557, 'f1-score': 0.7925283522348232, 'support': 727.0}  | {'precision': 0.6102831594634873, 'recall': 0.5930485155684286, 'f1-score': 0.6015424164524421, 'support': 4143.0}   | {'precision': 0.783003300330033, 'recall': 0.8654810761513908, 'f1-score': 0.8221789040502492, 'support': 2193.0}   | {'precision': 0.892235181338872, 'recall': 0.8890392422192152, 'f1-score': 0.8906343447230972, 'support': 12563.0}  | {'precision': 0.9259629814907454, 'recall': 0.9091355599214146, 'f1-score': 0.917472118959108, 'support': 10180.0}  | 0.8488   | {'precision': 0.7403139967924607, 'recall': 0.7872119934072589, 'f1-score': 0.7615099329812013, 'support': 30257.0}   | {'precision': 0.8495500818518233, 'recall': 0.8487622698879598, 'f1-score': 0.8488747259194414, 'support': 30257.0} |
+| No log        | 12.0  | 492  | 0.6363          | {'precision': 0.546583850931677, 'recall': 0.5966101694915255, 'f1-score': 0.5705024311183144, 'support': 295.0}     | {'precision': 0.6580310880829016, 'recall': 0.8141025641025641, 'f1-score': 0.7277936962750716, 'support': 156.0}    | {'precision': 0.7600502512562815, 'recall': 0.8321870701513068, 'f1-score': 0.7944845699277742, 'support': 727.0}  | {'precision': 0.6018252933507171, 'recall': 0.5570842384745354, 'f1-score': 0.5785911255953873, 'support': 4143.0}   | {'precision': 0.7675276752767528, 'recall': 0.853625170998632, 'f1-score': 0.8082901554404146, 'support': 2193.0}   | {'precision': 0.8818805551224076, 'recall': 0.9003422749343309, 'f1-score': 0.8910157942416007, 'support': 12563.0} | {'precision': 0.9259597806215722, 'recall': 0.8955795677799607, 'f1-score': 0.9105163287725957, 'support': 10180.0} | 0.8433   | {'precision': 0.73455121352033, 'recall': 0.7785044365618364, 'f1-score': 0.7544563001958797, 'support': 30257.0}     | {'precision': 0.8427252530453597, 'recall': 0.8433089863502661, 'f1-score': 0.8425156264772145, 'support': 30257.0} |
+| 0.3164        | 13.0  | 533  | 0.6392          | {'precision': 0.564935064935065, 'recall': 0.5898305084745763, 'f1-score': 0.5771144278606964, 'support': 295.0}     | {'precision': 0.6615384615384615, 'recall': 0.8269230769230769, 'f1-score': 0.7350427350427349, 'support': 156.0}    | {'precision': 0.7632911392405063, 'recall': 0.8294360385144429, 'f1-score': 0.7949901120632828, 'support': 727.0}  | {'precision': 0.6016421995521274, 'recall': 0.5836350470673425, 'f1-score': 0.5925018377848567, 'support': 4143.0}   | {'precision': 0.7977147693609818, 'recall': 0.8595531235750113, 'f1-score': 0.8274802458296752, 'support': 2193.0}  | {'precision': 0.8831720556997876, 'recall': 0.8935763750696489, 'f1-score': 0.8883437524728971, 'support': 12563.0} | {'precision': 0.9303008813696687, 'recall': 0.9020628683693517, 'f1-score': 0.9159642910578025, 'support': 10180.0} | 0.8467   | {'precision': 0.743227795956657, 'recall': 0.7835738625704929, 'f1-score': 0.7616339145874208, 'support': 30257.0}    | {'precision': 0.8471598021098077, 'recall': 0.8466801070826585, 'f1-score': 0.8466487613672259, 'support': 30257.0} |
+| 0.3164        | 14.0  | 574  | 0.6574          | {'precision': 0.5741935483870968, 'recall': 0.6033898305084746, 'f1-score': 0.5884297520661158, 'support': 295.0}    | {'precision': 0.673469387755102, 'recall': 0.8461538461538461, 'f1-score': 0.75, 'support': 156.0}                   | {'precision': 0.7689295039164491, 'recall': 0.8101788170563962, 'f1-score': 0.7890154052243804, 'support': 727.0}  | {'precision': 0.5957288303948348, 'recall': 0.5790489983104031, 'f1-score': 0.5872705018359853, 'support': 4143.0}   | {'precision': 0.7902335456475584, 'recall': 0.8486092111263109, 'f1-score': 0.8183817062445031, 'support': 2193.0}  | {'precision': 0.8890226287915263, 'recall': 0.8818753482448459, 'f1-score': 0.8854345654345654, 'support': 12563.0} | {'precision': 0.9146040824376295, 'recall': 0.9111001964636543, 'f1-score': 0.9128487771271099, 'support': 10180.0} | 0.8432   | {'precision': 0.7437402181900282, 'recall': 0.782908035409133, 'f1-score': 0.7616258154189514, 'support': 30257.0}    | {'precision': 0.8432431379603119, 'recall': 0.8432098357404898, 'f1-score': 0.8430607378149431, 'support': 30257.0} |
+| 0.3164        | 15.0  | 615  | 0.6657          | {'precision': 0.5636942675159236, 'recall': 0.6, 'f1-score': 0.5812807881773399, 'support': 295.0}                   | {'precision': 0.6717948717948717, 'recall': 0.8397435897435898, 'f1-score': 0.7464387464387464, 'support': 156.0}    | {'precision': 0.7634271099744245, 'recall': 0.8211829436038515, 'f1-score': 0.7912524850894631, 'support': 727.0}  | {'precision': 0.5987460815047022, 'recall': 0.5993241612358194, 'f1-score': 0.5990349819059108, 'support': 4143.0}   | {'precision': 0.793854033290653, 'recall': 0.8481532147742818, 'f1-score': 0.8201058201058201, 'support': 2193.0}   | {'precision': 0.8901107721945738, 'recall': 0.8826713364642204, 'f1-score': 0.8863754446265136, 'support': 12563.0} | {'precision': 0.9214414054701537, 'recall': 0.906777996070727, 'f1-score': 0.9140508961283296, 'support': 10180.0}  | 0.8450   | {'precision': 0.7432955059636147, 'recall': 0.7854076059846414, 'f1-score': 0.7626484517817319, 'support': 30257.0}   | {'precision': 0.8464277148202262, 'recall': 0.8450275969197211, 'f1-score': 0.8455573804598716, 'support': 30257.0} |
+| 0.3164        | 16.0  | 656  | 0.6708          | {'precision': 0.5619047619047619, 'recall': 0.6, 'f1-score': 0.580327868852459, 'support': 295.0}                    | {'precision': 0.6789473684210526, 'recall': 0.8269230769230769, 'f1-score': 0.7456647398843931, 'support': 156.0}    | {'precision': 0.7630573248407644, 'recall': 0.8239339752407153, 'f1-score': 0.7923280423280424, 'support': 727.0}  | {'precision': 0.5966467065868264, 'recall': 0.6012551291334781, 'f1-score': 0.5989420533782159, 'support': 4143.0}   | {'precision': 0.7935897435897435, 'recall': 0.8467852257181943, 'f1-score': 0.8193249503639972, 'support': 2193.0}  | {'precision': 0.8916157064692629, 'recall': 0.8820345458887209, 'f1-score': 0.8867992477291825, 'support': 12563.0} | {'precision': 0.9210893854748603, 'recall': 0.9069744597249508, 'f1-score': 0.9139774302118391, 'support': 10180.0} | 0.8450   | {'precision': 0.7438358567553245, 'recall': 0.7839866303755908, 'f1-score': 0.7624806189640186, 'support': 30257.0}   | {'precision': 0.8466380687769368, 'recall': 0.8449945467164623, 'f1-score': 0.8456518702970672, 'support': 30257.0} |
 ### Framework versions

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5320294299a3711fa3951e5c22d23d096a249c8fdfb70f42cb07e98d29df3c0b
 size 592330980

 version https://git-lfs.github.com/spec/v1
+oid sha256:36839a5b9a0527a68deeb5c6cc49397d4f6a1411f1e1b3337afdc01262dc4b52
 size 592330980