trainer: training complete at 2024-03-02 16:09:47.166003.

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README.md +31 -31
meta_data/README_s42_e16.md +31 -31
meta_data/meta_s42_e16_cvi4.json +1 -1
model.safetensors +1 -1

README.md CHANGED Viewed

@@ -17,12 +17,12 @@ model-index:
       name: essays_su_g
       type: essays_su_g
       config: sep_tok_full_labels
-      split: train[60%:80%]
       args: sep_tok_full_labels
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9161077515118197
 ---
 <!-- 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: 0.4671
-- B-claim: {'precision': 0.7346278317152104, 'recall': 0.6696165191740413, 'f1-score': 0.7006172839506173, 'support': 339.0}
-- B-majorclaim: {'precision': 0.9490445859872612, 'recall': 0.93125, 'f1-score': 0.9400630914826499, 'support': 160.0}
-- B-premise: {'precision': 0.8921971252566735, 'recall': 0.9234856535600425, 'f1-score': 0.9075718015665796, 'support': 941.0}
-- I-claim: {'precision': 0.7273820981713186, 'recall': 0.6434653043848446, 'f1-score': 0.6828552066862436, 'support': 4698.0}
-- I-majorclaim: {'precision': 0.9140926640926641, 'recall': 0.9339250493096647, 'f1-score': 0.9239024390243903, 'support': 2028.0}
-- I-premise: {'precision': 0.9001753588361369, 'recall': 0.9326424870466321, 'f1-score': 0.9161213563355145, 'support': 14861.0}
-- O: {'precision': 0.999324070597071, 'recall': 0.9964801917172171, 'f1-score': 0.9979001049947502, 'support': 13353.0}
-- Accuracy: 0.9161
-- Macro avg: {'precision': 0.8738348192366193, 'recall': 0.8615521721703489, 'f1-score': 0.8670044691486779, 'support': 36380.0}
-- Weighted avg: {'precision': 0.9134949094533051, 'recall': 0.9161077515118197, 'f1-score': 0.914324131528891, 'support': 36380.0}
 ## 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   | 0.4724          | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 339.0}                                                 | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 160.0}                                   | {'precision': 0.8, 'recall': 0.7863974495217854, 'f1-score': 0.7931404072883173, 'support': 941.0}                | {'precision': 0.46561443066516345, 'recall': 0.35163899531715626, 'f1-score': 0.40067911714770804, 'support': 4698.0} | {'precision': 0.4144271570014144, 'recall': 0.8668639053254438, 'f1-score': 0.5607655502392344, 'support': 2028.0} | {'precision': 0.8844441252513645, 'recall': 0.8286790929277976, 'f1-score': 0.8556539864512767, 'support': 14861.0} | {'precision': 0.9700167382286587, 'recall': 0.9982026510896428, 'f1-score': 0.9839078762825717, 'support': 13353.0} | 0.8190   | {'precision': 0.5049289215923716, 'recall': 0.5473974420259752, 'f1-score': 0.5134495624870155, 'support': 36380.0} | {'precision': 0.8212499318469384, 'recall': 0.8189664650907091, 'f1-score': 0.8141826255128369, 'support': 36380.0} |
-| No log        | 2.0   | 82   | 0.2806          | {'precision': 0.39147286821705424, 'recall': 0.29793510324483774, 'f1-score': 0.33835845896147404, 'support': 339.0} | {'precision': 1.0, 'recall': 0.0125, 'f1-score': 0.02469135802469136, 'support': 160.0}                | {'precision': 0.788975021533161, 'recall': 0.973432518597237, 'f1-score': 0.8715509039010466, 'support': 941.0}   | {'precision': 0.6001651073197578, 'recall': 0.46424010217113665, 'f1-score': 0.5235237638022083, 'support': 4698.0}   | {'precision': 0.890087660148348, 'recall': 0.650887573964497, 'f1-score': 0.7519225291939617, 'support': 2028.0}   | {'precision': 0.8537944400702562, 'recall': 0.9485902698337931, 'f1-score': 0.8986994772408516, 'support': 14861.0} | {'precision': 0.9998499737454054, 'recall': 0.9982026510896428, 'f1-score': 0.9990256333383302, 'support': 13353.0} | 0.8781   | {'precision': 0.7891921530048547, 'recall': 0.6208268884144491, 'f1-score': 0.6296817320660805, 'support': 36380.0} | {'precision': 0.871331614069924, 'recall': 0.8781198460692689, 'f1-score': 0.8691247740581066, 'support': 36380.0}  |
-| No log        | 3.0   | 123  | 0.2463          | {'precision': 0.705, 'recall': 0.415929203539823, 'f1-score': 0.523191094619666, 'support': 339.0}                   | {'precision': 0.9416058394160584, 'recall': 0.80625, 'f1-score': 0.8686868686868686, 'support': 160.0} | {'precision': 0.8233695652173914, 'recall': 0.9659936238044633, 'f1-score': 0.888997555012225, 'support': 941.0}  | {'precision': 0.6939824614454189, 'recall': 0.4885057471264368, 'f1-score': 0.5733916302311056, 'support': 4698.0}    | {'precision': 0.900974858902001, 'recall': 0.8658777120315582, 'f1-score': 0.883077696756349, 'support': 2028.0}   | {'precision': 0.862554311241662, 'recall': 0.9484556893883319, 'f1-score': 0.9034677264277932, 'support': 14861.0}  | {'precision': 0.9997751461549993, 'recall': 0.9989515464689583, 'f1-score': 0.9993631766248362, 'support': 13353.0} | 0.8979   | {'precision': 0.8467517403396473, 'recall': 0.7842805031942245, 'f1-score': 0.8057393926226919, 'support': 36380.0} | {'precision': 0.8911590560437058, 'recall': 0.8978559648158329, 'f1-score': 0.8908329908492291, 'support': 36380.0} |
-| No log        | 4.0   | 164  | 0.2455          | {'precision': 0.7248908296943232, 'recall': 0.4896755162241888, 'f1-score': 0.5845070422535211, 'support': 339.0}    | {'precision': 0.9424460431654677, 'recall': 0.81875, 'f1-score': 0.8762541806020067, 'support': 160.0} | {'precision': 0.8409302325581396, 'recall': 0.9606801275239107, 'f1-score': 0.8968253968253969, 'support': 941.0} | {'precision': 0.7380442541042113, 'recall': 0.44018731375053216, 'f1-score': 0.5514666666666667, 'support': 4698.0}   | {'precision': 0.8909090909090909, 'recall': 0.8939842209072978, 'f1-score': 0.8924440068914595, 'support': 2028.0} | {'precision': 0.8539305737802696, 'recall': 0.9633941188345333, 'f1-score': 0.9053656685743194, 'support': 14861.0} | {'precision': 0.999850007499625, 'recall': 0.9984273197034375, 'f1-score': 0.9991381571551693, 'support': 13353.0}  | 0.8997   | {'precision': 0.8558572902444468, 'recall': 0.7950140881348429, 'f1-score': 0.8151430169955056, 'support': 36380.0} | {'precision': 0.8934359443718076, 'recall': 0.8996976360637713, 'f1-score': 0.8900236150023304, 'support': 36380.0} |
-| No log        | 5.0   | 205  | 0.2526          | {'precision': 0.7388059701492538, 'recall': 0.584070796460177, 'f1-score': 0.6523887973640857, 'support': 339.0}     | {'precision': 0.9315068493150684, 'recall': 0.85, 'f1-score': 0.888888888888889, 'support': 160.0}     | {'precision': 0.8685491723466408, 'recall': 0.9479277364505845, 'f1-score': 0.9065040650406505, 'support': 941.0} | {'precision': 0.7125307125307125, 'recall': 0.6172839506172839, 'f1-score': 0.6614963503649636, 'support': 4698.0}    | {'precision': 0.8987531172069826, 'recall': 0.888560157790927, 'f1-score': 0.8936275725266551, 'support': 2028.0}  | {'precision': 0.8955877616747182, 'recall': 0.9356032568467801, 'f1-score': 0.9151582965839531, 'support': 14861.0} | {'precision': 0.9991003823375065, 'recall': 0.9980528720137797, 'f1-score': 0.9985763524651581, 'support': 13353.0} | 0.9115   | {'precision': 0.8635477093658405, 'recall': 0.8316426814542189, 'f1-score': 0.8452343318906221, 'support': 36380.0} | {'precision': 0.9081159656876019, 'recall': 0.9114623419461243, 'f1-score': 0.9090309620899378, 'support': 36380.0} |
-| No log        | 6.0   | 246  | 0.2673          | {'precision': 0.7210031347962382, 'recall': 0.6784660766961652, 'f1-score': 0.6990881458966565, 'support': 339.0}    | {'precision': 0.9192546583850931, 'recall': 0.925, 'f1-score': 0.9221183800623053, 'support': 160.0}   | {'precision': 0.8932642487046633, 'recall': 0.9160467587672688, 'f1-score': 0.9045120671563485, 'support': 941.0} | {'precision': 0.7050987597611392, 'recall': 0.6534695615155385, 'f1-score': 0.6783031374281926, 'support': 4698.0}    | {'precision': 0.8852927177534508, 'recall': 0.9171597633136095, 'f1-score': 0.9009445386292081, 'support': 2028.0} | {'precision': 0.904881101376721, 'recall': 0.9243657896507638, 'f1-score': 0.9145196724585581, 'support': 14861.0}  | {'precision': 0.9996992255056771, 'recall': 0.99565640679997, 'f1-score': 0.9976737205463005, 'support': 13353.0}   | 0.9126   | {'precision': 0.8612134066118546, 'recall': 0.8585949081061879, 'f1-score': 0.8595942374539386, 'support': 36380.0} | {'precision': 0.9108414479595167, 'recall': 0.9126443100604728, 'f1-score': 0.9115468219984093, 'support': 36380.0} |
-| No log        | 7.0   | 287  | 0.3082          | {'precision': 0.7455357142857143, 'recall': 0.49262536873156343, 'f1-score': 0.5932504440497335, 'support': 339.0}   | {'precision': 0.9530201342281879, 'recall': 0.8875, 'f1-score': 0.919093851132686, 'support': 160.0}   | {'precision': 0.8419083255378859, 'recall': 0.9564293304994687, 'f1-score': 0.8955223880597015, 'support': 941.0} | {'precision': 0.7359364659166115, 'recall': 0.4733929331630481, 'f1-score': 0.5761658031088083, 'support': 4698.0}    | {'precision': 0.912444663059518, 'recall': 0.9146942800788954, 'f1-score': 0.9135680866781581, 'support': 2028.0}  | {'precision': 0.8574441164065795, 'recall': 0.9576071596796986, 'f1-score': 0.9047619047619048, 'support': 14861.0} | {'precision': 0.9997741984043353, 'recall': 0.9947577323447915, 'f1-score': 0.9972596568940275, 'support': 13353.0} | 0.9016   | {'precision': 0.8637233739769761, 'recall': 0.8110009720710665, 'f1-score': 0.8285174478121456, 'support': 36380.0} | {'precision': 0.8960358642584588, 'recall': 0.9016492578339748, 'f1-score': 0.8936908018647435, 'support': 36380.0} |
-| No log        | 8.0   | 328  | 0.3109          | {'precision': 0.714765100671141, 'recall': 0.6283185840707964, 'f1-score': 0.6687598116169545, 'support': 339.0}     | {'precision': 0.9577464788732394, 'recall': 0.85, 'f1-score': 0.9006622516556291, 'support': 160.0}    | {'precision': 0.8762475049900199, 'recall': 0.9330499468650372, 'f1-score': 0.9037570766855377, 'support': 941.0} | {'precision': 0.7084223013048636, 'recall': 0.6355896126011068, 'f1-score': 0.6700325367440816, 'support': 4698.0}    | {'precision': 0.951974386339381, 'recall': 0.8796844181459567, 'f1-score': 0.9144028703229115, 'support': 2028.0}  | {'precision': 0.8920465505047258, 'recall': 0.9335845501648611, 'f1-score': 0.9123429999342408, 'support': 14861.0} | {'precision': 0.9993983152827918, 'recall': 0.9951321800344491, 'f1-score': 0.9972606852039475, 'support': 13353.0} | 0.9115   | {'precision': 0.8715143768523089, 'recall': 0.8364798988403154, 'f1-score': 0.8524597474519003, 'support': 36380.0} | {'precision': 0.9093055312257066, 'recall': 0.9114623419461243, 'f1-score': 0.9097917557931217, 'support': 36380.0} |
-| No log        | 9.0   | 369  | 0.3515          | {'precision': 0.7183098591549296, 'recall': 0.6017699115044248, 'f1-score': 0.6548956661316213, 'support': 339.0}    | {'precision': 0.9517241379310345, 'recall': 0.8625, 'f1-score': 0.9049180327868853, 'support': 160.0}  | {'precision': 0.8705533596837944, 'recall': 0.9362380446333688, 'f1-score': 0.9022017409114182, 'support': 941.0} | {'precision': 0.7166541070082894, 'recall': 0.60727969348659, 'f1-score': 0.6574490148634635, 'support': 4698.0}      | {'precision': 0.941908713692946, 'recall': 0.8954635108481263, 'f1-score': 0.9180990899898889, 'support': 2028.0}  | {'precision': 0.8871285868804479, 'recall': 0.938227575533275, 'f1-score': 0.9119628491072013, 'support': 14861.0}  | {'precision': 0.9994741981521821, 'recall': 0.9964801917172171, 'f1-score': 0.9979749493737343, 'support': 13353.0} | 0.9110   | {'precision': 0.8693932803576605, 'recall': 0.8339941325318574, 'f1-score': 0.8496430490234591, 'support': 36380.0} | {'precision': 0.9076856069113689, 'recall': 0.9109675645959319, 'f1-score': 0.908328976914783, 'support': 36380.0}  |
-| No log        | 10.0  | 410  | 0.3666          | {'precision': 0.7186440677966102, 'recall': 0.6253687315634219, 'f1-score': 0.6687697160883281, 'support': 339.0}    | {'precision': 0.9403973509933775, 'recall': 0.8875, 'f1-score': 0.9131832797427653, 'support': 160.0}  | {'precision': 0.8801611278952669, 'recall': 0.9287991498405951, 'f1-score': 0.9038262668045501, 'support': 941.0} | {'precision': 0.7035942885278188, 'recall': 0.6083439761600681, 'f1-score': 0.6525114155251142, 'support': 4698.0}    | {'precision': 0.9091796875, 'recall': 0.9181459566074951, 'f1-score': 0.913640824337586, 'support': 2028.0}        | {'precision': 0.8907005220081201, 'recall': 0.9300181683601373, 'f1-score': 0.909934821252222, 'support': 14861.0}  | {'precision': 0.9993991287366681, 'recall': 0.9964801917172171, 'f1-score': 0.9979375257809279, 'support': 13353.0} | 0.9092   | {'precision': 0.8631537390654088, 'recall': 0.8420937391784192, 'f1-score': 0.8514005499330703, 'support': 36380.0} | {'precision': 0.9058079970815979, 'recall': 0.9091533809785597, 'f1-score': 0.9068083056033942, 'support': 36380.0} |
-| No log        | 11.0  | 451  | 0.3872          | {'precision': 0.7272727272727273, 'recall': 0.6607669616519174, 'f1-score': 0.6924265842349304, 'support': 339.0}    | {'precision': 0.9316770186335404, 'recall': 0.9375, 'f1-score': 0.9345794392523364, 'support': 160.0}  | {'precision': 0.8900308324768756, 'recall': 0.9202975557917109, 'f1-score': 0.9049111807732496, 'support': 941.0} | {'precision': 0.7143188674866559, 'recall': 0.6551724137931034, 'f1-score': 0.6834684134562007, 'support': 4698.0}    | {'precision': 0.9243452958292919, 'recall': 0.9398422090729783, 'f1-score': 0.9320293398533007, 'support': 2028.0} | {'precision': 0.9015017378188733, 'recall': 0.9250386918780701, 'f1-score': 0.9131185652607107, 'support': 14861.0} | {'precision': 0.9993242228562847, 'recall': 0.9967048603310118, 'f1-score': 0.9980128229162761, 'support': 13353.0} | 0.9148   | {'precision': 0.8697815289106071, 'recall': 0.8621889560741132, 'f1-score': 0.8655066208210008, 'support': 36380.0} | {'precision': 0.9127204168171501, 'recall': 0.9147883452446399, 'f1-score': 0.9135018437004899, 'support': 36380.0} |
-| No log        | 12.0  | 492  | 0.4655          | {'precision': 0.7546468401486989, 'recall': 0.5988200589970502, 'f1-score': 0.6677631578947368, 'support': 339.0}    | {'precision': 0.9325153374233128, 'recall': 0.95, 'f1-score': 0.9411764705882352, 'support': 160.0}    | {'precision': 0.875, 'recall': 0.9373007438894793, 'f1-score': 0.9050795279630579, 'support': 941.0}              | {'precision': 0.7343623070674249, 'recall': 0.5772669220945083, 'f1-score': 0.6464068644976761, 'support': 4698.0}    | {'precision': 0.9018867924528302, 'recall': 0.9428007889546351, 'f1-score': 0.9218900675024109, 'support': 2028.0} | {'precision': 0.8842823737597169, 'recall': 0.9415247964470762, 'f1-score': 0.9120062573328118, 'support': 14861.0} | {'precision': 0.9992483463619964, 'recall': 0.9955815172620385, 'f1-score': 0.997411561691113, 'support': 13353.0}  | 0.9111   | {'precision': 0.8688488567448543, 'recall': 0.8490421182349696, 'f1-score': 0.8559619867814344, 'support': 36380.0} | {'precision': 0.9068649475511307, 'recall': 0.9111324903793293, 'f1-score': 0.907279105591616, 'support': 36380.0}  |
-| 0.1948        | 13.0  | 533  | 0.4358          | {'precision': 0.7190332326283988, 'recall': 0.7020648967551623, 'f1-score': 0.7104477611940299, 'support': 339.0}    | {'precision': 0.9490445859872612, 'recall': 0.93125, 'f1-score': 0.9400630914826499, 'support': 160.0} | {'precision': 0.9012605042016807, 'recall': 0.9117959617428267, 'f1-score': 0.9064976228209191, 'support': 941.0} | {'precision': 0.7068927548998019, 'recall': 0.6832694763729247, 'f1-score': 0.6948803983115057, 'support': 4698.0}    | {'precision': 0.9245098039215687, 'recall': 0.9299802761341223, 'f1-score': 0.927236971484759, 'support': 2028.0}  | {'precision': 0.9093388319808434, 'recall': 0.9199246349505417, 'f1-score': 0.9146011038635222, 'support': 14861.0} | {'precision': 0.9993996247654784, 'recall': 0.9973039766344641, 'f1-score': 0.9983507009520954, 'support': 13353.0} | 0.9161   | {'precision': 0.8727827626264332, 'recall': 0.8679413175128632, 'f1-score': 0.8702968071584973, 'support': 36380.0} | {'precision': 0.9152897512508446, 'recall': 0.9161352391423859, 'f1-score': 0.9156711036977506, 'support': 36380.0} |
-| 0.1948        | 14.0  | 574  | 0.4497          | {'precision': 0.7331288343558282, 'recall': 0.7050147492625368, 'f1-score': 0.718796992481203, 'support': 339.0}     | {'precision': 0.9612903225806452, 'recall': 0.93125, 'f1-score': 0.9460317460317461, 'support': 160.0} | {'precision': 0.9009384775808134, 'recall': 0.9181721572794899, 'f1-score': 0.9094736842105262, 'support': 941.0} | {'precision': 0.7201365187713311, 'recall': 0.6736909323116219, 'f1-score': 0.6961398878258, 'support': 4698.0}       | {'precision': 0.9266732283464567, 'recall': 0.9285009861932939, 'f1-score': 0.9275862068965517, 'support': 2028.0} | {'precision': 0.9067807768268598, 'recall': 0.9268555278917974, 'f1-score': 0.9167082626202122, 'support': 14861.0} | {'precision': 0.9993244764692637, 'recall': 0.9970793080206695, 'f1-score': 0.9982006297795771, 'support': 13353.0} | 0.9178   | {'precision': 0.8783246621330283, 'recall': 0.8686519515656299, 'f1-score': 0.8732767728350882, 'support': 36380.0} | {'precision': 0.9162249523049875, 'recall': 0.9177570093457944, 'f1-score': 0.9168399262643154, 'support': 36380.0} |
-| 0.1948        | 15.0  | 615  | 0.4661          | {'precision': 0.7324414715719063, 'recall': 0.6460176991150443, 'f1-score': 0.6865203761755485, 'support': 339.0}    | {'precision': 0.954248366013072, 'recall': 0.9125, 'f1-score': 0.9329073482428115, 'support': 160.0}   | {'precision': 0.8846153846153846, 'recall': 0.9287991498405951, 'f1-score': 0.9061689994815967, 'support': 941.0} | {'precision': 0.7287968441814595, 'recall': 0.6292039165602384, 'f1-score': 0.6753484121544437, 'support': 4698.0}    | {'precision': 0.9236453201970444, 'recall': 0.9245562130177515, 'f1-score': 0.9241005421389847, 'support': 2028.0} | {'precision': 0.8956415373720467, 'recall': 0.9361415786286252, 'f1-score': 0.9154438375995262, 'support': 14861.0} | {'precision': 0.9993243750469184, 'recall': 0.9969295289448065, 'f1-score': 0.9981255154832421, 'support': 13353.0} | 0.9152   | {'precision': 0.8741018998568331, 'recall': 0.853449726586723, 'f1-score': 0.8626592901823076, 'support': 36380.0}  | {'precision': 0.9121645966069168, 'recall': 0.9151731720725673, 'f1-score': 0.9129726286511344, 'support': 36380.0} |
-| 0.1948        | 16.0  | 656  | 0.4671          | {'precision': 0.7346278317152104, 'recall': 0.6696165191740413, 'f1-score': 0.7006172839506173, 'support': 339.0}    | {'precision': 0.9490445859872612, 'recall': 0.93125, 'f1-score': 0.9400630914826499, 'support': 160.0} | {'precision': 0.8921971252566735, 'recall': 0.9234856535600425, 'f1-score': 0.9075718015665796, 'support': 941.0} | {'precision': 0.7273820981713186, 'recall': 0.6434653043848446, 'f1-score': 0.6828552066862436, 'support': 4698.0}    | {'precision': 0.9140926640926641, 'recall': 0.9339250493096647, 'f1-score': 0.9239024390243903, 'support': 2028.0} | {'precision': 0.9001753588361369, 'recall': 0.9326424870466321, 'f1-score': 0.9161213563355145, 'support': 14861.0} | {'precision': 0.999324070597071, 'recall': 0.9964801917172171, 'f1-score': 0.9979001049947502, 'support': 13353.0}  | 0.9161   | {'precision': 0.8738348192366193, 'recall': 0.8615521721703489, 'f1-score': 0.8670044691486779, 'support': 36380.0} | {'precision': 0.9134949094533051, 'recall': 0.9161077515118197, 'f1-score': 0.914324131528891, 'support': 36380.0}  |
 ### Framework versions

       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: 0.8987712506312069
 ---
 <!-- 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: 0.4995
+- B-claim: {'precision': 0.6529850746268657, 'recall': 0.6457564575645757, 'f1-score': 0.6493506493506495, 'support': 271.0}
+- B-majorclaim: {'precision': 0.8591549295774648, 'recall': 0.8776978417266187, 'f1-score': 0.8683274021352312, 'support': 139.0}
+- B-premise: {'precision': 0.8767772511848341, 'recall': 0.8767772511848341, 'f1-score': 0.876777251184834, 'support': 633.0}
+- I-claim: {'precision': 0.6591271953166578, 'recall': 0.6190952261934516, 'f1-score': 0.6384843407655625, 'support': 4001.0}
+- I-majorclaim: {'precision': 0.8964467005076142, 'recall': 0.877297565822156, 'f1-score': 0.8867687672608586, 'support': 2013.0}
+- I-premise: {'precision': 0.885505376344086, 'recall': 0.9080804516584333, 'f1-score': 0.8966508427333304, 'support': 11336.0}
+- O: {'precision': 1.0, 'recall': 0.9997347949080623, 'f1-score': 0.9998673798682641, 'support': 11312.0}
+- Accuracy: 0.8988
+- Macro avg: {'precision': 0.8328566467939318, 'recall': 0.829205655579733, 'f1-score': 0.8308895190426757, 'support': 29705.0}
+- Weighted avg: {'precision': 0.896925957019205, 'recall': 0.8987712506312069, 'f1-score': 0.8977022947337076, 'support': 29705.0}
 ## 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   | 0.4083          | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 271.0}                                                 | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 139.0}                                               | {'precision': 0.643595041322314, 'recall': 0.9842022116903634, 'f1-score': 0.778263585259213, 'support': 633.0}   | {'precision': 0.4563708012760368, 'recall': 0.6078480379905024, 'f1-score': 0.5213290460878884, 'support': 4001.0} | {'precision': 0.7011784511784511, 'recall': 0.4138102334823646, 'f1-score': 0.520462355513902, 'support': 2013.0}  | {'precision': 0.8778050331607159, 'recall': 0.8523288637967537, 'f1-score': 0.8648793805666204, 'support': 11336.0} | {'precision': 0.9991081780076697, 'recall': 0.9903642149929278, 'f1-score': 0.9947169811320755, 'support': 11312.0} | 0.8333   | {'precision': 0.5254367864207411, 'recall': 0.5497933659932731, 'f1-score': 0.5256644783656713, 'support': 29705.0} | {'precision': 0.8381591322948091, 'recall': 0.8332940582393537, 'f1-score': 0.830926787853407, 'support': 29705.0}  |
+| No log        | 2.0   | 82   | 0.2959          | {'precision': 0.38823529411764707, 'recall': 0.24354243542435425, 'f1-score': 0.29931972789115646, 'support': 271.0} | {'precision': 0.8620689655172413, 'recall': 0.17985611510791366, 'f1-score': 0.2976190476190476, 'support': 139.0} | {'precision': 0.7422802850356295, 'recall': 0.9873617693522907, 'f1-score': 0.8474576271186441, 'support': 633.0} | {'precision': 0.5749261291684254, 'recall': 0.340414896275931, 'f1-score': 0.42762951334379906, 'support': 4001.0} | {'precision': 0.7699071812408402, 'recall': 0.7829110779930452, 'f1-score': 0.7763546798029557, 'support': 2013.0} | {'precision': 0.8290439755777108, 'recall': 0.9462773465067043, 'f1-score': 0.8837899073120494, 'support': 11336.0} | {'precision': 0.9999115748518879, 'recall': 0.9996463932107497, 'f1-score': 0.9997789664471067, 'support': 11312.0} | 0.8648   | {'precision': 0.7380533436441974, 'recall': 0.6400014334101413, 'f1-score': 0.6474213527906798, 'support': 29705.0} | {'precision': 0.850161508562683, 'recall': 0.8648039050664871, 'f1-score': 0.8503893311871605, 'support': 29705.0}  |
+| No log        | 3.0   | 123  | 0.2633          | {'precision': 0.61328125, 'recall': 0.5793357933579336, 'f1-score': 0.5958254269449716, 'support': 271.0}            | {'precision': 0.7655172413793103, 'recall': 0.7985611510791367, 'f1-score': 0.7816901408450705, 'support': 139.0}  | {'precision': 0.8738317757009346, 'recall': 0.8862559241706162, 'f1-score': 0.88, 'support': 633.0}               | {'precision': 0.6150895140664961, 'recall': 0.6010997250687328, 'f1-score': 0.6080141575022121, 'support': 4001.0} | {'precision': 0.7346859149434257, 'recall': 0.9354197714853453, 'f1-score': 0.8229895104895104, 'support': 2013.0} | {'precision': 0.9111703104905383, 'recall': 0.875, 'f1-score': 0.8927189271892718, 'support': 11336.0}              | {'precision': 1.0, 'recall': 0.9992043847241867, 'f1-score': 0.9996020340481981, 'support': 11312.0}                | 0.8867   | {'precision': 0.7876537152258151, 'recall': 0.8106966785551358, 'f1-score': 0.7972628852884621, 'support': 29705.0} | {'precision': 0.8889636142603039, 'recall': 0.8866857431408853, 'f1-score': 0.8868495578802252, 'support': 29705.0} |
+| No log        | 4.0   | 164  | 0.2767          | {'precision': 0.6180555555555556, 'recall': 0.6568265682656826, 'f1-score': 0.6368515205724509, 'support': 271.0}    | {'precision': 0.7368421052631579, 'recall': 0.9064748201438849, 'f1-score': 0.8129032258064516, 'support': 139.0}  | {'precision': 0.9126712328767124, 'recall': 0.8420221169036335, 'f1-score': 0.8759244042728019, 'support': 633.0} | {'precision': 0.6039107545750815, 'recall': 0.6020994751312172, 'f1-score': 0.6030037546933668, 'support': 4001.0} | {'precision': 0.7743306417339566, 'recall': 0.905116741182315, 'f1-score': 0.8346312414109024, 'support': 2013.0}  | {'precision': 0.9007175946952494, 'recall': 0.8747353563867325, 'f1-score': 0.8875363616021481, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9999115983026874, 'f1-score': 0.9999557971975424, 'support': 11312.0}                | 0.8852   | {'precision': 0.7923611263856734, 'recall': 0.8267409537594504, 'f1-score': 0.8072580436508092, 'support': 29705.0} | {'precision': 0.8868925824921324, 'recall': 0.8852045110250799, 'f1-score': 0.8855540596827394, 'support': 29705.0} |
+| No log        | 5.0   | 205  | 0.2875          | {'precision': 0.6273885350318471, 'recall': 0.7269372693726938, 'f1-score': 0.6735042735042734, 'support': 271.0}    | {'precision': 0.7865853658536586, 'recall': 0.9280575539568345, 'f1-score': 0.8514851485148515, 'support': 139.0}  | {'precision': 0.9257950530035336, 'recall': 0.8278041074249605, 'f1-score': 0.8740617180984154, 'support': 633.0} | {'precision': 0.5824691841126981, 'recall': 0.744063984003999, 'f1-score': 0.6534240561896401, 'support': 4001.0}  | {'precision': 0.8339432753888381, 'recall': 0.9056135121708893, 'f1-score': 0.8683019766611098, 'support': 2013.0} | {'precision': 0.9326903957049115, 'recall': 0.8275405786873676, 'f1-score': 0.8769748527624568, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9994695898161244, 'f1-score': 0.9997347245556637, 'support': 11312.0}                | 0.8866   | {'precision': 0.8126959727279266, 'recall': 0.8513552279189812, 'f1-score': 0.8282123928980587, 'support': 29705.0} | {'precision': 0.90084333519953, 'recall': 0.8866184144083488, 'f1-score': 0.8909875382676978, 'support': 29705.0}   |
+| No log        | 6.0   | 246  | 0.2945          | {'precision': 0.6326530612244898, 'recall': 0.6863468634686347, 'f1-score': 0.6584070796460177, 'support': 271.0}    | {'precision': 0.8818897637795275, 'recall': 0.8057553956834532, 'f1-score': 0.8421052631578947, 'support': 139.0}  | {'precision': 0.8858520900321544, 'recall': 0.8704581358609794, 'f1-score': 0.8780876494023905, 'support': 633.0} | {'precision': 0.6304404482668752, 'recall': 0.6045988502874281, 'f1-score': 0.6172492982903802, 'support': 4001.0} | {'precision': 0.8976501305483029, 'recall': 0.8539493293591655, 'f1-score': 0.8752545824847251, 'support': 2013.0} | {'precision': 0.8802859357505813, 'recall': 0.9016407904022583, 'f1-score': 0.8908354033206956, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9988507779349364, 'f1-score': 0.9994250585997965, 'support': 11312.0}                | 0.8923   | {'precision': 0.829824489943133, 'recall': 0.8173714489995507, 'f1-score': 0.8230520478431285, 'support': 29705.0}  | {'precision': 0.8912660947222903, 'recall': 0.8923413566739606, 'f1-score': 0.8916619674856285, 'support': 29705.0} |
+| No log        | 7.0   | 287  | 0.3037          | {'precision': 0.6442953020134228, 'recall': 0.7084870848708487, 'f1-score': 0.6748681898066783, 'support': 271.0}    | {'precision': 0.8705035971223022, 'recall': 0.8705035971223022, 'f1-score': 0.8705035971223022, 'support': 139.0}  | {'precision': 0.8991735537190083, 'recall': 0.8593996840442338, 'f1-score': 0.8788368336025849, 'support': 633.0} | {'precision': 0.6310387984981226, 'recall': 0.6300924768807799, 'f1-score': 0.6305652826413206, 'support': 4001.0} | {'precision': 0.891640866873065, 'recall': 0.8584202682563339, 'f1-score': 0.8747152619589977, 'support': 2013.0}  | {'precision': 0.8886845331932037, 'recall': 0.8951129146083274, 'f1-score': 0.8918871407225103, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.8943   | {'precision': 0.832190950202732, 'recall': 0.8317165751118323, 'f1-score': 0.8316251865506278, 'support': 29705.0}  | {'precision': 0.8944813348740749, 'recall': 0.8942938899175223, 'f1-score': 0.894338297946804, 'support': 29705.0}  |
+| No log        | 8.0   | 328  | 0.3549          | {'precision': 0.6498054474708171, 'recall': 0.6162361623616236, 'f1-score': 0.6325757575757576, 'support': 271.0}    | {'precision': 0.8796992481203008, 'recall': 0.841726618705036, 'f1-score': 0.8602941176470588, 'support': 139.0}   | {'precision': 0.863914373088685, 'recall': 0.8925750394944708, 'f1-score': 0.8780108780108781, 'support': 633.0}  | {'precision': 0.644374282433984, 'recall': 0.5611097225693576, 'f1-score': 0.5998663994655979, 'support': 4001.0}  | {'precision': 0.9037546271813856, 'recall': 0.8489816194734228, 'f1-score': 0.8755122950819673, 'support': 2013.0} | {'precision': 0.8685594989561587, 'recall': 0.9175194071983063, 'f1-score': 0.8923684097636309, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9999115983026874, 'f1-score': 0.9999557971975424, 'support': 11312.0}                | 0.8926   | {'precision': 0.8300153538930474, 'recall': 0.811151452586415, 'f1-score': 0.8197976649632047, 'support': 29705.0}  | {'precision': 0.8887602531095763, 'recall': 0.892610671604107, 'f1-score': 0.8899730612246367, 'support': 29705.0}  |
+| No log        | 9.0   | 369  | 0.3716          | {'precision': 0.6468531468531469, 'recall': 0.6826568265682657, 'f1-score': 0.6642728904847396, 'support': 271.0}    | {'precision': 0.8333333333333334, 'recall': 0.8633093525179856, 'f1-score': 0.8480565371024734, 'support': 139.0}  | {'precision': 0.8941368078175895, 'recall': 0.8672985781990521, 'f1-score': 0.8805132317562149, 'support': 633.0} | {'precision': 0.6205917159763313, 'recall': 0.6553361659585104, 'f1-score': 0.637490882567469, 'support': 4001.0}  | {'precision': 0.8750640040962622, 'recall': 0.8489816194734228, 'f1-score': 0.8618255168935955, 'support': 2013.0} | {'precision': 0.8960551033187226, 'recall': 0.8836450247000706, 'f1-score': 0.8898067954696869, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9992927864214993, 'f1-score': 0.9996462681287585, 'support': 11312.0}                | 0.8923   | {'precision': 0.8237191587707694, 'recall': 0.8286457648341152, 'f1-score': 0.8259445889147053, 'support': 29705.0} | {'precision': 0.8945056752252882, 'recall': 0.8923076923076924, 'f1-score': 0.8933030430182268, 'support': 29705.0} |
+| No log        | 10.0  | 410  | 0.4143          | {'precision': 0.6746987951807228, 'recall': 0.6199261992619927, 'f1-score': 0.6461538461538461, 'support': 271.0}    | {'precision': 0.8157894736842105, 'recall': 0.8920863309352518, 'f1-score': 0.852233676975945, 'support': 139.0}   | {'precision': 0.8785046728971962, 'recall': 0.8909952606635071, 'f1-score': 0.8847058823529412, 'support': 633.0} | {'precision': 0.6611758023288838, 'recall': 0.5818545363659086, 'f1-score': 0.6189843126827972, 'support': 4001.0} | {'precision': 0.8256503879507074, 'recall': 0.8986587183308494, 'f1-score': 0.8606089438629877, 'support': 2013.0} | {'precision': 0.8856627437505369, 'recall': 0.9094918842625265, 'f1-score': 0.8974191582887234, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9997347949080623, 'f1-score': 0.9998673798682641, 'support': 11312.0}                | 0.8959   | {'precision': 0.8202116965417511, 'recall': 0.8275353892468712, 'f1-score': 0.822853314312215, 'support': 29705.0}  | {'precision': 0.8924963153509083, 'recall': 0.8958761151321326, 'f1-score': 0.8936607445011815, 'support': 29705.0} |
+| No log        | 11.0  | 451  | 0.4242          | {'precision': 0.6442953020134228, 'recall': 0.7084870848708487, 'f1-score': 0.6748681898066783, 'support': 271.0}    | {'precision': 0.8661971830985915, 'recall': 0.8848920863309353, 'f1-score': 0.8754448398576513, 'support': 139.0}  | {'precision': 0.8988391376451078, 'recall': 0.8562401263823065, 'f1-score': 0.8770226537216829, 'support': 633.0} | {'precision': 0.6332931242460796, 'recall': 0.6560859785053736, 'f1-score': 0.6444880923152466, 'support': 4001.0} | {'precision': 0.8797595190380761, 'recall': 0.8723298559364133, 'f1-score': 0.8760289348964829, 'support': 2013.0} | {'precision': 0.8979136947218259, 'recall': 0.8884086097388849, 'f1-score': 0.8931358637814828, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9993811881188119, 'f1-score': 0.9996904982977407, 'support': 11312.0}                | 0.8959   | {'precision': 0.8314711372518719, 'recall': 0.8379749899833678, 'f1-score': 0.8343827246681379, 'support': 29705.0} | {'precision': 0.8974745650471141, 'recall': 0.8959434438646693, 'f1-score': 0.8966457372110589, 'support': 29705.0} |
+| No log        | 12.0  | 492  | 0.4911          | {'precision': 0.6926605504587156, 'recall': 0.5571955719557196, 'f1-score': 0.6175869120654396, 'support': 271.0}    | {'precision': 0.8759124087591241, 'recall': 0.8633093525179856, 'f1-score': 0.8695652173913043, 'support': 139.0}  | {'precision': 0.8461538461538461, 'recall': 0.9210110584518167, 'f1-score': 0.8819969742813918, 'support': 633.0} | {'precision': 0.6817567567567567, 'recall': 0.5043739065233691, 'f1-score': 0.5798017526217497, 'support': 4001.0} | {'precision': 0.9035639412997903, 'recall': 0.8564331843020367, 'f1-score': 0.8793675082887019, 'support': 2013.0} | {'precision': 0.8544101168560909, 'recall': 0.9416901905434015, 'f1-score': 0.8959295006294586, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9988507779349364, 'f1-score': 0.9994250585997965, 'support': 11312.0}                | 0.8945   | {'precision': 0.8363510886120462, 'recall': 0.8061234346041807, 'f1-score': 0.8176675605539775, 'support': 29705.0} | {'precision': 0.888377522333214, 'recall': 0.8944622117488639, 'f1-score': 0.8886802353660483, 'support': 29705.0}  |
+| 0.1948        | 13.0  | 533  | 0.4856          | {'precision': 0.6967213114754098, 'recall': 0.6273062730627307, 'f1-score': 0.6601941747572815, 'support': 271.0}    | {'precision': 0.8689655172413793, 'recall': 0.9064748201438849, 'f1-score': 0.8873239436619718, 'support': 139.0}  | {'precision': 0.8715596330275229, 'recall': 0.9004739336492891, 'f1-score': 0.8857808857808857, 'support': 633.0} | {'precision': 0.6689675007190107, 'recall': 0.5813546613346663, 'f1-score': 0.622091468307034, 'support': 4001.0}  | {'precision': 0.8964467005076142, 'recall': 0.877297565822156, 'f1-score': 0.8867687672608586, 'support': 2013.0}  | {'precision': 0.8748636172891313, 'recall': 0.9195483415666902, 'f1-score': 0.8966496064685389, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.998939179632249, 'f1-score': 0.9994693083318592, 'support': 11312.0}                 | 0.8982   | {'precision': 0.8396463257514384, 'recall': 0.8301992536016665, 'f1-score': 0.8340397363669184, 'support': 29705.0} | {'precision': 0.8945239883555292, 'recall': 0.898232620770914, 'f1-score': 0.8957219390068148, 'support': 29705.0}  |
+| 0.1948        | 14.0  | 574  | 0.4750          | {'precision': 0.6655052264808362, 'recall': 0.7047970479704797, 'f1-score': 0.6845878136200716, 'support': 271.0}    | {'precision': 0.8661971830985915, 'recall': 0.8848920863309353, 'f1-score': 0.8754448398576513, 'support': 139.0}  | {'precision': 0.8973941368078175, 'recall': 0.8704581358609794, 'f1-score': 0.8837209302325582, 'support': 633.0} | {'precision': 0.6448780487804878, 'recall': 0.6608347913021745, 'f1-score': 0.6527589186520183, 'support': 4001.0} | {'precision': 0.8922610015174507, 'recall': 0.8763040238450075, 'f1-score': 0.8842105263157896, 'support': 2013.0} | {'precision': 0.8977292886287032, 'recall': 0.8928193366266761, 'f1-score': 0.8952675807164971, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9999115983026874, 'f1-score': 0.9999557971975424, 'support': 11312.0}                | 0.8990   | {'precision': 0.8377092693305553, 'recall': 0.8414310028912771, 'f1-score': 0.839420915227447, 'support': 29705.0}  | {'precision': 0.899974465529261, 'recall': 0.899006901195085, 'f1-score': 0.8994601237155254, 'support': 29705.0}   |
+| 0.1948        | 15.0  | 615  | 0.5226          | {'precision': 0.6761133603238867, 'recall': 0.6162361623616236, 'f1-score': 0.6447876447876448, 'support': 271.0}    | {'precision': 0.8695652173913043, 'recall': 0.8633093525179856, 'f1-score': 0.8664259927797834, 'support': 139.0}  | {'precision': 0.8677811550151976, 'recall': 0.9020537124802528, 'f1-score': 0.8845855925639039, 'support': 633.0} | {'precision': 0.6685476685476686, 'recall': 0.5626093476630842, 'f1-score': 0.6110206297502714, 'support': 4001.0} | {'precision': 0.8988186954288649, 'recall': 0.8693492300049677, 'f1-score': 0.8838383838383838, 'support': 2013.0} | {'precision': 0.8697276652274992, 'recall': 0.9240472829922372, 'f1-score': 0.8960650128314799, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9992927864214993, 'f1-score': 0.9996462681287585, 'support': 11312.0}                | 0.8968   | {'precision': 0.8357933945620601, 'recall': 0.8195568392059501, 'f1-score': 0.8266242178114608, 'support': 29705.0} | {'precision': 0.8924024852976349, 'recall': 0.8967513886551086, 'f1-score': 0.8936126955615038, 'support': 29705.0} |
+| 0.1948        | 16.0  | 656  | 0.4995          | {'precision': 0.6529850746268657, 'recall': 0.6457564575645757, 'f1-score': 0.6493506493506495, 'support': 271.0}    | {'precision': 0.8591549295774648, 'recall': 0.8776978417266187, 'f1-score': 0.8683274021352312, 'support': 139.0}  | {'precision': 0.8767772511848341, 'recall': 0.8767772511848341, 'f1-score': 0.876777251184834, 'support': 633.0}  | {'precision': 0.6591271953166578, 'recall': 0.6190952261934516, 'f1-score': 0.6384843407655625, 'support': 4001.0} | {'precision': 0.8964467005076142, 'recall': 0.877297565822156, 'f1-score': 0.8867687672608586, 'support': 2013.0}  | {'precision': 0.885505376344086, 'recall': 0.9080804516584333, 'f1-score': 0.8966508427333304, 'support': 11336.0}  | {'precision': 1.0, 'recall': 0.9997347949080623, 'f1-score': 0.9998673798682641, 'support': 11312.0}                | 0.8988   | {'precision': 0.8328566467939318, 'recall': 0.829205655579733, 'f1-score': 0.8308895190426757, 'support': 29705.0}  | {'precision': 0.896925957019205, 'recall': 0.8987712506312069, 'f1-score': 0.8977022947337076, 'support': 29705.0}  |
 ### 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: sep_tok_full_labels
-      split: train[60%:80%]
       args: sep_tok_full_labels
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9161077515118197
 ---
 <!-- 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: 0.4671
-- B-claim: {'precision': 0.7346278317152104, 'recall': 0.6696165191740413, 'f1-score': 0.7006172839506173, 'support': 339.0}
-- B-majorclaim: {'precision': 0.9490445859872612, 'recall': 0.93125, 'f1-score': 0.9400630914826499, 'support': 160.0}
-- B-premise: {'precision': 0.8921971252566735, 'recall': 0.9234856535600425, 'f1-score': 0.9075718015665796, 'support': 941.0}
-- I-claim: {'precision': 0.7273820981713186, 'recall': 0.6434653043848446, 'f1-score': 0.6828552066862436, 'support': 4698.0}
-- I-majorclaim: {'precision': 0.9140926640926641, 'recall': 0.9339250493096647, 'f1-score': 0.9239024390243903, 'support': 2028.0}
-- I-premise: {'precision': 0.9001753588361369, 'recall': 0.9326424870466321, 'f1-score': 0.9161213563355145, 'support': 14861.0}
-- O: {'precision': 0.999324070597071, 'recall': 0.9964801917172171, 'f1-score': 0.9979001049947502, 'support': 13353.0}
-- Accuracy: 0.9161
-- Macro avg: {'precision': 0.8738348192366193, 'recall': 0.8615521721703489, 'f1-score': 0.8670044691486779, 'support': 36380.0}
-- Weighted avg: {'precision': 0.9134949094533051, 'recall': 0.9161077515118197, 'f1-score': 0.914324131528891, 'support': 36380.0}
 ## 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   | 0.4724          | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 339.0}                                                 | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 160.0}                                   | {'precision': 0.8, 'recall': 0.7863974495217854, 'f1-score': 0.7931404072883173, 'support': 941.0}                | {'precision': 0.46561443066516345, 'recall': 0.35163899531715626, 'f1-score': 0.40067911714770804, 'support': 4698.0} | {'precision': 0.4144271570014144, 'recall': 0.8668639053254438, 'f1-score': 0.5607655502392344, 'support': 2028.0} | {'precision': 0.8844441252513645, 'recall': 0.8286790929277976, 'f1-score': 0.8556539864512767, 'support': 14861.0} | {'precision': 0.9700167382286587, 'recall': 0.9982026510896428, 'f1-score': 0.9839078762825717, 'support': 13353.0} | 0.8190   | {'precision': 0.5049289215923716, 'recall': 0.5473974420259752, 'f1-score': 0.5134495624870155, 'support': 36380.0} | {'precision': 0.8212499318469384, 'recall': 0.8189664650907091, 'f1-score': 0.8141826255128369, 'support': 36380.0} |
-| No log        | 2.0   | 82   | 0.2806          | {'precision': 0.39147286821705424, 'recall': 0.29793510324483774, 'f1-score': 0.33835845896147404, 'support': 339.0} | {'precision': 1.0, 'recall': 0.0125, 'f1-score': 0.02469135802469136, 'support': 160.0}                | {'precision': 0.788975021533161, 'recall': 0.973432518597237, 'f1-score': 0.8715509039010466, 'support': 941.0}   | {'precision': 0.6001651073197578, 'recall': 0.46424010217113665, 'f1-score': 0.5235237638022083, 'support': 4698.0}   | {'precision': 0.890087660148348, 'recall': 0.650887573964497, 'f1-score': 0.7519225291939617, 'support': 2028.0}   | {'precision': 0.8537944400702562, 'recall': 0.9485902698337931, 'f1-score': 0.8986994772408516, 'support': 14861.0} | {'precision': 0.9998499737454054, 'recall': 0.9982026510896428, 'f1-score': 0.9990256333383302, 'support': 13353.0} | 0.8781   | {'precision': 0.7891921530048547, 'recall': 0.6208268884144491, 'f1-score': 0.6296817320660805, 'support': 36380.0} | {'precision': 0.871331614069924, 'recall': 0.8781198460692689, 'f1-score': 0.8691247740581066, 'support': 36380.0}  |
-| No log        | 3.0   | 123  | 0.2463          | {'precision': 0.705, 'recall': 0.415929203539823, 'f1-score': 0.523191094619666, 'support': 339.0}                   | {'precision': 0.9416058394160584, 'recall': 0.80625, 'f1-score': 0.8686868686868686, 'support': 160.0} | {'precision': 0.8233695652173914, 'recall': 0.9659936238044633, 'f1-score': 0.888997555012225, 'support': 941.0}  | {'precision': 0.6939824614454189, 'recall': 0.4885057471264368, 'f1-score': 0.5733916302311056, 'support': 4698.0}    | {'precision': 0.900974858902001, 'recall': 0.8658777120315582, 'f1-score': 0.883077696756349, 'support': 2028.0}   | {'precision': 0.862554311241662, 'recall': 0.9484556893883319, 'f1-score': 0.9034677264277932, 'support': 14861.0}  | {'precision': 0.9997751461549993, 'recall': 0.9989515464689583, 'f1-score': 0.9993631766248362, 'support': 13353.0} | 0.8979   | {'precision': 0.8467517403396473, 'recall': 0.7842805031942245, 'f1-score': 0.8057393926226919, 'support': 36380.0} | {'precision': 0.8911590560437058, 'recall': 0.8978559648158329, 'f1-score': 0.8908329908492291, 'support': 36380.0} |
-| No log        | 4.0   | 164  | 0.2455          | {'precision': 0.7248908296943232, 'recall': 0.4896755162241888, 'f1-score': 0.5845070422535211, 'support': 339.0}    | {'precision': 0.9424460431654677, 'recall': 0.81875, 'f1-score': 0.8762541806020067, 'support': 160.0} | {'precision': 0.8409302325581396, 'recall': 0.9606801275239107, 'f1-score': 0.8968253968253969, 'support': 941.0} | {'precision': 0.7380442541042113, 'recall': 0.44018731375053216, 'f1-score': 0.5514666666666667, 'support': 4698.0}   | {'precision': 0.8909090909090909, 'recall': 0.8939842209072978, 'f1-score': 0.8924440068914595, 'support': 2028.0} | {'precision': 0.8539305737802696, 'recall': 0.9633941188345333, 'f1-score': 0.9053656685743194, 'support': 14861.0} | {'precision': 0.999850007499625, 'recall': 0.9984273197034375, 'f1-score': 0.9991381571551693, 'support': 13353.0}  | 0.8997   | {'precision': 0.8558572902444468, 'recall': 0.7950140881348429, 'f1-score': 0.8151430169955056, 'support': 36380.0} | {'precision': 0.8934359443718076, 'recall': 0.8996976360637713, 'f1-score': 0.8900236150023304, 'support': 36380.0} |
-| No log        | 5.0   | 205  | 0.2526          | {'precision': 0.7388059701492538, 'recall': 0.584070796460177, 'f1-score': 0.6523887973640857, 'support': 339.0}     | {'precision': 0.9315068493150684, 'recall': 0.85, 'f1-score': 0.888888888888889, 'support': 160.0}     | {'precision': 0.8685491723466408, 'recall': 0.9479277364505845, 'f1-score': 0.9065040650406505, 'support': 941.0} | {'precision': 0.7125307125307125, 'recall': 0.6172839506172839, 'f1-score': 0.6614963503649636, 'support': 4698.0}    | {'precision': 0.8987531172069826, 'recall': 0.888560157790927, 'f1-score': 0.8936275725266551, 'support': 2028.0}  | {'precision': 0.8955877616747182, 'recall': 0.9356032568467801, 'f1-score': 0.9151582965839531, 'support': 14861.0} | {'precision': 0.9991003823375065, 'recall': 0.9980528720137797, 'f1-score': 0.9985763524651581, 'support': 13353.0} | 0.9115   | {'precision': 0.8635477093658405, 'recall': 0.8316426814542189, 'f1-score': 0.8452343318906221, 'support': 36380.0} | {'precision': 0.9081159656876019, 'recall': 0.9114623419461243, 'f1-score': 0.9090309620899378, 'support': 36380.0} |
-| No log        | 6.0   | 246  | 0.2673          | {'precision': 0.7210031347962382, 'recall': 0.6784660766961652, 'f1-score': 0.6990881458966565, 'support': 339.0}    | {'precision': 0.9192546583850931, 'recall': 0.925, 'f1-score': 0.9221183800623053, 'support': 160.0}   | {'precision': 0.8932642487046633, 'recall': 0.9160467587672688, 'f1-score': 0.9045120671563485, 'support': 941.0} | {'precision': 0.7050987597611392, 'recall': 0.6534695615155385, 'f1-score': 0.6783031374281926, 'support': 4698.0}    | {'precision': 0.8852927177534508, 'recall': 0.9171597633136095, 'f1-score': 0.9009445386292081, 'support': 2028.0} | {'precision': 0.904881101376721, 'recall': 0.9243657896507638, 'f1-score': 0.9145196724585581, 'support': 14861.0}  | {'precision': 0.9996992255056771, 'recall': 0.99565640679997, 'f1-score': 0.9976737205463005, 'support': 13353.0}   | 0.9126   | {'precision': 0.8612134066118546, 'recall': 0.8585949081061879, 'f1-score': 0.8595942374539386, 'support': 36380.0} | {'precision': 0.9108414479595167, 'recall': 0.9126443100604728, 'f1-score': 0.9115468219984093, 'support': 36380.0} |
-| No log        | 7.0   | 287  | 0.3082          | {'precision': 0.7455357142857143, 'recall': 0.49262536873156343, 'f1-score': 0.5932504440497335, 'support': 339.0}   | {'precision': 0.9530201342281879, 'recall': 0.8875, 'f1-score': 0.919093851132686, 'support': 160.0}   | {'precision': 0.8419083255378859, 'recall': 0.9564293304994687, 'f1-score': 0.8955223880597015, 'support': 941.0} | {'precision': 0.7359364659166115, 'recall': 0.4733929331630481, 'f1-score': 0.5761658031088083, 'support': 4698.0}    | {'precision': 0.912444663059518, 'recall': 0.9146942800788954, 'f1-score': 0.9135680866781581, 'support': 2028.0}  | {'precision': 0.8574441164065795, 'recall': 0.9576071596796986, 'f1-score': 0.9047619047619048, 'support': 14861.0} | {'precision': 0.9997741984043353, 'recall': 0.9947577323447915, 'f1-score': 0.9972596568940275, 'support': 13353.0} | 0.9016   | {'precision': 0.8637233739769761, 'recall': 0.8110009720710665, 'f1-score': 0.8285174478121456, 'support': 36380.0} | {'precision': 0.8960358642584588, 'recall': 0.9016492578339748, 'f1-score': 0.8936908018647435, 'support': 36380.0} |
-| No log        | 8.0   | 328  | 0.3109          | {'precision': 0.714765100671141, 'recall': 0.6283185840707964, 'f1-score': 0.6687598116169545, 'support': 339.0}     | {'precision': 0.9577464788732394, 'recall': 0.85, 'f1-score': 0.9006622516556291, 'support': 160.0}    | {'precision': 0.8762475049900199, 'recall': 0.9330499468650372, 'f1-score': 0.9037570766855377, 'support': 941.0} | {'precision': 0.7084223013048636, 'recall': 0.6355896126011068, 'f1-score': 0.6700325367440816, 'support': 4698.0}    | {'precision': 0.951974386339381, 'recall': 0.8796844181459567, 'f1-score': 0.9144028703229115, 'support': 2028.0}  | {'precision': 0.8920465505047258, 'recall': 0.9335845501648611, 'f1-score': 0.9123429999342408, 'support': 14861.0} | {'precision': 0.9993983152827918, 'recall': 0.9951321800344491, 'f1-score': 0.9972606852039475, 'support': 13353.0} | 0.9115   | {'precision': 0.8715143768523089, 'recall': 0.8364798988403154, 'f1-score': 0.8524597474519003, 'support': 36380.0} | {'precision': 0.9093055312257066, 'recall': 0.9114623419461243, 'f1-score': 0.9097917557931217, 'support': 36380.0} |
-| No log        | 9.0   | 369  | 0.3515          | {'precision': 0.7183098591549296, 'recall': 0.6017699115044248, 'f1-score': 0.6548956661316213, 'support': 339.0}    | {'precision': 0.9517241379310345, 'recall': 0.8625, 'f1-score': 0.9049180327868853, 'support': 160.0}  | {'precision': 0.8705533596837944, 'recall': 0.9362380446333688, 'f1-score': 0.9022017409114182, 'support': 941.0} | {'precision': 0.7166541070082894, 'recall': 0.60727969348659, 'f1-score': 0.6574490148634635, 'support': 4698.0}      | {'precision': 0.941908713692946, 'recall': 0.8954635108481263, 'f1-score': 0.9180990899898889, 'support': 2028.0}  | {'precision': 0.8871285868804479, 'recall': 0.938227575533275, 'f1-score': 0.9119628491072013, 'support': 14861.0}  | {'precision': 0.9994741981521821, 'recall': 0.9964801917172171, 'f1-score': 0.9979749493737343, 'support': 13353.0} | 0.9110   | {'precision': 0.8693932803576605, 'recall': 0.8339941325318574, 'f1-score': 0.8496430490234591, 'support': 36380.0} | {'precision': 0.9076856069113689, 'recall': 0.9109675645959319, 'f1-score': 0.908328976914783, 'support': 36380.0}  |
-| No log        | 10.0  | 410  | 0.3666          | {'precision': 0.7186440677966102, 'recall': 0.6253687315634219, 'f1-score': 0.6687697160883281, 'support': 339.0}    | {'precision': 0.9403973509933775, 'recall': 0.8875, 'f1-score': 0.9131832797427653, 'support': 160.0}  | {'precision': 0.8801611278952669, 'recall': 0.9287991498405951, 'f1-score': 0.9038262668045501, 'support': 941.0} | {'precision': 0.7035942885278188, 'recall': 0.6083439761600681, 'f1-score': 0.6525114155251142, 'support': 4698.0}    | {'precision': 0.9091796875, 'recall': 0.9181459566074951, 'f1-score': 0.913640824337586, 'support': 2028.0}        | {'precision': 0.8907005220081201, 'recall': 0.9300181683601373, 'f1-score': 0.909934821252222, 'support': 14861.0}  | {'precision': 0.9993991287366681, 'recall': 0.9964801917172171, 'f1-score': 0.9979375257809279, 'support': 13353.0} | 0.9092   | {'precision': 0.8631537390654088, 'recall': 0.8420937391784192, 'f1-score': 0.8514005499330703, 'support': 36380.0} | {'precision': 0.9058079970815979, 'recall': 0.9091533809785597, 'f1-score': 0.9068083056033942, 'support': 36380.0} |
-| No log        | 11.0  | 451  | 0.3872          | {'precision': 0.7272727272727273, 'recall': 0.6607669616519174, 'f1-score': 0.6924265842349304, 'support': 339.0}    | {'precision': 0.9316770186335404, 'recall': 0.9375, 'f1-score': 0.9345794392523364, 'support': 160.0}  | {'precision': 0.8900308324768756, 'recall': 0.9202975557917109, 'f1-score': 0.9049111807732496, 'support': 941.0} | {'precision': 0.7143188674866559, 'recall': 0.6551724137931034, 'f1-score': 0.6834684134562007, 'support': 4698.0}    | {'precision': 0.9243452958292919, 'recall': 0.9398422090729783, 'f1-score': 0.9320293398533007, 'support': 2028.0} | {'precision': 0.9015017378188733, 'recall': 0.9250386918780701, 'f1-score': 0.9131185652607107, 'support': 14861.0} | {'precision': 0.9993242228562847, 'recall': 0.9967048603310118, 'f1-score': 0.9980128229162761, 'support': 13353.0} | 0.9148   | {'precision': 0.8697815289106071, 'recall': 0.8621889560741132, 'f1-score': 0.8655066208210008, 'support': 36380.0} | {'precision': 0.9127204168171501, 'recall': 0.9147883452446399, 'f1-score': 0.9135018437004899, 'support': 36380.0} |
-| No log        | 12.0  | 492  | 0.4655          | {'precision': 0.7546468401486989, 'recall': 0.5988200589970502, 'f1-score': 0.6677631578947368, 'support': 339.0}    | {'precision': 0.9325153374233128, 'recall': 0.95, 'f1-score': 0.9411764705882352, 'support': 160.0}    | {'precision': 0.875, 'recall': 0.9373007438894793, 'f1-score': 0.9050795279630579, 'support': 941.0}              | {'precision': 0.7343623070674249, 'recall': 0.5772669220945083, 'f1-score': 0.6464068644976761, 'support': 4698.0}    | {'precision': 0.9018867924528302, 'recall': 0.9428007889546351, 'f1-score': 0.9218900675024109, 'support': 2028.0} | {'precision': 0.8842823737597169, 'recall': 0.9415247964470762, 'f1-score': 0.9120062573328118, 'support': 14861.0} | {'precision': 0.9992483463619964, 'recall': 0.9955815172620385, 'f1-score': 0.997411561691113, 'support': 13353.0}  | 0.9111   | {'precision': 0.8688488567448543, 'recall': 0.8490421182349696, 'f1-score': 0.8559619867814344, 'support': 36380.0} | {'precision': 0.9068649475511307, 'recall': 0.9111324903793293, 'f1-score': 0.907279105591616, 'support': 36380.0}  |
-| 0.1948        | 13.0  | 533  | 0.4358          | {'precision': 0.7190332326283988, 'recall': 0.7020648967551623, 'f1-score': 0.7104477611940299, 'support': 339.0}    | {'precision': 0.9490445859872612, 'recall': 0.93125, 'f1-score': 0.9400630914826499, 'support': 160.0} | {'precision': 0.9012605042016807, 'recall': 0.9117959617428267, 'f1-score': 0.9064976228209191, 'support': 941.0} | {'precision': 0.7068927548998019, 'recall': 0.6832694763729247, 'f1-score': 0.6948803983115057, 'support': 4698.0}    | {'precision': 0.9245098039215687, 'recall': 0.9299802761341223, 'f1-score': 0.927236971484759, 'support': 2028.0}  | {'precision': 0.9093388319808434, 'recall': 0.9199246349505417, 'f1-score': 0.9146011038635222, 'support': 14861.0} | {'precision': 0.9993996247654784, 'recall': 0.9973039766344641, 'f1-score': 0.9983507009520954, 'support': 13353.0} | 0.9161   | {'precision': 0.8727827626264332, 'recall': 0.8679413175128632, 'f1-score': 0.8702968071584973, 'support': 36380.0} | {'precision': 0.9152897512508446, 'recall': 0.9161352391423859, 'f1-score': 0.9156711036977506, 'support': 36380.0} |
-| 0.1948        | 14.0  | 574  | 0.4497          | {'precision': 0.7331288343558282, 'recall': 0.7050147492625368, 'f1-score': 0.718796992481203, 'support': 339.0}     | {'precision': 0.9612903225806452, 'recall': 0.93125, 'f1-score': 0.9460317460317461, 'support': 160.0} | {'precision': 0.9009384775808134, 'recall': 0.9181721572794899, 'f1-score': 0.9094736842105262, 'support': 941.0} | {'precision': 0.7201365187713311, 'recall': 0.6736909323116219, 'f1-score': 0.6961398878258, 'support': 4698.0}       | {'precision': 0.9266732283464567, 'recall': 0.9285009861932939, 'f1-score': 0.9275862068965517, 'support': 2028.0} | {'precision': 0.9067807768268598, 'recall': 0.9268555278917974, 'f1-score': 0.9167082626202122, 'support': 14861.0} | {'precision': 0.9993244764692637, 'recall': 0.9970793080206695, 'f1-score': 0.9982006297795771, 'support': 13353.0} | 0.9178   | {'precision': 0.8783246621330283, 'recall': 0.8686519515656299, 'f1-score': 0.8732767728350882, 'support': 36380.0} | {'precision': 0.9162249523049875, 'recall': 0.9177570093457944, 'f1-score': 0.9168399262643154, 'support': 36380.0} |
-| 0.1948        | 15.0  | 615  | 0.4661          | {'precision': 0.7324414715719063, 'recall': 0.6460176991150443, 'f1-score': 0.6865203761755485, 'support': 339.0}    | {'precision': 0.954248366013072, 'recall': 0.9125, 'f1-score': 0.9329073482428115, 'support': 160.0}   | {'precision': 0.8846153846153846, 'recall': 0.9287991498405951, 'f1-score': 0.9061689994815967, 'support': 941.0} | {'precision': 0.7287968441814595, 'recall': 0.6292039165602384, 'f1-score': 0.6753484121544437, 'support': 4698.0}    | {'precision': 0.9236453201970444, 'recall': 0.9245562130177515, 'f1-score': 0.9241005421389847, 'support': 2028.0} | {'precision': 0.8956415373720467, 'recall': 0.9361415786286252, 'f1-score': 0.9154438375995262, 'support': 14861.0} | {'precision': 0.9993243750469184, 'recall': 0.9969295289448065, 'f1-score': 0.9981255154832421, 'support': 13353.0} | 0.9152   | {'precision': 0.8741018998568331, 'recall': 0.853449726586723, 'f1-score': 0.8626592901823076, 'support': 36380.0}  | {'precision': 0.9121645966069168, 'recall': 0.9151731720725673, 'f1-score': 0.9129726286511344, 'support': 36380.0} |
-| 0.1948        | 16.0  | 656  | 0.4671          | {'precision': 0.7346278317152104, 'recall': 0.6696165191740413, 'f1-score': 0.7006172839506173, 'support': 339.0}    | {'precision': 0.9490445859872612, 'recall': 0.93125, 'f1-score': 0.9400630914826499, 'support': 160.0} | {'precision': 0.8921971252566735, 'recall': 0.9234856535600425, 'f1-score': 0.9075718015665796, 'support': 941.0} | {'precision': 0.7273820981713186, 'recall': 0.6434653043848446, 'f1-score': 0.6828552066862436, 'support': 4698.0}    | {'precision': 0.9140926640926641, 'recall': 0.9339250493096647, 'f1-score': 0.9239024390243903, 'support': 2028.0} | {'precision': 0.9001753588361369, 'recall': 0.9326424870466321, 'f1-score': 0.9161213563355145, 'support': 14861.0} | {'precision': 0.999324070597071, 'recall': 0.9964801917172171, 'f1-score': 0.9979001049947502, 'support': 13353.0}  | 0.9161   | {'precision': 0.8738348192366193, 'recall': 0.8615521721703489, 'f1-score': 0.8670044691486779, 'support': 36380.0} | {'precision': 0.9134949094533051, 'recall': 0.9161077515118197, 'f1-score': 0.914324131528891, 'support': 36380.0}  |
 ### Framework versions

       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: 0.8987712506312069
 ---
 <!-- 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: 0.4995
+- B-claim: {'precision': 0.6529850746268657, 'recall': 0.6457564575645757, 'f1-score': 0.6493506493506495, 'support': 271.0}
+- B-majorclaim: {'precision': 0.8591549295774648, 'recall': 0.8776978417266187, 'f1-score': 0.8683274021352312, 'support': 139.0}
+- B-premise: {'precision': 0.8767772511848341, 'recall': 0.8767772511848341, 'f1-score': 0.876777251184834, 'support': 633.0}
+- I-claim: {'precision': 0.6591271953166578, 'recall': 0.6190952261934516, 'f1-score': 0.6384843407655625, 'support': 4001.0}
+- I-majorclaim: {'precision': 0.8964467005076142, 'recall': 0.877297565822156, 'f1-score': 0.8867687672608586, 'support': 2013.0}
+- I-premise: {'precision': 0.885505376344086, 'recall': 0.9080804516584333, 'f1-score': 0.8966508427333304, 'support': 11336.0}
+- O: {'precision': 1.0, 'recall': 0.9997347949080623, 'f1-score': 0.9998673798682641, 'support': 11312.0}
+- Accuracy: 0.8988
+- Macro avg: {'precision': 0.8328566467939318, 'recall': 0.829205655579733, 'f1-score': 0.8308895190426757, 'support': 29705.0}
+- Weighted avg: {'precision': 0.896925957019205, 'recall': 0.8987712506312069, 'f1-score': 0.8977022947337076, 'support': 29705.0}
 ## 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   | 0.4083          | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 271.0}                                                 | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 139.0}                                               | {'precision': 0.643595041322314, 'recall': 0.9842022116903634, 'f1-score': 0.778263585259213, 'support': 633.0}   | {'precision': 0.4563708012760368, 'recall': 0.6078480379905024, 'f1-score': 0.5213290460878884, 'support': 4001.0} | {'precision': 0.7011784511784511, 'recall': 0.4138102334823646, 'f1-score': 0.520462355513902, 'support': 2013.0}  | {'precision': 0.8778050331607159, 'recall': 0.8523288637967537, 'f1-score': 0.8648793805666204, 'support': 11336.0} | {'precision': 0.9991081780076697, 'recall': 0.9903642149929278, 'f1-score': 0.9947169811320755, 'support': 11312.0} | 0.8333   | {'precision': 0.5254367864207411, 'recall': 0.5497933659932731, 'f1-score': 0.5256644783656713, 'support': 29705.0} | {'precision': 0.8381591322948091, 'recall': 0.8332940582393537, 'f1-score': 0.830926787853407, 'support': 29705.0}  |
+| No log        | 2.0   | 82   | 0.2959          | {'precision': 0.38823529411764707, 'recall': 0.24354243542435425, 'f1-score': 0.29931972789115646, 'support': 271.0} | {'precision': 0.8620689655172413, 'recall': 0.17985611510791366, 'f1-score': 0.2976190476190476, 'support': 139.0} | {'precision': 0.7422802850356295, 'recall': 0.9873617693522907, 'f1-score': 0.8474576271186441, 'support': 633.0} | {'precision': 0.5749261291684254, 'recall': 0.340414896275931, 'f1-score': 0.42762951334379906, 'support': 4001.0} | {'precision': 0.7699071812408402, 'recall': 0.7829110779930452, 'f1-score': 0.7763546798029557, 'support': 2013.0} | {'precision': 0.8290439755777108, 'recall': 0.9462773465067043, 'f1-score': 0.8837899073120494, 'support': 11336.0} | {'precision': 0.9999115748518879, 'recall': 0.9996463932107497, 'f1-score': 0.9997789664471067, 'support': 11312.0} | 0.8648   | {'precision': 0.7380533436441974, 'recall': 0.6400014334101413, 'f1-score': 0.6474213527906798, 'support': 29705.0} | {'precision': 0.850161508562683, 'recall': 0.8648039050664871, 'f1-score': 0.8503893311871605, 'support': 29705.0}  |
+| No log        | 3.0   | 123  | 0.2633          | {'precision': 0.61328125, 'recall': 0.5793357933579336, 'f1-score': 0.5958254269449716, 'support': 271.0}            | {'precision': 0.7655172413793103, 'recall': 0.7985611510791367, 'f1-score': 0.7816901408450705, 'support': 139.0}  | {'precision': 0.8738317757009346, 'recall': 0.8862559241706162, 'f1-score': 0.88, 'support': 633.0}               | {'precision': 0.6150895140664961, 'recall': 0.6010997250687328, 'f1-score': 0.6080141575022121, 'support': 4001.0} | {'precision': 0.7346859149434257, 'recall': 0.9354197714853453, 'f1-score': 0.8229895104895104, 'support': 2013.0} | {'precision': 0.9111703104905383, 'recall': 0.875, 'f1-score': 0.8927189271892718, 'support': 11336.0}              | {'precision': 1.0, 'recall': 0.9992043847241867, 'f1-score': 0.9996020340481981, 'support': 11312.0}                | 0.8867   | {'precision': 0.7876537152258151, 'recall': 0.8106966785551358, 'f1-score': 0.7972628852884621, 'support': 29705.0} | {'precision': 0.8889636142603039, 'recall': 0.8866857431408853, 'f1-score': 0.8868495578802252, 'support': 29705.0} |
+| No log        | 4.0   | 164  | 0.2767          | {'precision': 0.6180555555555556, 'recall': 0.6568265682656826, 'f1-score': 0.6368515205724509, 'support': 271.0}    | {'precision': 0.7368421052631579, 'recall': 0.9064748201438849, 'f1-score': 0.8129032258064516, 'support': 139.0}  | {'precision': 0.9126712328767124, 'recall': 0.8420221169036335, 'f1-score': 0.8759244042728019, 'support': 633.0} | {'precision': 0.6039107545750815, 'recall': 0.6020994751312172, 'f1-score': 0.6030037546933668, 'support': 4001.0} | {'precision': 0.7743306417339566, 'recall': 0.905116741182315, 'f1-score': 0.8346312414109024, 'support': 2013.0}  | {'precision': 0.9007175946952494, 'recall': 0.8747353563867325, 'f1-score': 0.8875363616021481, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9999115983026874, 'f1-score': 0.9999557971975424, 'support': 11312.0}                | 0.8852   | {'precision': 0.7923611263856734, 'recall': 0.8267409537594504, 'f1-score': 0.8072580436508092, 'support': 29705.0} | {'precision': 0.8868925824921324, 'recall': 0.8852045110250799, 'f1-score': 0.8855540596827394, 'support': 29705.0} |
+| No log        | 5.0   | 205  | 0.2875          | {'precision': 0.6273885350318471, 'recall': 0.7269372693726938, 'f1-score': 0.6735042735042734, 'support': 271.0}    | {'precision': 0.7865853658536586, 'recall': 0.9280575539568345, 'f1-score': 0.8514851485148515, 'support': 139.0}  | {'precision': 0.9257950530035336, 'recall': 0.8278041074249605, 'f1-score': 0.8740617180984154, 'support': 633.0} | {'precision': 0.5824691841126981, 'recall': 0.744063984003999, 'f1-score': 0.6534240561896401, 'support': 4001.0}  | {'precision': 0.8339432753888381, 'recall': 0.9056135121708893, 'f1-score': 0.8683019766611098, 'support': 2013.0} | {'precision': 0.9326903957049115, 'recall': 0.8275405786873676, 'f1-score': 0.8769748527624568, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9994695898161244, 'f1-score': 0.9997347245556637, 'support': 11312.0}                | 0.8866   | {'precision': 0.8126959727279266, 'recall': 0.8513552279189812, 'f1-score': 0.8282123928980587, 'support': 29705.0} | {'precision': 0.90084333519953, 'recall': 0.8866184144083488, 'f1-score': 0.8909875382676978, 'support': 29705.0}   |
+| No log        | 6.0   | 246  | 0.2945          | {'precision': 0.6326530612244898, 'recall': 0.6863468634686347, 'f1-score': 0.6584070796460177, 'support': 271.0}    | {'precision': 0.8818897637795275, 'recall': 0.8057553956834532, 'f1-score': 0.8421052631578947, 'support': 139.0}  | {'precision': 0.8858520900321544, 'recall': 0.8704581358609794, 'f1-score': 0.8780876494023905, 'support': 633.0} | {'precision': 0.6304404482668752, 'recall': 0.6045988502874281, 'f1-score': 0.6172492982903802, 'support': 4001.0} | {'precision': 0.8976501305483029, 'recall': 0.8539493293591655, 'f1-score': 0.8752545824847251, 'support': 2013.0} | {'precision': 0.8802859357505813, 'recall': 0.9016407904022583, 'f1-score': 0.8908354033206956, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9988507779349364, 'f1-score': 0.9994250585997965, 'support': 11312.0}                | 0.8923   | {'precision': 0.829824489943133, 'recall': 0.8173714489995507, 'f1-score': 0.8230520478431285, 'support': 29705.0}  | {'precision': 0.8912660947222903, 'recall': 0.8923413566739606, 'f1-score': 0.8916619674856285, 'support': 29705.0} |
+| No log        | 7.0   | 287  | 0.3037          | {'precision': 0.6442953020134228, 'recall': 0.7084870848708487, 'f1-score': 0.6748681898066783, 'support': 271.0}    | {'precision': 0.8705035971223022, 'recall': 0.8705035971223022, 'f1-score': 0.8705035971223022, 'support': 139.0}  | {'precision': 0.8991735537190083, 'recall': 0.8593996840442338, 'f1-score': 0.8788368336025849, 'support': 633.0} | {'precision': 0.6310387984981226, 'recall': 0.6300924768807799, 'f1-score': 0.6305652826413206, 'support': 4001.0} | {'precision': 0.891640866873065, 'recall': 0.8584202682563339, 'f1-score': 0.8747152619589977, 'support': 2013.0}  | {'precision': 0.8886845331932037, 'recall': 0.8951129146083274, 'f1-score': 0.8918871407225103, 'support': 11336.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | 0.8943   | {'precision': 0.832190950202732, 'recall': 0.8317165751118323, 'f1-score': 0.8316251865506278, 'support': 29705.0}  | {'precision': 0.8944813348740749, 'recall': 0.8942938899175223, 'f1-score': 0.894338297946804, 'support': 29705.0}  |
+| No log        | 8.0   | 328  | 0.3549          | {'precision': 0.6498054474708171, 'recall': 0.6162361623616236, 'f1-score': 0.6325757575757576, 'support': 271.0}    | {'precision': 0.8796992481203008, 'recall': 0.841726618705036, 'f1-score': 0.8602941176470588, 'support': 139.0}   | {'precision': 0.863914373088685, 'recall': 0.8925750394944708, 'f1-score': 0.8780108780108781, 'support': 633.0}  | {'precision': 0.644374282433984, 'recall': 0.5611097225693576, 'f1-score': 0.5998663994655979, 'support': 4001.0}  | {'precision': 0.9037546271813856, 'recall': 0.8489816194734228, 'f1-score': 0.8755122950819673, 'support': 2013.0} | {'precision': 0.8685594989561587, 'recall': 0.9175194071983063, 'f1-score': 0.8923684097636309, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9999115983026874, 'f1-score': 0.9999557971975424, 'support': 11312.0}                | 0.8926   | {'precision': 0.8300153538930474, 'recall': 0.811151452586415, 'f1-score': 0.8197976649632047, 'support': 29705.0}  | {'precision': 0.8887602531095763, 'recall': 0.892610671604107, 'f1-score': 0.8899730612246367, 'support': 29705.0}  |
+| No log        | 9.0   | 369  | 0.3716          | {'precision': 0.6468531468531469, 'recall': 0.6826568265682657, 'f1-score': 0.6642728904847396, 'support': 271.0}    | {'precision': 0.8333333333333334, 'recall': 0.8633093525179856, 'f1-score': 0.8480565371024734, 'support': 139.0}  | {'precision': 0.8941368078175895, 'recall': 0.8672985781990521, 'f1-score': 0.8805132317562149, 'support': 633.0} | {'precision': 0.6205917159763313, 'recall': 0.6553361659585104, 'f1-score': 0.637490882567469, 'support': 4001.0}  | {'precision': 0.8750640040962622, 'recall': 0.8489816194734228, 'f1-score': 0.8618255168935955, 'support': 2013.0} | {'precision': 0.8960551033187226, 'recall': 0.8836450247000706, 'f1-score': 0.8898067954696869, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9992927864214993, 'f1-score': 0.9996462681287585, 'support': 11312.0}                | 0.8923   | {'precision': 0.8237191587707694, 'recall': 0.8286457648341152, 'f1-score': 0.8259445889147053, 'support': 29705.0} | {'precision': 0.8945056752252882, 'recall': 0.8923076923076924, 'f1-score': 0.8933030430182268, 'support': 29705.0} |
+| No log        | 10.0  | 410  | 0.4143          | {'precision': 0.6746987951807228, 'recall': 0.6199261992619927, 'f1-score': 0.6461538461538461, 'support': 271.0}    | {'precision': 0.8157894736842105, 'recall': 0.8920863309352518, 'f1-score': 0.852233676975945, 'support': 139.0}   | {'precision': 0.8785046728971962, 'recall': 0.8909952606635071, 'f1-score': 0.8847058823529412, 'support': 633.0} | {'precision': 0.6611758023288838, 'recall': 0.5818545363659086, 'f1-score': 0.6189843126827972, 'support': 4001.0} | {'precision': 0.8256503879507074, 'recall': 0.8986587183308494, 'f1-score': 0.8606089438629877, 'support': 2013.0} | {'precision': 0.8856627437505369, 'recall': 0.9094918842625265, 'f1-score': 0.8974191582887234, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9997347949080623, 'f1-score': 0.9998673798682641, 'support': 11312.0}                | 0.8959   | {'precision': 0.8202116965417511, 'recall': 0.8275353892468712, 'f1-score': 0.822853314312215, 'support': 29705.0}  | {'precision': 0.8924963153509083, 'recall': 0.8958761151321326, 'f1-score': 0.8936607445011815, 'support': 29705.0} |
+| No log        | 11.0  | 451  | 0.4242          | {'precision': 0.6442953020134228, 'recall': 0.7084870848708487, 'f1-score': 0.6748681898066783, 'support': 271.0}    | {'precision': 0.8661971830985915, 'recall': 0.8848920863309353, 'f1-score': 0.8754448398576513, 'support': 139.0}  | {'precision': 0.8988391376451078, 'recall': 0.8562401263823065, 'f1-score': 0.8770226537216829, 'support': 633.0} | {'precision': 0.6332931242460796, 'recall': 0.6560859785053736, 'f1-score': 0.6444880923152466, 'support': 4001.0} | {'precision': 0.8797595190380761, 'recall': 0.8723298559364133, 'f1-score': 0.8760289348964829, 'support': 2013.0} | {'precision': 0.8979136947218259, 'recall': 0.8884086097388849, 'f1-score': 0.8931358637814828, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9993811881188119, 'f1-score': 0.9996904982977407, 'support': 11312.0}                | 0.8959   | {'precision': 0.8314711372518719, 'recall': 0.8379749899833678, 'f1-score': 0.8343827246681379, 'support': 29705.0} | {'precision': 0.8974745650471141, 'recall': 0.8959434438646693, 'f1-score': 0.8966457372110589, 'support': 29705.0} |
+| No log        | 12.0  | 492  | 0.4911          | {'precision': 0.6926605504587156, 'recall': 0.5571955719557196, 'f1-score': 0.6175869120654396, 'support': 271.0}    | {'precision': 0.8759124087591241, 'recall': 0.8633093525179856, 'f1-score': 0.8695652173913043, 'support': 139.0}  | {'precision': 0.8461538461538461, 'recall': 0.9210110584518167, 'f1-score': 0.8819969742813918, 'support': 633.0} | {'precision': 0.6817567567567567, 'recall': 0.5043739065233691, 'f1-score': 0.5798017526217497, 'support': 4001.0} | {'precision': 0.9035639412997903, 'recall': 0.8564331843020367, 'f1-score': 0.8793675082887019, 'support': 2013.0} | {'precision': 0.8544101168560909, 'recall': 0.9416901905434015, 'f1-score': 0.8959295006294586, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9988507779349364, 'f1-score': 0.9994250585997965, 'support': 11312.0}                | 0.8945   | {'precision': 0.8363510886120462, 'recall': 0.8061234346041807, 'f1-score': 0.8176675605539775, 'support': 29705.0} | {'precision': 0.888377522333214, 'recall': 0.8944622117488639, 'f1-score': 0.8886802353660483, 'support': 29705.0}  |
+| 0.1948        | 13.0  | 533  | 0.4856          | {'precision': 0.6967213114754098, 'recall': 0.6273062730627307, 'f1-score': 0.6601941747572815, 'support': 271.0}    | {'precision': 0.8689655172413793, 'recall': 0.9064748201438849, 'f1-score': 0.8873239436619718, 'support': 139.0}  | {'precision': 0.8715596330275229, 'recall': 0.9004739336492891, 'f1-score': 0.8857808857808857, 'support': 633.0} | {'precision': 0.6689675007190107, 'recall': 0.5813546613346663, 'f1-score': 0.622091468307034, 'support': 4001.0}  | {'precision': 0.8964467005076142, 'recall': 0.877297565822156, 'f1-score': 0.8867687672608586, 'support': 2013.0}  | {'precision': 0.8748636172891313, 'recall': 0.9195483415666902, 'f1-score': 0.8966496064685389, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.998939179632249, 'f1-score': 0.9994693083318592, 'support': 11312.0}                 | 0.8982   | {'precision': 0.8396463257514384, 'recall': 0.8301992536016665, 'f1-score': 0.8340397363669184, 'support': 29705.0} | {'precision': 0.8945239883555292, 'recall': 0.898232620770914, 'f1-score': 0.8957219390068148, 'support': 29705.0}  |
+| 0.1948        | 14.0  | 574  | 0.4750          | {'precision': 0.6655052264808362, 'recall': 0.7047970479704797, 'f1-score': 0.6845878136200716, 'support': 271.0}    | {'precision': 0.8661971830985915, 'recall': 0.8848920863309353, 'f1-score': 0.8754448398576513, 'support': 139.0}  | {'precision': 0.8973941368078175, 'recall': 0.8704581358609794, 'f1-score': 0.8837209302325582, 'support': 633.0} | {'precision': 0.6448780487804878, 'recall': 0.6608347913021745, 'f1-score': 0.6527589186520183, 'support': 4001.0} | {'precision': 0.8922610015174507, 'recall': 0.8763040238450075, 'f1-score': 0.8842105263157896, 'support': 2013.0} | {'precision': 0.8977292886287032, 'recall': 0.8928193366266761, 'f1-score': 0.8952675807164971, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9999115983026874, 'f1-score': 0.9999557971975424, 'support': 11312.0}                | 0.8990   | {'precision': 0.8377092693305553, 'recall': 0.8414310028912771, 'f1-score': 0.839420915227447, 'support': 29705.0}  | {'precision': 0.899974465529261, 'recall': 0.899006901195085, 'f1-score': 0.8994601237155254, 'support': 29705.0}   |
+| 0.1948        | 15.0  | 615  | 0.5226          | {'precision': 0.6761133603238867, 'recall': 0.6162361623616236, 'f1-score': 0.6447876447876448, 'support': 271.0}    | {'precision': 0.8695652173913043, 'recall': 0.8633093525179856, 'f1-score': 0.8664259927797834, 'support': 139.0}  | {'precision': 0.8677811550151976, 'recall': 0.9020537124802528, 'f1-score': 0.8845855925639039, 'support': 633.0} | {'precision': 0.6685476685476686, 'recall': 0.5626093476630842, 'f1-score': 0.6110206297502714, 'support': 4001.0} | {'precision': 0.8988186954288649, 'recall': 0.8693492300049677, 'f1-score': 0.8838383838383838, 'support': 2013.0} | {'precision': 0.8697276652274992, 'recall': 0.9240472829922372, 'f1-score': 0.8960650128314799, 'support': 11336.0} | {'precision': 1.0, 'recall': 0.9992927864214993, 'f1-score': 0.9996462681287585, 'support': 11312.0}                | 0.8968   | {'precision': 0.8357933945620601, 'recall': 0.8195568392059501, 'f1-score': 0.8266242178114608, 'support': 29705.0} | {'precision': 0.8924024852976349, 'recall': 0.8967513886551086, 'f1-score': 0.8936126955615038, 'support': 29705.0} |
+| 0.1948        | 16.0  | 656  | 0.4995          | {'precision': 0.6529850746268657, 'recall': 0.6457564575645757, 'f1-score': 0.6493506493506495, 'support': 271.0}    | {'precision': 0.8591549295774648, 'recall': 0.8776978417266187, 'f1-score': 0.8683274021352312, 'support': 139.0}  | {'precision': 0.8767772511848341, 'recall': 0.8767772511848341, 'f1-score': 0.876777251184834, 'support': 633.0}  | {'precision': 0.6591271953166578, 'recall': 0.6190952261934516, 'f1-score': 0.6384843407655625, 'support': 4001.0} | {'precision': 0.8964467005076142, 'recall': 0.877297565822156, 'f1-score': 0.8867687672608586, 'support': 2013.0}  | {'precision': 0.885505376344086, 'recall': 0.9080804516584333, 'f1-score': 0.8966508427333304, 'support': 11336.0}  | {'precision': 1.0, 'recall': 0.9997347949080623, 'f1-score': 0.9998673798682641, 'support': 11312.0}                | 0.8988   | {'precision': 0.8328566467939318, 'recall': 0.829205655579733, 'f1-score': 0.8308895190426757, 'support': 29705.0}  | {'precision': 0.896925957019205, 'recall': 0.8987712506312069, 'f1-score': 0.8977022947337076, 'support': 29705.0}  |
 ### Framework versions

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