trainer: training complete at 2024-03-02 15:57:21.877070.

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README.md +31 -31
meta_data/README_s42_e16.md +31 -31
meta_data/meta_s42_e16_cvi3.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[40%:60%]
       args: sep_tok_full_labels
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9046282877493756
 ---
 <!-- 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: 0.4607
-- B-claim: {'precision': 0.6819672131147541, 'recall': 0.6561514195583596, 'f1-score': 0.6688102893890675, 'support': 317.0}
-- B-majorclaim: {'precision': 0.8853503184713376, 'recall': 0.896774193548387, 'f1-score': 0.8910256410256411, 'support': 155.0}
-- B-premise: {'precision': 0.8817204301075269, 'recall': 0.8967193195625759, 'f1-score': 0.8891566265060241, 'support': 823.0}
-- I-claim: {'precision': 0.6920813924981614, 'recall': 0.6498618784530387, 'f1-score': 0.6703074913926155, 'support': 4344.0}
-- I-majorclaim: {'precision': 0.8773408239700374, 'recall': 0.8864711447492905, 'f1-score': 0.8818823529411765, 'support': 2114.0}
-- I-premise: {'precision': 0.9018829810259, 'recall': 0.9187183067538767, 'f1-score': 0.9102228047182176, 'support': 13607.0}
-- O: {'precision': 0.9999095513748191, 'recall': 0.9985547827657845, 'f1-score': 0.9992317078682154, 'support': 11071.0}
-- Accuracy: 0.9046
-- Macro avg: {'precision': 0.8457503872232196, 'recall': 0.8433215779130447, 'f1-score': 0.8443767019772797, 'support': 32431.0}
-- Weighted avg: {'precision': 0.9029042970267227, 'recall': 0.9046282877493756, 'f1-score': 0.9036387628518002, 'support': 32431.0}
 ## 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   | 0.4118          | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 317.0}                                              | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 155.0}                                               | {'precision': 0.6759259259259259, 'recall': 0.9756986634264885, 'f1-score': 0.798607657881651, 'support': 823.0}  | {'precision': 0.5029573299535277, 'recall': 0.5481123388581952, 'f1-score': 0.5245648821326283, 'support': 4344.0}  | {'precision': 0.6704953338119167, 'recall': 0.44181646168401134, 'f1-score': 0.5326489877388081, 'support': 2114.0} | {'precision': 0.8756645636917842, 'recall': 0.9078415521422797, 'f1-score': 0.8914627985855524, 'support': 13607.0} | {'precision': 0.9967299482241803, 'recall': 0.9911480444404299, 'f1-score': 0.9939311594202898, 'support': 11071.0} | 0.8462   | {'precision': 0.5316818716581907, 'recall': 0.5520881515073436, 'f1-score': 0.5344593551084185, 'support': 32431.0} | {'precision': 0.835883129998383, 'recall': 0.8462273750423978, 'f1-score': 0.8385782145723601, 'support': 32431.0}  |
-| No log        | 2.0   | 82   | 0.3001          | {'precision': 0.43, 'recall': 0.27129337539432175, 'f1-score': 0.3326885880077369, 'support': 317.0}              | {'precision': 0.896551724137931, 'recall': 0.16774193548387098, 'f1-score': 0.28260869565217395, 'support': 155.0} | {'precision': 0.76981852913085, 'recall': 0.9793438639125152, 'f1-score': 0.8620320855614974, 'support': 823.0}   | {'precision': 0.6927835051546392, 'recall': 0.46408839779005523, 'f1-score': 0.5558312655086849, 'support': 4344.0} | {'precision': 0.7640091116173121, 'recall': 0.793282876064333, 'f1-score': 0.7783708517057322, 'support': 2114.0}   | {'precision': 0.8649596400688103, 'recall': 0.9607554934959948, 'f1-score': 0.9103443473416662, 'support': 13607.0} | {'precision': 0.9998171177761521, 'recall': 0.9876253274320296, 'f1-score': 0.9936838278729495, 'support': 11071.0} | 0.8824   | {'precision': 0.773991375412242, 'recall': 0.6605901813675886, 'f1-score': 0.6736513802357773, 'support': 32431.0}  | {'precision': 0.8748383987044155, 'recall': 0.8824273072060683, 'f1-score': 0.8728332529732901, 'support': 32431.0} |
-| No log        | 3.0   | 123  | 0.2602          | {'precision': 0.6417322834645669, 'recall': 0.5141955835962145, 'f1-score': 0.5709281961471102, 'support': 317.0} | {'precision': 0.8357142857142857, 'recall': 0.7548387096774194, 'f1-score': 0.7932203389830508, 'support': 155.0}  | {'precision': 0.8512304250559284, 'recall': 0.9246658566221142, 'f1-score': 0.8864298194525335, 'support': 823.0} | {'precision': 0.669375175119081, 'recall': 0.5499539594843462, 'f1-score': 0.6038165044862884, 'support': 4344.0}   | {'precision': 0.7790169351507642, 'recall': 0.8921475875118259, 'f1-score': 0.831753031973539, 'support': 2114.0}   | {'precision': 0.890888479523877, 'recall': 0.9240831924744617, 'f1-score': 0.9071822805815085, 'support': 13607.0}  | {'precision': 0.9996376483377117, 'recall': 0.9967482612230151, 'f1-score': 0.9981908638625057, 'support': 11071.0} | 0.8919   | {'precision': 0.8096564617666021, 'recall': 0.7938047357984852, 'f1-score': 0.7987887193552196, 'support': 32431.0} | {'precision': 0.8873436833652745, 'recall': 0.8918935586321729, 'f1-score': 0.8883404854276872, 'support': 32431.0} |
-| No log        | 4.0   | 164  | 0.2530          | {'precision': 0.6433333333333333, 'recall': 0.6088328075709779, 'f1-score': 0.6256077795786061, 'support': 317.0} | {'precision': 0.8284023668639053, 'recall': 0.9032258064516129, 'f1-score': 0.8641975308641976, 'support': 155.0}  | {'precision': 0.8792270531400966, 'recall': 0.8845686512758202, 'f1-score': 0.8818897637795277, 'support': 823.0} | {'precision': 0.6606835505286452, 'recall': 0.6185543278084714, 'f1-score': 0.6389252169777673, 'support': 4344.0}  | {'precision': 0.8184976118106817, 'recall': 0.8916745506149479, 'f1-score': 0.8535204890196967, 'support': 2114.0}  | {'precision': 0.9034563220067084, 'recall': 0.9105607407951789, 'f1-score': 0.9069946195234434, 'support': 13607.0} | {'precision': 1.0, 'recall': 0.9981031523800922, 'f1-score': 0.9990506758283985, 'support': 11071.0}                | 0.8965   | {'precision': 0.8190857482404815, 'recall': 0.830788576699586, 'f1-score': 0.8243122965102339, 'support': 32431.0}  | {'precision': 0.8948409351137605, 'recall': 0.8964570935216305, 'f1-score': 0.8954353191480889, 'support': 32431.0} |
-| No log        | 5.0   | 205  | 0.2600          | {'precision': 0.7109375, 'recall': 0.5741324921135647, 'f1-score': 0.6352530541012217, 'support': 317.0}          | {'precision': 0.8896103896103896, 'recall': 0.8838709677419355, 'f1-score': 0.8867313915857605, 'support': 155.0}  | {'precision': 0.863431151241535, 'recall': 0.9295261239368166, 'f1-score': 0.8952603861907549, 'support': 823.0}  | {'precision': 0.7121212121212122, 'recall': 0.6275322283609577, 'f1-score': 0.667156142927068, 'support': 4344.0}   | {'precision': 0.8813799621928167, 'recall': 0.8822138126773889, 'f1-score': 0.8817966903073287, 'support': 2114.0}  | {'precision': 0.8983086830372939, 'recall': 0.9329021827000809, 'f1-score': 0.9152786790684261, 'support': 13607.0} | {'precision': 1.0, 'recall': 0.9990064131514769, 'f1-score': 0.9995029596493606, 'support': 11071.0}                | 0.9074   | {'precision': 0.8508269854576067, 'recall': 0.8327406029546031, 'f1-score': 0.8401399005471315, 'support': 32431.0} | {'precision': 0.90422246218063, 'recall': 0.907434245012488, 'f1-score': 0.9052313102348954, 'support': 32431.0}    |
-| No log        | 6.0   | 246  | 0.2758          | {'precision': 0.7026022304832714, 'recall': 0.5962145110410094, 'f1-score': 0.6450511945392492, 'support': 317.0} | {'precision': 0.9047619047619048, 'recall': 0.8580645161290322, 'f1-score': 0.880794701986755, 'support': 155.0}   | {'precision': 0.8660612939841089, 'recall': 0.9270959902794653, 'f1-score': 0.8955399061032863, 'support': 823.0} | {'precision': 0.7183248866364363, 'recall': 0.6199355432780848, 'f1-score': 0.6655134066477203, 'support': 4344.0}  | {'precision': 0.8960591133004926, 'recall': 0.8604541154210028, 'f1-score': 0.8778957528957528, 'support': 2114.0}  | {'precision': 0.8941776752638568, 'recall': 0.9401778496362166, 'f1-score': 0.9166009887511642, 'support': 13607.0} | {'precision': 1.0, 'recall': 0.9979225002258152, 'f1-score': 0.9989601699896017, 'support': 11071.0}                | 0.9077   | {'precision': 0.8545695863471529, 'recall': 0.8285521465729466, 'f1-score': 0.8400508744162184, 'support': 32431.0} | {'precision': 0.904334721335495, 'recall': 0.9077117572692794, 'f1-score': 0.9052009899846191, 'support': 32431.0}  |
-| No log        | 7.0   | 287  | 0.2923          | {'precision': 0.6936619718309859, 'recall': 0.6214511041009464, 'f1-score': 0.6555740432612313, 'support': 317.0} | {'precision': 0.910958904109589, 'recall': 0.8580645161290322, 'f1-score': 0.883720930232558, 'support': 155.0}    | {'precision': 0.8688147295742232, 'recall': 0.9173754556500607, 'f1-score': 0.892434988179669, 'support': 823.0}  | {'precision': 0.6873800383877159, 'recall': 0.6595303867403315, 'f1-score': 0.6731672932330828, 'support': 4344.0}  | {'precision': 0.9308342133051742, 'recall': 0.8339640491958372, 'f1-score': 0.8797405189620758, 'support': 2114.0}  | {'precision': 0.8992862241256245, 'recall': 0.925920482104799, 'f1-score': 0.912409023427599, 'support': 13607.0}   | {'precision': 1.0, 'recall': 0.9990064131514769, 'f1-score': 0.9995029596493606, 'support': 11071.0}                | 0.9057   | {'precision': 0.8558480116190447, 'recall': 0.8307589152960692, 'f1-score': 0.8423642509922252, 'support': 32431.0} | {'precision': 0.9046120706425255, 'recall': 0.9056766673861429, 'f1-score': 0.9048109752434238, 'support': 32431.0} |
-| No log        | 8.0   | 328  | 0.3232          | {'precision': 0.7061224489795919, 'recall': 0.5457413249211357, 'f1-score': 0.6156583629893239, 'support': 317.0} | {'precision': 0.9084967320261438, 'recall': 0.896774193548387, 'f1-score': 0.9025974025974025, 'support': 155.0}   | {'precision': 0.8496659242761693, 'recall': 0.9270959902794653, 'f1-score': 0.8866937826844857, 'support': 823.0} | {'precision': 0.7257503949447077, 'recall': 0.5287753222836096, 'f1-score': 0.6117991743241443, 'support': 4344.0}  | {'precision': 0.8606143970655663, 'recall': 0.8878902554399243, 'f1-score': 0.8740395809080327, 'support': 2114.0}  | {'precision': 0.8743462609522515, 'recall': 0.9460571764532961, 'f1-score': 0.9087892693258031, 'support': 13607.0} | {'precision': 0.9999096331104284, 'recall': 0.9994580435371692, 'f1-score': 0.999683787324389, 'support': 11071.0}  | 0.9000   | {'precision': 0.8464151130506943, 'recall': 0.8188274723518553, 'f1-score': 0.8284659085933688, 'support': 32431.0} | {'precision': 0.8943036149810097, 'recall': 0.8999722487743209, 'f1-score': 0.8943167144432094, 'support': 32431.0} |
-| No log        | 9.0   | 369  | 0.3633          | {'precision': 0.7035573122529645, 'recall': 0.5615141955835962, 'f1-score': 0.6245614035087719, 'support': 317.0} | {'precision': 0.9060402684563759, 'recall': 0.8709677419354839, 'f1-score': 0.8881578947368421, 'support': 155.0}  | {'precision': 0.8547486033519553, 'recall': 0.9295261239368166, 'f1-score': 0.890570430733411, 'support': 823.0}  | {'precision': 0.7197630922693267, 'recall': 0.5315377532228361, 'f1-score': 0.6114936440677966, 'support': 4344.0}  | {'precision': 0.8848780487804878, 'recall': 0.8580889309366131, 'f1-score': 0.8712776176753123, 'support': 2114.0}  | {'precision': 0.8723188992310805, 'recall': 0.9504666715661056, 'f1-score': 0.9097175816832553, 'support': 13607.0} | {'precision': 0.9999095022624435, 'recall': 0.9980128263029536, 'f1-score': 0.9989602640025315, 'support': 11071.0} | 0.8998   | {'precision': 0.8487451038006621, 'recall': 0.8143020347834865, 'f1-score': 0.8278198337725601, 'support': 32431.0} | {'precision': 0.8943247645610162, 'recall': 0.8998489099935247, 'f1-score': 0.8943546419605405, 'support': 32431.0} |
-| No log        | 10.0  | 410  | 0.3689          | {'precision': 0.6383561643835617, 'recall': 0.7350157728706624, 'f1-score': 0.6832844574780059, 'support': 317.0} | {'precision': 0.879746835443038, 'recall': 0.896774193548387, 'f1-score': 0.8881789137380192, 'support': 155.0}    | {'precision': 0.9108527131782945, 'recall': 0.8566221142162819, 'f1-score': 0.8829054477144646, 'support': 823.0} | {'precision': 0.6362704918032787, 'recall': 0.7147790055248618, 'f1-score': 0.6732437120555073, 'support': 4344.0}  | {'precision': 0.8423403305046896, 'recall': 0.8921475875118259, 'f1-score': 0.8665288306914771, 'support': 2114.0}  | {'precision': 0.9262117937635073, 'recall': 0.8818990225619167, 'f1-score': 0.9035124044723865, 'support': 13607.0} | {'precision': 1.0, 'recall': 0.9989160870743383, 'f1-score': 0.9994577496610935, 'support': 11071.0}                | 0.8981   | {'precision': 0.8333969041537671, 'recall': 0.8537362547583249, 'f1-score': 0.8424445022587078, 'support': 32431.0} | {'precision': 0.9036718509873083, 'recall': 0.8981221670623786, 'f1-score': 0.9002621798749209, 'support': 32431.0} |
-| No log        | 11.0  | 451  | 0.4103          | {'precision': 0.7154150197628458, 'recall': 0.5709779179810726, 'f1-score': 0.6350877192982457, 'support': 317.0} | {'precision': 0.896774193548387, 'recall': 0.896774193548387, 'f1-score': 0.896774193548387, 'support': 155.0}     | {'precision': 0.8592342342342343, 'recall': 0.9270959902794653, 'f1-score': 0.8918760958503799, 'support': 823.0} | {'precision': 0.706850926198177, 'recall': 0.5534069981583793, 'f1-score': 0.6207876049063913, 'support': 4344.0}   | {'precision': 0.8774740810556079, 'recall': 0.8807947019867549, 'f1-score': 0.8791312559017942, 'support': 2114.0}  | {'precision': 0.8783570300157978, 'recall': 0.9398103917101492, 'f1-score': 0.9080451608322092, 'support': 13607.0} | {'precision': 0.9999095268252963, 'recall': 0.998283804534369, 'f1-score': 0.9990960043391791, 'support': 11071.0}  | 0.9000   | {'precision': 0.8477164302343352, 'recall': 0.8238777140283682, 'f1-score': 0.832971147810941, 'support': 32431.0}  | {'precision': 0.8948314712991845, 'recall': 0.9000339181647189, 'f1-score': 0.8956333147937184, 'support': 32431.0} |
-| No log        | 12.0  | 492  | 0.3971          | {'precision': 0.6933333333333334, 'recall': 0.6561514195583596, 'f1-score': 0.674230145867099, 'support': 317.0}  | {'precision': 0.8805031446540881, 'recall': 0.9032258064516129, 'f1-score': 0.89171974522293, 'support': 155.0}    | {'precision': 0.8843861740166865, 'recall': 0.9015795868772782, 'f1-score': 0.8929001203369434, 'support': 823.0} | {'precision': 0.6998045920859794, 'recall': 0.6595303867403315, 'f1-score': 0.6790708698743778, 'support': 4344.0}  | {'precision': 0.8721144967682364, 'recall': 0.8935666982024598, 'f1-score': 0.8827102803738317, 'support': 2114.0}  | {'precision': 0.9050408620814349, 'recall': 0.919673697361652, 'f1-score': 0.9122986075672522, 'support': 13607.0}  | {'precision': 0.9999094694912185, 'recall': 0.9976515219943998, 'f1-score': 0.9987792196048288, 'support': 11071.0} | 0.9066   | {'precision': 0.8478702960615683, 'recall': 0.8473398738837278, 'f1-score': 0.8473869984067518, 'support': 32431.0} | {'precision': 0.9050786104829543, 'recall': 0.9066325429373131, 'f1-score': 0.9057343159521435, 'support': 32431.0} |
-| 0.1957        | 13.0  | 533  | 0.4370          | {'precision': 0.675, 'recall': 0.6813880126182965, 'f1-score': 0.6781789638932496, 'support': 317.0}              | {'precision': 0.8421052631578947, 'recall': 0.9290322580645162, 'f1-score': 0.8834355828220859, 'support': 155.0}  | {'precision': 0.895910780669145, 'recall': 0.8784933171324423, 'f1-score': 0.8871165644171779, 'support': 823.0}  | {'precision': 0.6602881584871679, 'recall': 0.6751841620626151, 'f1-score': 0.6676530844525382, 'support': 4344.0}  | {'precision': 0.8328358208955224, 'recall': 0.9238410596026491, 'f1-score': 0.8759811616954475, 'support': 2114.0}  | {'precision': 0.9138385130559109, 'recall': 0.8924818108326596, 'f1-score': 0.9030339083878643, 'support': 13607.0} | {'precision': 0.999909559555033, 'recall': 0.9986451088429229, 'f1-score': 0.9992769342010123, 'support': 11071.0}  | 0.8994   | {'precision': 0.8314125851172391, 'recall': 0.8541522470223003, 'f1-score': 0.8420965999813396, 'support': 32431.0} | {'precision': 0.9008461643213939, 'recall': 0.8994172242607382, 'f1-score': 0.8999012883989392, 'support': 32431.0} |
-| 0.1957        | 14.0  | 574  | 0.4532          | {'precision': 0.6666666666666666, 'recall': 0.694006309148265, 'f1-score': 0.6800618238021638, 'support': 317.0}  | {'precision': 0.8875, 'recall': 0.9161290322580645, 'f1-score': 0.9015873015873015, 'support': 155.0}              | {'precision': 0.8948019801980198, 'recall': 0.8784933171324423, 'f1-score': 0.8865726548129982, 'support': 823.0} | {'precision': 0.660063034669068, 'recall': 0.6749539594843462, 'f1-score': 0.6674254495788755, 'support': 4344.0}   | {'precision': 0.8716998610467809, 'recall': 0.8902554399243141, 'f1-score': 0.8808799438333722, 'support': 2114.0}  | {'precision': 0.9096036811637227, 'recall': 0.9007128683765708, 'f1-score': 0.905136442524279, 'support': 13607.0}  | {'precision': 0.9999095677337674, 'recall': 0.9987354349200614, 'f1-score': 0.9993221564462921, 'support': 11071.0} | 0.9007   | {'precision': 0.8414635416397179, 'recall': 0.8504694801777236, 'f1-score': 0.845855110369326, 'support': 32431.0}  | {'precision': 0.9016799144604528, 'recall': 0.9007431161542968, 'f1-score': 0.9011790708421438, 'support': 32431.0} |
-| 0.1957        | 15.0  | 615  | 0.4669          | {'precision': 0.6872964169381107, 'recall': 0.6656151419558359, 'f1-score': 0.6762820512820512, 'support': 317.0} | {'precision': 0.8650306748466258, 'recall': 0.9096774193548387, 'f1-score': 0.8867924528301888, 'support': 155.0}  | {'precision': 0.8890229191797346, 'recall': 0.8955042527339003, 'f1-score': 0.8922518159806295, 'support': 823.0} | {'precision': 0.6812977099236641, 'recall': 0.6574585635359116, 'f1-score': 0.669165885660731, 'support': 4344.0}   | {'precision': 0.8544961590600995, 'recall': 0.8945127719962157, 'f1-score': 0.8740466836145135, 'support': 2114.0}  | {'precision': 0.9068645368813509, 'recall': 0.9116631145733813, 'f1-score': 0.9092574946859194, 'support': 13607.0} | {'precision': 0.9999094858797972, 'recall': 0.9978321741486768, 'f1-score': 0.9988697499886975, 'support': 11071.0} | 0.9031   | {'precision': 0.8405597003870547, 'recall': 0.8474662054712514, 'f1-score': 0.8438094477203901, 'support': 32431.0} | {'precision': 0.9022011157514956, 'recall': 0.9030865529894238, 'f1-score': 0.9025778580304222, 'support': 32431.0} |
-| 0.1957        | 16.0  | 656  | 0.4607          | {'precision': 0.6819672131147541, 'recall': 0.6561514195583596, 'f1-score': 0.6688102893890675, 'support': 317.0} | {'precision': 0.8853503184713376, 'recall': 0.896774193548387, 'f1-score': 0.8910256410256411, 'support': 155.0}   | {'precision': 0.8817204301075269, 'recall': 0.8967193195625759, 'f1-score': 0.8891566265060241, 'support': 823.0} | {'precision': 0.6920813924981614, 'recall': 0.6498618784530387, 'f1-score': 0.6703074913926155, 'support': 4344.0}  | {'precision': 0.8773408239700374, 'recall': 0.8864711447492905, 'f1-score': 0.8818823529411765, 'support': 2114.0}  | {'precision': 0.9018829810259, 'recall': 0.9187183067538767, 'f1-score': 0.9102228047182176, 'support': 13607.0}    | {'precision': 0.9999095513748191, 'recall': 0.9985547827657845, 'f1-score': 0.9992317078682154, 'support': 11071.0} | 0.9046   | {'precision': 0.8457503872232196, 'recall': 0.8433215779130447, 'f1-score': 0.8443767019772797, 'support': 32431.0} | {'precision': 0.9029042970267227, 'recall': 0.9046282877493756, 'f1-score': 0.9036387628518002, 'support': 32431.0} |
 ### Framework versions

       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
 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
 ### 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

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[40%:60%]
       args: sep_tok_full_labels
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9046282877493756
 ---
 <!-- 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: 0.4607
-- B-claim: {'precision': 0.6819672131147541, 'recall': 0.6561514195583596, 'f1-score': 0.6688102893890675, 'support': 317.0}
-- B-majorclaim: {'precision': 0.8853503184713376, 'recall': 0.896774193548387, 'f1-score': 0.8910256410256411, 'support': 155.0}
-- B-premise: {'precision': 0.8817204301075269, 'recall': 0.8967193195625759, 'f1-score': 0.8891566265060241, 'support': 823.0}
-- I-claim: {'precision': 0.6920813924981614, 'recall': 0.6498618784530387, 'f1-score': 0.6703074913926155, 'support': 4344.0}
-- I-majorclaim: {'precision': 0.8773408239700374, 'recall': 0.8864711447492905, 'f1-score': 0.8818823529411765, 'support': 2114.0}
-- I-premise: {'precision': 0.9018829810259, 'recall': 0.9187183067538767, 'f1-score': 0.9102228047182176, 'support': 13607.0}
-- O: {'precision': 0.9999095513748191, 'recall': 0.9985547827657845, 'f1-score': 0.9992317078682154, 'support': 11071.0}
-- Accuracy: 0.9046
-- Macro avg: {'precision': 0.8457503872232196, 'recall': 0.8433215779130447, 'f1-score': 0.8443767019772797, 'support': 32431.0}
-- Weighted avg: {'precision': 0.9029042970267227, 'recall': 0.9046282877493756, 'f1-score': 0.9036387628518002, 'support': 32431.0}
 ## 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   | 0.4118          | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 317.0}                                              | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 155.0}                                               | {'precision': 0.6759259259259259, 'recall': 0.9756986634264885, 'f1-score': 0.798607657881651, 'support': 823.0}  | {'precision': 0.5029573299535277, 'recall': 0.5481123388581952, 'f1-score': 0.5245648821326283, 'support': 4344.0}  | {'precision': 0.6704953338119167, 'recall': 0.44181646168401134, 'f1-score': 0.5326489877388081, 'support': 2114.0} | {'precision': 0.8756645636917842, 'recall': 0.9078415521422797, 'f1-score': 0.8914627985855524, 'support': 13607.0} | {'precision': 0.9967299482241803, 'recall': 0.9911480444404299, 'f1-score': 0.9939311594202898, 'support': 11071.0} | 0.8462   | {'precision': 0.5316818716581907, 'recall': 0.5520881515073436, 'f1-score': 0.5344593551084185, 'support': 32431.0} | {'precision': 0.835883129998383, 'recall': 0.8462273750423978, 'f1-score': 0.8385782145723601, 'support': 32431.0}  |
-| No log        | 2.0   | 82   | 0.3001          | {'precision': 0.43, 'recall': 0.27129337539432175, 'f1-score': 0.3326885880077369, 'support': 317.0}              | {'precision': 0.896551724137931, 'recall': 0.16774193548387098, 'f1-score': 0.28260869565217395, 'support': 155.0} | {'precision': 0.76981852913085, 'recall': 0.9793438639125152, 'f1-score': 0.8620320855614974, 'support': 823.0}   | {'precision': 0.6927835051546392, 'recall': 0.46408839779005523, 'f1-score': 0.5558312655086849, 'support': 4344.0} | {'precision': 0.7640091116173121, 'recall': 0.793282876064333, 'f1-score': 0.7783708517057322, 'support': 2114.0}   | {'precision': 0.8649596400688103, 'recall': 0.9607554934959948, 'f1-score': 0.9103443473416662, 'support': 13607.0} | {'precision': 0.9998171177761521, 'recall': 0.9876253274320296, 'f1-score': 0.9936838278729495, 'support': 11071.0} | 0.8824   | {'precision': 0.773991375412242, 'recall': 0.6605901813675886, 'f1-score': 0.6736513802357773, 'support': 32431.0}  | {'precision': 0.8748383987044155, 'recall': 0.8824273072060683, 'f1-score': 0.8728332529732901, 'support': 32431.0} |
-| No log        | 3.0   | 123  | 0.2602          | {'precision': 0.6417322834645669, 'recall': 0.5141955835962145, 'f1-score': 0.5709281961471102, 'support': 317.0} | {'precision': 0.8357142857142857, 'recall': 0.7548387096774194, 'f1-score': 0.7932203389830508, 'support': 155.0}  | {'precision': 0.8512304250559284, 'recall': 0.9246658566221142, 'f1-score': 0.8864298194525335, 'support': 823.0} | {'precision': 0.669375175119081, 'recall': 0.5499539594843462, 'f1-score': 0.6038165044862884, 'support': 4344.0}   | {'precision': 0.7790169351507642, 'recall': 0.8921475875118259, 'f1-score': 0.831753031973539, 'support': 2114.0}   | {'precision': 0.890888479523877, 'recall': 0.9240831924744617, 'f1-score': 0.9071822805815085, 'support': 13607.0}  | {'precision': 0.9996376483377117, 'recall': 0.9967482612230151, 'f1-score': 0.9981908638625057, 'support': 11071.0} | 0.8919   | {'precision': 0.8096564617666021, 'recall': 0.7938047357984852, 'f1-score': 0.7987887193552196, 'support': 32431.0} | {'precision': 0.8873436833652745, 'recall': 0.8918935586321729, 'f1-score': 0.8883404854276872, 'support': 32431.0} |
-| No log        | 4.0   | 164  | 0.2530          | {'precision': 0.6433333333333333, 'recall': 0.6088328075709779, 'f1-score': 0.6256077795786061, 'support': 317.0} | {'precision': 0.8284023668639053, 'recall': 0.9032258064516129, 'f1-score': 0.8641975308641976, 'support': 155.0}  | {'precision': 0.8792270531400966, 'recall': 0.8845686512758202, 'f1-score': 0.8818897637795277, 'support': 823.0} | {'precision': 0.6606835505286452, 'recall': 0.6185543278084714, 'f1-score': 0.6389252169777673, 'support': 4344.0}  | {'precision': 0.8184976118106817, 'recall': 0.8916745506149479, 'f1-score': 0.8535204890196967, 'support': 2114.0}  | {'precision': 0.9034563220067084, 'recall': 0.9105607407951789, 'f1-score': 0.9069946195234434, 'support': 13607.0} | {'precision': 1.0, 'recall': 0.9981031523800922, 'f1-score': 0.9990506758283985, 'support': 11071.0}                | 0.8965   | {'precision': 0.8190857482404815, 'recall': 0.830788576699586, 'f1-score': 0.8243122965102339, 'support': 32431.0}  | {'precision': 0.8948409351137605, 'recall': 0.8964570935216305, 'f1-score': 0.8954353191480889, 'support': 32431.0} |
-| No log        | 5.0   | 205  | 0.2600          | {'precision': 0.7109375, 'recall': 0.5741324921135647, 'f1-score': 0.6352530541012217, 'support': 317.0}          | {'precision': 0.8896103896103896, 'recall': 0.8838709677419355, 'f1-score': 0.8867313915857605, 'support': 155.0}  | {'precision': 0.863431151241535, 'recall': 0.9295261239368166, 'f1-score': 0.8952603861907549, 'support': 823.0}  | {'precision': 0.7121212121212122, 'recall': 0.6275322283609577, 'f1-score': 0.667156142927068, 'support': 4344.0}   | {'precision': 0.8813799621928167, 'recall': 0.8822138126773889, 'f1-score': 0.8817966903073287, 'support': 2114.0}  | {'precision': 0.8983086830372939, 'recall': 0.9329021827000809, 'f1-score': 0.9152786790684261, 'support': 13607.0} | {'precision': 1.0, 'recall': 0.9990064131514769, 'f1-score': 0.9995029596493606, 'support': 11071.0}                | 0.9074   | {'precision': 0.8508269854576067, 'recall': 0.8327406029546031, 'f1-score': 0.8401399005471315, 'support': 32431.0} | {'precision': 0.90422246218063, 'recall': 0.907434245012488, 'f1-score': 0.9052313102348954, 'support': 32431.0}    |
-| No log        | 6.0   | 246  | 0.2758          | {'precision': 0.7026022304832714, 'recall': 0.5962145110410094, 'f1-score': 0.6450511945392492, 'support': 317.0} | {'precision': 0.9047619047619048, 'recall': 0.8580645161290322, 'f1-score': 0.880794701986755, 'support': 155.0}   | {'precision': 0.8660612939841089, 'recall': 0.9270959902794653, 'f1-score': 0.8955399061032863, 'support': 823.0} | {'precision': 0.7183248866364363, 'recall': 0.6199355432780848, 'f1-score': 0.6655134066477203, 'support': 4344.0}  | {'precision': 0.8960591133004926, 'recall': 0.8604541154210028, 'f1-score': 0.8778957528957528, 'support': 2114.0}  | {'precision': 0.8941776752638568, 'recall': 0.9401778496362166, 'f1-score': 0.9166009887511642, 'support': 13607.0} | {'precision': 1.0, 'recall': 0.9979225002258152, 'f1-score': 0.9989601699896017, 'support': 11071.0}                | 0.9077   | {'precision': 0.8545695863471529, 'recall': 0.8285521465729466, 'f1-score': 0.8400508744162184, 'support': 32431.0} | {'precision': 0.904334721335495, 'recall': 0.9077117572692794, 'f1-score': 0.9052009899846191, 'support': 32431.0}  |
-| No log        | 7.0   | 287  | 0.2923          | {'precision': 0.6936619718309859, 'recall': 0.6214511041009464, 'f1-score': 0.6555740432612313, 'support': 317.0} | {'precision': 0.910958904109589, 'recall': 0.8580645161290322, 'f1-score': 0.883720930232558, 'support': 155.0}    | {'precision': 0.8688147295742232, 'recall': 0.9173754556500607, 'f1-score': 0.892434988179669, 'support': 823.0}  | {'precision': 0.6873800383877159, 'recall': 0.6595303867403315, 'f1-score': 0.6731672932330828, 'support': 4344.0}  | {'precision': 0.9308342133051742, 'recall': 0.8339640491958372, 'f1-score': 0.8797405189620758, 'support': 2114.0}  | {'precision': 0.8992862241256245, 'recall': 0.925920482104799, 'f1-score': 0.912409023427599, 'support': 13607.0}   | {'precision': 1.0, 'recall': 0.9990064131514769, 'f1-score': 0.9995029596493606, 'support': 11071.0}                | 0.9057   | {'precision': 0.8558480116190447, 'recall': 0.8307589152960692, 'f1-score': 0.8423642509922252, 'support': 32431.0} | {'precision': 0.9046120706425255, 'recall': 0.9056766673861429, 'f1-score': 0.9048109752434238, 'support': 32431.0} |
-| No log        | 8.0   | 328  | 0.3232          | {'precision': 0.7061224489795919, 'recall': 0.5457413249211357, 'f1-score': 0.6156583629893239, 'support': 317.0} | {'precision': 0.9084967320261438, 'recall': 0.896774193548387, 'f1-score': 0.9025974025974025, 'support': 155.0}   | {'precision': 0.8496659242761693, 'recall': 0.9270959902794653, 'f1-score': 0.8866937826844857, 'support': 823.0} | {'precision': 0.7257503949447077, 'recall': 0.5287753222836096, 'f1-score': 0.6117991743241443, 'support': 4344.0}  | {'precision': 0.8606143970655663, 'recall': 0.8878902554399243, 'f1-score': 0.8740395809080327, 'support': 2114.0}  | {'precision': 0.8743462609522515, 'recall': 0.9460571764532961, 'f1-score': 0.9087892693258031, 'support': 13607.0} | {'precision': 0.9999096331104284, 'recall': 0.9994580435371692, 'f1-score': 0.999683787324389, 'support': 11071.0}  | 0.9000   | {'precision': 0.8464151130506943, 'recall': 0.8188274723518553, 'f1-score': 0.8284659085933688, 'support': 32431.0} | {'precision': 0.8943036149810097, 'recall': 0.8999722487743209, 'f1-score': 0.8943167144432094, 'support': 32431.0} |
-| No log        | 9.0   | 369  | 0.3633          | {'precision': 0.7035573122529645, 'recall': 0.5615141955835962, 'f1-score': 0.6245614035087719, 'support': 317.0} | {'precision': 0.9060402684563759, 'recall': 0.8709677419354839, 'f1-score': 0.8881578947368421, 'support': 155.0}  | {'precision': 0.8547486033519553, 'recall': 0.9295261239368166, 'f1-score': 0.890570430733411, 'support': 823.0}  | {'precision': 0.7197630922693267, 'recall': 0.5315377532228361, 'f1-score': 0.6114936440677966, 'support': 4344.0}  | {'precision': 0.8848780487804878, 'recall': 0.8580889309366131, 'f1-score': 0.8712776176753123, 'support': 2114.0}  | {'precision': 0.8723188992310805, 'recall': 0.9504666715661056, 'f1-score': 0.9097175816832553, 'support': 13607.0} | {'precision': 0.9999095022624435, 'recall': 0.9980128263029536, 'f1-score': 0.9989602640025315, 'support': 11071.0} | 0.8998   | {'precision': 0.8487451038006621, 'recall': 0.8143020347834865, 'f1-score': 0.8278198337725601, 'support': 32431.0} | {'precision': 0.8943247645610162, 'recall': 0.8998489099935247, 'f1-score': 0.8943546419605405, 'support': 32431.0} |
-| No log        | 10.0  | 410  | 0.3689          | {'precision': 0.6383561643835617, 'recall': 0.7350157728706624, 'f1-score': 0.6832844574780059, 'support': 317.0} | {'precision': 0.879746835443038, 'recall': 0.896774193548387, 'f1-score': 0.8881789137380192, 'support': 155.0}    | {'precision': 0.9108527131782945, 'recall': 0.8566221142162819, 'f1-score': 0.8829054477144646, 'support': 823.0} | {'precision': 0.6362704918032787, 'recall': 0.7147790055248618, 'f1-score': 0.6732437120555073, 'support': 4344.0}  | {'precision': 0.8423403305046896, 'recall': 0.8921475875118259, 'f1-score': 0.8665288306914771, 'support': 2114.0}  | {'precision': 0.9262117937635073, 'recall': 0.8818990225619167, 'f1-score': 0.9035124044723865, 'support': 13607.0} | {'precision': 1.0, 'recall': 0.9989160870743383, 'f1-score': 0.9994577496610935, 'support': 11071.0}                | 0.8981   | {'precision': 0.8333969041537671, 'recall': 0.8537362547583249, 'f1-score': 0.8424445022587078, 'support': 32431.0} | {'precision': 0.9036718509873083, 'recall': 0.8981221670623786, 'f1-score': 0.9002621798749209, 'support': 32431.0} |
-| No log        | 11.0  | 451  | 0.4103          | {'precision': 0.7154150197628458, 'recall': 0.5709779179810726, 'f1-score': 0.6350877192982457, 'support': 317.0} | {'precision': 0.896774193548387, 'recall': 0.896774193548387, 'f1-score': 0.896774193548387, 'support': 155.0}     | {'precision': 0.8592342342342343, 'recall': 0.9270959902794653, 'f1-score': 0.8918760958503799, 'support': 823.0} | {'precision': 0.706850926198177, 'recall': 0.5534069981583793, 'f1-score': 0.6207876049063913, 'support': 4344.0}   | {'precision': 0.8774740810556079, 'recall': 0.8807947019867549, 'f1-score': 0.8791312559017942, 'support': 2114.0}  | {'precision': 0.8783570300157978, 'recall': 0.9398103917101492, 'f1-score': 0.9080451608322092, 'support': 13607.0} | {'precision': 0.9999095268252963, 'recall': 0.998283804534369, 'f1-score': 0.9990960043391791, 'support': 11071.0}  | 0.9000   | {'precision': 0.8477164302343352, 'recall': 0.8238777140283682, 'f1-score': 0.832971147810941, 'support': 32431.0}  | {'precision': 0.8948314712991845, 'recall': 0.9000339181647189, 'f1-score': 0.8956333147937184, 'support': 32431.0} |
-| No log        | 12.0  | 492  | 0.3971          | {'precision': 0.6933333333333334, 'recall': 0.6561514195583596, 'f1-score': 0.674230145867099, 'support': 317.0}  | {'precision': 0.8805031446540881, 'recall': 0.9032258064516129, 'f1-score': 0.89171974522293, 'support': 155.0}    | {'precision': 0.8843861740166865, 'recall': 0.9015795868772782, 'f1-score': 0.8929001203369434, 'support': 823.0} | {'precision': 0.6998045920859794, 'recall': 0.6595303867403315, 'f1-score': 0.6790708698743778, 'support': 4344.0}  | {'precision': 0.8721144967682364, 'recall': 0.8935666982024598, 'f1-score': 0.8827102803738317, 'support': 2114.0}  | {'precision': 0.9050408620814349, 'recall': 0.919673697361652, 'f1-score': 0.9122986075672522, 'support': 13607.0}  | {'precision': 0.9999094694912185, 'recall': 0.9976515219943998, 'f1-score': 0.9987792196048288, 'support': 11071.0} | 0.9066   | {'precision': 0.8478702960615683, 'recall': 0.8473398738837278, 'f1-score': 0.8473869984067518, 'support': 32431.0} | {'precision': 0.9050786104829543, 'recall': 0.9066325429373131, 'f1-score': 0.9057343159521435, 'support': 32431.0} |
-| 0.1957        | 13.0  | 533  | 0.4370          | {'precision': 0.675, 'recall': 0.6813880126182965, 'f1-score': 0.6781789638932496, 'support': 317.0}              | {'precision': 0.8421052631578947, 'recall': 0.9290322580645162, 'f1-score': 0.8834355828220859, 'support': 155.0}  | {'precision': 0.895910780669145, 'recall': 0.8784933171324423, 'f1-score': 0.8871165644171779, 'support': 823.0}  | {'precision': 0.6602881584871679, 'recall': 0.6751841620626151, 'f1-score': 0.6676530844525382, 'support': 4344.0}  | {'precision': 0.8328358208955224, 'recall': 0.9238410596026491, 'f1-score': 0.8759811616954475, 'support': 2114.0}  | {'precision': 0.9138385130559109, 'recall': 0.8924818108326596, 'f1-score': 0.9030339083878643, 'support': 13607.0} | {'precision': 0.999909559555033, 'recall': 0.9986451088429229, 'f1-score': 0.9992769342010123, 'support': 11071.0}  | 0.8994   | {'precision': 0.8314125851172391, 'recall': 0.8541522470223003, 'f1-score': 0.8420965999813396, 'support': 32431.0} | {'precision': 0.9008461643213939, 'recall': 0.8994172242607382, 'f1-score': 0.8999012883989392, 'support': 32431.0} |
-| 0.1957        | 14.0  | 574  | 0.4532          | {'precision': 0.6666666666666666, 'recall': 0.694006309148265, 'f1-score': 0.6800618238021638, 'support': 317.0}  | {'precision': 0.8875, 'recall': 0.9161290322580645, 'f1-score': 0.9015873015873015, 'support': 155.0}              | {'precision': 0.8948019801980198, 'recall': 0.8784933171324423, 'f1-score': 0.8865726548129982, 'support': 823.0} | {'precision': 0.660063034669068, 'recall': 0.6749539594843462, 'f1-score': 0.6674254495788755, 'support': 4344.0}   | {'precision': 0.8716998610467809, 'recall': 0.8902554399243141, 'f1-score': 0.8808799438333722, 'support': 2114.0}  | {'precision': 0.9096036811637227, 'recall': 0.9007128683765708, 'f1-score': 0.905136442524279, 'support': 13607.0}  | {'precision': 0.9999095677337674, 'recall': 0.9987354349200614, 'f1-score': 0.9993221564462921, 'support': 11071.0} | 0.9007   | {'precision': 0.8414635416397179, 'recall': 0.8504694801777236, 'f1-score': 0.845855110369326, 'support': 32431.0}  | {'precision': 0.9016799144604528, 'recall': 0.9007431161542968, 'f1-score': 0.9011790708421438, 'support': 32431.0} |
-| 0.1957        | 15.0  | 615  | 0.4669          | {'precision': 0.6872964169381107, 'recall': 0.6656151419558359, 'f1-score': 0.6762820512820512, 'support': 317.0} | {'precision': 0.8650306748466258, 'recall': 0.9096774193548387, 'f1-score': 0.8867924528301888, 'support': 155.0}  | {'precision': 0.8890229191797346, 'recall': 0.8955042527339003, 'f1-score': 0.8922518159806295, 'support': 823.0} | {'precision': 0.6812977099236641, 'recall': 0.6574585635359116, 'f1-score': 0.669165885660731, 'support': 4344.0}   | {'precision': 0.8544961590600995, 'recall': 0.8945127719962157, 'f1-score': 0.8740466836145135, 'support': 2114.0}  | {'precision': 0.9068645368813509, 'recall': 0.9116631145733813, 'f1-score': 0.9092574946859194, 'support': 13607.0} | {'precision': 0.9999094858797972, 'recall': 0.9978321741486768, 'f1-score': 0.9988697499886975, 'support': 11071.0} | 0.9031   | {'precision': 0.8405597003870547, 'recall': 0.8474662054712514, 'f1-score': 0.8438094477203901, 'support': 32431.0} | {'precision': 0.9022011157514956, 'recall': 0.9030865529894238, 'f1-score': 0.9025778580304222, 'support': 32431.0} |
-| 0.1957        | 16.0  | 656  | 0.4607          | {'precision': 0.6819672131147541, 'recall': 0.6561514195583596, 'f1-score': 0.6688102893890675, 'support': 317.0} | {'precision': 0.8853503184713376, 'recall': 0.896774193548387, 'f1-score': 0.8910256410256411, 'support': 155.0}   | {'precision': 0.8817204301075269, 'recall': 0.8967193195625759, 'f1-score': 0.8891566265060241, 'support': 823.0} | {'precision': 0.6920813924981614, 'recall': 0.6498618784530387, 'f1-score': 0.6703074913926155, 'support': 4344.0}  | {'precision': 0.8773408239700374, 'recall': 0.8864711447492905, 'f1-score': 0.8818823529411765, 'support': 2114.0}  | {'precision': 0.9018829810259, 'recall': 0.9187183067538767, 'f1-score': 0.9102228047182176, 'support': 13607.0}    | {'precision': 0.9999095513748191, 'recall': 0.9985547827657845, 'f1-score': 0.9992317078682154, 'support': 11071.0} | 0.9046   | {'precision': 0.8457503872232196, 'recall': 0.8433215779130447, 'f1-score': 0.8443767019772797, 'support': 32431.0} | {'precision': 0.9029042970267227, 'recall': 0.9046282877493756, 'f1-score': 0.9036387628518002, 'support': 32431.0} |
 ### Framework versions

       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
 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
 ### 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

meta_data/meta_s42_e16_cvi3.json CHANGED Viewed

@@ -1 +1 @@

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