trainer: training complete at 2024-04-23 13:44:47.084513.

README.md

@@ -17,12 +17,12 @@ model-index:
       name: essays_su_g
       type: essays_su_g
       config: simple
-      split: train[80%:100%]
+      split: train[0%:20%]
       args: simple
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8590463087005322
+      value: 0.8399468193904684
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,14 +32,14 @@ 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: 1.1263
-- Claim: {'precision': 0.6273854961832062, 'recall': 0.6309980806142035, 'f1-score': 0.6291866028708135, 'support': 4168.0}
-- Majorclaim: {'precision': 0.8152077807250221, 'recall': 0.8568773234200744, 'f1-score': 0.8355233348436791, 'support': 2152.0}
-- O: {'precision': 0.9466531895777179, 'recall': 0.9136137004118795, 'f1-score': 0.9298400441257586, 'support': 9226.0}
-- Premise: {'precision': 0.8827175597422723, 'recall': 0.8964631823076286, 'f1-score': 0.889537272951426, 'support': 12073.0}
-- Accuracy: 0.8590
-- Macro avg: {'precision': 0.8179910065570546, 'recall': 0.8244880716884464, 'f1-score': 0.8210218136979194, 'support': 27619.0}
-- Weighted avg: {'precision': 0.8602824620016775, 'recall': 0.8590463087005322, 'f1-score': 0.8595019269631762, 'support': 27619.0}
+- Loss: 1.0670
+- Claim: {'precision': 0.5894120517199317, 'recall': 0.5668700140778977, 'f1-score': 0.5779213012797513, 'support': 4262.0}
+- Majorclaim: {'precision': 0.7822390174775626, 'recall': 0.7648960739030023, 'f1-score': 0.7734703409621673, 'support': 2165.0}
+- O: {'precision': 0.9166666666666666, 'recall': 0.882853668423186, 'f1-score': 0.8994424943217014, 'support': 9868.0}
+- Premise: {'precision': 0.8707947700896136, 'recall': 0.9091954904517218, 'f1-score': 0.889580910216486, 'support': 13039.0}
+- Accuracy: 0.8399
+- Macro avg: {'precision': 0.7897781264884436, 'recall': 0.780953811713952, 'f1-score': 0.7851037616950265, 'support': 29334.0}
+- Weighted avg: {'precision': 0.8388075717984049, 'recall': 0.8399468193904684, 'f1-score': 0.8390471090378641, 'support': 29334.0}
 
 ## Model description
 
@@ -64,62 +64,32 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 50
+- num_epochs: 20
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Claim                                                                                                                | Majorclaim                                                                                                         | O                                                                                                                  | Premise                                                                                                             | Accuracy | Macro avg                                                                                                           | Weighted avg                                                                                                        |
-|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:--------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
-| No log        | 1.0   | 81   | 0.5105          | {'precision': 0.5640703517587939, 'recall': 0.32317658349328215, 'f1-score': 0.41092129347162903, 'support': 4168.0} | {'precision': 0.5929304446978335, 'recall': 0.724907063197026, 'f1-score': 0.6523102655237298, 'support': 2152.0}  | {'precision': 0.8545380875202593, 'recall': 0.9143724257533059, 'f1-score': 0.8834432924913603, 'support': 9226.0} | {'precision': 0.8441231929604023, 'recall': 0.8899196554294707, 'f1-score': 0.8664166767469054, 'support': 12073.0} | 0.7997   | {'precision': 0.7139155192343223, 'recall': 0.7130939319682712, 'f1-score': 0.7032728820584061, 'support': 27619.0} | {'precision': 0.7857670171690952, 'recall': 0.7997031029363844, 'f1-score': 0.7866826459135919, 'support': 27619.0} |
-| No log        | 2.0   | 162  | 0.4469          | {'precision': 0.5678977272727272, 'recall': 0.47960652591170827, 'f1-score': 0.5200312174817897, 'support': 4168.0}  | {'precision': 0.7948320413436692, 'recall': 0.7146840148698885, 'f1-score': 0.7526302911671151, 'support': 2152.0} | {'precision': 0.944560669456067, 'recall': 0.8808801213960546, 'f1-score': 0.9116096466629278, 'support': 9226.0}  | {'precision': 0.8259587020648967, 'recall': 0.9276898865236478, 'f1-score': 0.8738735224125151, 'support': 12073.0} | 0.8278   | {'precision': 0.7833122850343401, 'recall': 0.7507151371753248, 'f1-score': 0.7645361694310869, 'support': 27619.0} | {'precision': 0.8242076985653165, 'recall': 0.8278359100619139, 'f1-score': 0.8236335905447046, 'support': 27619.0} |
-| No log        | 3.0   | 243  | 0.4093          | {'precision': 0.5744204961366409, 'recall': 0.6777831094049904, 'f1-score': 0.6218357913273168, 'support': 4168.0}   | {'precision': 0.7360824742268042, 'recall': 0.8294609665427509, 'f1-score': 0.7799868909766223, 'support': 2152.0} | {'precision': 0.9330596419204014, 'recall': 0.8868415347929763, 'f1-score': 0.9093637121422617, 'support': 9226.0} | {'precision': 0.89797514556357, 'recall': 0.855876749772219, 'f1-score': 0.876420695504665, 'support': 12073.0}     | 0.8373   | {'precision': 0.7853844394618541, 'recall': 0.8124905901282342, 'f1-score': 0.7969017724877165, 'support': 27619.0} | {'precision': 0.8482528803063183, 'recall': 0.8372859263550454, 'f1-score': 0.8414917278933443, 'support': 27619.0} |
-| No log        | 4.0   | 324  | 0.5161          | {'precision': 0.516112873601603, 'recall': 0.7416026871401151, 'f1-score': 0.608644284729743, 'support': 4168.0}     | {'precision': 0.7790381125226861, 'recall': 0.7978624535315985, 'f1-score': 0.788337924701561, 'support': 2152.0}  | {'precision': 0.9442684500762643, 'recall': 0.8723173639713853, 'f1-score': 0.9068679925629612, 'support': 9226.0} | {'precision': 0.8985600293497202, 'recall': 0.8114801623457302, 'f1-score': 0.8528029247910863, 'support': 12073.0} | 0.8202   | {'precision': 0.7844948663875684, 'recall': 0.8058156667472073, 'f1-score': 0.789163281696338, 'support': 27619.0}  | {'precision': 0.8468005514342695, 'recall': 0.8201962417176581, 'f1-score': 0.8289940404467937, 'support': 27619.0} |
-| No log        | 5.0   | 405  | 0.5154          | {'precision': 0.5811590856615101, 'recall': 0.6038867562380038, 'f1-score': 0.5923049770561243, 'support': 4168.0}   | {'precision': 0.8014598540145985, 'recall': 0.7653345724907064, 'f1-score': 0.7829807463750891, 'support': 2152.0} | {'precision': 0.9311288483466362, 'recall': 0.8851073054411446, 'f1-score': 0.9075350077795066, 'support': 9226.0} | {'precision': 0.8633555323758325, 'recall': 0.891244926695933, 'f1-score': 0.8770785784153896, 'support': 12073.0}  | 0.8360   | {'precision': 0.7942758300996444, 'recall': 0.7863933902164468, 'f1-score': 0.7899748274065275, 'support': 27619.0} | {'precision': 0.8385857117236715, 'recall': 0.8360186827908324, 'f1-score': 0.8369451960444566, 'support': 27619.0} |
-| No log        | 6.0   | 486  | 0.5418          | {'precision': 0.6108374384236454, 'recall': 0.5057581573896354, 'f1-score': 0.5533534584591154, 'support': 4168.0}   | {'precision': 0.8107317073170732, 'recall': 0.7723048327137546, 'f1-score': 0.7910518800571156, 'support': 2152.0} | {'precision': 0.919331636605068, 'recall': 0.9004985909386516, 'f1-score': 0.909817664129661, 'support': 9226.0}   | {'precision': 0.8410671966975002, 'recall': 0.9112896546011762, 'f1-score': 0.8747714081259442, 'support': 12073.0} | 0.8357   | {'precision': 0.7954919947608217, 'recall': 0.7724628089108043, 'f1-score': 0.782248602692959, 'support': 27619.0}  | {'precision': 0.8301032992701898, 'recall': 0.8356566132010572, 'f1-score': 0.8314498656832355, 'support': 27619.0} |
-| 0.345         | 7.0   | 567  | 0.5832          | {'precision': 0.6017184735911044, 'recall': 0.571257197696737, 'f1-score': 0.5860923076923077, 'support': 4168.0}    | {'precision': 0.8264023210831721, 'recall': 0.7941449814126395, 'f1-score': 0.8099526066350711, 'support': 2152.0} | {'precision': 0.9157418381639909, 'recall': 0.9212009538261435, 'f1-score': 0.9184632841627491, 'support': 9226.0} | {'precision': 0.8666450093397222, 'recall': 0.8838731052762362, 'f1-score': 0.8751742803247764, 'support': 12073.0} | 0.8422   | {'precision': 0.8026269105444974, 'recall': 0.792619059552939, 'f1-score': 0.7974206197037261, 'support': 27619.0}  | {'precision': 0.8399297508801243, 'recall': 0.84217386581701, 'f1-score': 0.8409273360363069, 'support': 27619.0}   |
-| 0.345         | 8.0   | 648  | 0.5916          | {'precision': 0.6281560826319816, 'recall': 0.5909309021113244, 'f1-score': 0.6089751514402275, 'support': 4168.0}   | {'precision': 0.806993006993007, 'recall': 0.804368029739777, 'f1-score': 0.8056783802653014, 'support': 2152.0}   | {'precision': 0.9243136825987094, 'recall': 0.9159982657706481, 'f1-score': 0.9201371876531113, 'support': 9226.0} | {'precision': 0.8721998388396455, 'recall': 0.8965460117617825, 'f1-score': 0.8842053669893396, 'support': 12073.0} | 0.8497   | {'precision': 0.8079156527658359, 'recall': 0.801960802345883, 'f1-score': 0.8047490215869949, 'support': 27619.0}  | {'precision': 0.8476986926907486, 'recall': 0.8497411202433107, 'f1-score': 0.8485544514458778, 'support': 27619.0} |
-| 0.345         | 9.0   | 729  | 0.6681          | {'precision': 0.5974557019536574, 'recall': 0.6309980806142035, 'f1-score': 0.6137689614935823, 'support': 4168.0}   | {'precision': 0.761437908496732, 'recall': 0.8661710037174721, 'f1-score': 0.8104347826086956, 'support': 2152.0}  | {'precision': 0.9265518003092555, 'recall': 0.9092781270323, 'f1-score': 0.9178336980306346, 'support': 9226.0}    | {'precision': 0.8886043533930857, 'recall': 0.8622546177420691, 'f1-score': 0.8752312090129477, 'support': 12073.0} | 0.8434   | {'precision': 0.7935124410381827, 'recall': 0.8171754572765112, 'f1-score': 0.804317162786465, 'support': 27619.0}  | {'precision': 0.8474346288061019, 'recall': 0.8433686954632681, 'f1-score': 0.8449561811840803, 'support': 27619.0} |
-| 0.345         | 10.0  | 810  | 0.7243          | {'precision': 0.5741487455197133, 'recall': 0.6149232245681382, 'f1-score': 0.5938368860055606, 'support': 4168.0}   | {'precision': 0.8037466547725245, 'recall': 0.837360594795539, 'f1-score': 0.8202093764223942, 'support': 2152.0}  | {'precision': 0.9286033519553073, 'recall': 0.9008237589421201, 'f1-score': 0.9145026408450704, 'support': 9226.0} | {'precision': 0.8756164841594918, 'recall': 0.8676385322620724, 'f1-score': 0.8716092527874855, 'support': 12073.0} | 0.8382   | {'precision': 0.7955288091017592, 'recall': 0.8051865276419675, 'f1-score': 0.8000395390151277, 'support': 27619.0} | {'precision': 0.8422219164630815, 'recall': 0.8382273072884608, 'f1-score': 0.840013852502701, 'support': 27619.0}  |
-| 0.345         | 11.0  | 891  | 0.7493          | {'precision': 0.5898203592814372, 'recall': 0.614443378119002, 'f1-score': 0.6018801410105759, 'support': 4168.0}    | {'precision': 0.8243443839683325, 'recall': 0.7741635687732342, 'f1-score': 0.7984663311766117, 'support': 2152.0} | {'precision': 0.9334944195144402, 'recall': 0.8793626707132018, 'f1-score': 0.9056203605514316, 'support': 9226.0} | {'precision': 0.8616792678074016, 'recall': 0.8967945001242442, 'f1-score': 0.878886273236464, 'support': 12073.0}  | 0.8388   | {'precision': 0.8023346076429029, 'recall': 0.7911910294324205, 'f1-score': 0.7962132764937708, 'support': 27619.0} | {'precision': 0.8417333606018996, 'recall': 0.838806618632101, 'f1-score': 0.8397473983726959, 'support': 27619.0}  |
-| 0.345         | 12.0  | 972  | 0.7472          | {'precision': 0.5856969205834684, 'recall': 0.6936180422264875, 'f1-score': 0.6351054481546573, 'support': 4168.0}   | {'precision': 0.7993659420289855, 'recall': 0.8201672862453532, 'f1-score': 0.8096330275229358, 'support': 2152.0} | {'precision': 0.9461520684076727, 'recall': 0.8874918707999133, 'f1-score': 0.9158836689038031, 'support': 9226.0} | {'precision': 0.8926486760849336, 'recall': 0.8740164002319225, 'f1-score': 0.8832342847576798, 'support': 12073.0} | 0.8471   | {'precision': 0.8059659017762651, 'recall': 0.8188233998759191, 'f1-score': 0.810964107334769, 'support': 27619.0}  | {'precision': 0.8569306173916821, 'recall': 0.8470980122379521, 'f1-score': 0.8509605717920246, 'support': 27619.0} |
-| 0.0604        | 13.0  | 1053 | 0.8128          | {'precision': 0.5960222412318221, 'recall': 0.6686660268714012, 'f1-score': 0.6302578018995931, 'support': 4168.0}   | {'precision': 0.8172757475083057, 'recall': 0.800185873605948, 'f1-score': 0.8086405259450574, 'support': 2152.0}  | {'precision': 0.9477475417333638, 'recall': 0.8984391935833514, 'f1-score': 0.9224348987313599, 'support': 9226.0} | {'precision': 0.8838709677419355, 'recall': 0.8851155470885447, 'f1-score': 0.8844928196002152, 'support': 12073.0} | 0.8503   | {'precision': 0.8112291245538568, 'recall': 0.8131016602873112, 'f1-score': 0.8114565115440564, 'support': 27619.0} | {'precision': 0.8565802934093382, 'recall': 0.8502842246279735, 'f1-score': 0.8528902247322565, 'support': 27619.0} |
-| 0.0604        | 14.0  | 1134 | 0.8995          | {'precision': 0.6241429970617042, 'recall': 0.6115642994241842, 'f1-score': 0.6177896267571498, 'support': 4168.0}   | {'precision': 0.7095697329376854, 'recall': 0.8889405204460966, 'f1-score': 0.7891914191419142, 'support': 2152.0} | {'precision': 0.9549846806504831, 'recall': 0.8783871667027965, 'f1-score': 0.915085817524842, 'support': 9226.0}  | {'precision': 0.8733101270946328, 'recall': 0.8935641514122422, 'f1-score': 0.8833210513387375, 'support': 12073.0} | 0.8456   | {'precision': 0.7905018844361265, 'recall': 0.8181140344963299, 'f1-score': 0.8013469786906608, 'support': 27619.0} | {'precision': 0.850232952139105, 'recall': 0.8455773199608965, 'f1-score': 0.8465260836240982, 'support': 27619.0}  |
-| 0.0604        | 15.0  | 1215 | 0.9128          | {'precision': 0.5816304108987036, 'recall': 0.6350767754318618, 'f1-score': 0.6071797224452345, 'support': 4168.0}   | {'precision': 0.7725922783198982, 'recall': 0.8461895910780669, 'f1-score': 0.8077178975382568, 'support': 2152.0} | {'precision': 0.9512505789717461, 'recall': 0.8904183828311294, 'f1-score': 0.9198298062926884, 'support': 9226.0} | {'precision': 0.8719668737060041, 'recall': 0.8721113227863828, 'f1-score': 0.8720390922643698, 'support': 12073.0} | 0.8404   | {'precision': 0.794360035474088, 'recall': 0.8109490180318603, 'f1-score': 0.8016916296351374, 'support': 27619.0}  | {'precision': 0.8468933720777774, 'recall': 0.8404359317860893, 'f1-score': 0.8430215341764057, 'support': 27619.0} |
-| 0.0604        | 16.0  | 1296 | 0.8803          | {'precision': 0.6304191616766467, 'recall': 0.6314779270633397, 'f1-score': 0.6309481002037637, 'support': 4168.0}   | {'precision': 0.8195592286501377, 'recall': 0.8294609665427509, 'f1-score': 0.8244803695150116, 'support': 2152.0} | {'precision': 0.9101446193109315, 'recall': 0.9277043138955127, 'f1-score': 0.9188405797101449, 'support': 9226.0} | {'precision': 0.8933569381217332, 'recall': 0.8777437256688478, 'f1-score': 0.8854815124294965, 'support': 12073.0} | 0.8535   | {'precision': 0.8133699869398623, 'recall': 0.8165967332926127, 'f1-score': 0.8149376404646043, 'support': 27619.0} | {'precision': 0.8535345630772185, 'recall': 0.8535066439769724, 'f1-score': 0.8534601153123827, 'support': 27619.0} |
-| 0.0604        | 17.0  | 1377 | 0.8617          | {'precision': 0.6221813161527842, 'recall': 0.6487523992322457, 'f1-score': 0.6351891003053795, 'support': 4168.0}   | {'precision': 0.7972493345164152, 'recall': 0.8350371747211895, 'f1-score': 0.8157058556513844, 'support': 2152.0} | {'precision': 0.9221517603323858, 'recall': 0.914155647084327, 'f1-score': 0.9181362943609842, 'support': 9226.0}  | {'precision': 0.8921923692411353, 'recall': 0.8774124078522323, 'f1-score': 0.8847406664996242, 'support': 12073.0} | 0.8519   | {'precision': 0.8084436950606801, 'recall': 0.8188394072224987, 'f1-score': 0.813442979204343, 'support': 27619.0}  | {'precision': 0.8540549226358285, 'recall': 0.8518773308229842, 'f1-score': 0.8528573333523664, 'support': 27619.0} |
-| 0.0604        | 18.0  | 1458 | 0.9965          | {'precision': 0.6335570469798658, 'recall': 0.5662188099808061, 'f1-score': 0.5979982262764474, 'support': 4168.0}   | {'precision': 0.8203703703703704, 'recall': 0.8234200743494424, 'f1-score': 0.8218923933209649, 'support': 2152.0} | {'precision': 0.9406885581183957, 'recall': 0.8973553002384566, 'f1-score': 0.9185111222055806, 'support': 9226.0} | {'precision': 0.8547127503286167, 'recall': 0.9155967862171789, 'f1-score': 0.8841078141246101, 'support': 12073.0} | 0.8496   | {'precision': 0.8123321814493122, 'recall': 0.800647742696471, 'f1-score': 0.8056273889819007, 'support': 27619.0}  | {'precision': 0.8473819646173586, 'recall': 0.8495962924074008, 'f1-score': 0.8475754477331567, 'support': 27619.0} |
-| 0.0201        | 19.0  | 1539 | 0.9760          | {'precision': 0.5662385321100918, 'recall': 0.7404030710172744, 'f1-score': 0.6417134539405281, 'support': 4168.0}   | {'precision': 0.8062157221206582, 'recall': 0.8197026022304833, 'f1-score': 0.8129032258064516, 'support': 2152.0} | {'precision': 0.9517297802711547, 'recall': 0.8826143507478864, 'f1-score': 0.9158699808795411, 'support': 9226.0} | {'precision': 0.8939168490153173, 'recall': 0.8459372152737513, 'f1-score': 0.8692654694016513, 'support': 12073.0} | 0.8402   | {'precision': 0.8045252208793054, 'recall': 0.8221643098173489, 'f1-score': 0.809938032507043, 'support': 27619.0}  | {'precision': 0.8569454182549012, 'recall': 0.8402186900322242, 'f1-score': 0.8461018818074655, 'support': 27619.0} |
-| 0.0201        | 20.0  | 1620 | 1.0000          | {'precision': 0.6002422774076317, 'recall': 0.7132917466410749, 'f1-score': 0.651902203705734, 'support': 4168.0}    | {'precision': 0.8425531914893617, 'recall': 0.8280669144981413, 'f1-score': 0.8352472463088821, 'support': 2152.0} | {'precision': 0.9323666150099623, 'recall': 0.9129633644049425, 'f1-score': 0.9225629791894853, 'support': 9226.0} | {'precision': 0.8987583572110793, 'recall': 0.8573676799469891, 'f1-score': 0.8775752437473505, 'support': 12073.0} | 0.8519   | {'precision': 0.8184801102795087, 'recall': 0.8279224263727869, 'f1-score': 0.821821918237863, 'support': 27619.0}  | {'precision': 0.8605564400235849, 'recall': 0.8519135377819617, 'f1-score': 0.8552486484979966, 'support': 27619.0} |
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-| 0.0039        | 41.0  | 3321 | 1.1615          | {'precision': 0.5966553852279515, 'recall': 0.7190499040307101, 'f1-score': 0.6521597214666522, 'support': 4168.0}   | {'precision': 0.8222222222222222, 'recall': 0.8252788104089219, 'f1-score': 0.823747680890538, 'support': 2152.0}  | {'precision': 0.9584831265220921, 'recall': 0.8958378495556037, 'f1-score': 0.9261023026500084, 'support': 9226.0} | {'precision': 0.8921527131126725, 'recall': 0.8729396173279218, 'f1-score': 0.8824415975885456, 'support': 12073.0} | 0.8537   | {'precision': 0.8173783617712345, 'recall': 0.8282765453307894, 'f1-score': 0.821112825648936, 'support': 27619.0}  | {'precision': 0.8642676019607676, 'recall': 0.8536514718128825, 'f1-score': 0.857701002218941, 'support': 27619.0}  |
-| 0.0039        | 42.0  | 3402 | 1.1097          | {'precision': 0.6225523295070898, 'recall': 0.6636276391554703, 'f1-score': 0.6424340959238184, 'support': 4168.0}   | {'precision': 0.8328716528162512, 'recall': 0.8382899628252788, 'f1-score': 0.8355720240852247, 'support': 2152.0} | {'precision': 0.9516516173276945, 'recall': 0.9024495989594624, 'f1-score': 0.9263977746870653, 'support': 9226.0} | {'precision': 0.8826360003262377, 'recall': 0.8963803528534747, 'f1-score': 0.889455083422372, 'support': 12073.0}  | 0.8588   | {'precision': 0.8224278999943182, 'recall': 0.8251868884484215, 'f1-score': 0.8234647445296202, 'support': 27619.0} | {'precision': 0.8625634584760528, 'recall': 0.8587566530287121, 'f1-score': 0.860319106378328, 'support': 27619.0}  |
-| 0.0039        | 43.0  | 3483 | 1.1389          | {'precision': 0.6155963302752293, 'recall': 0.6439539347408829, 'f1-score': 0.6294559099437148, 'support': 4168.0}   | {'precision': 0.8046532045654082, 'recall': 0.8517657992565055, 'f1-score': 0.8275395033860045, 'support': 2152.0} | {'precision': 0.9582417582417583, 'recall': 0.897897246910904, 'f1-score': 0.9270885792624923, 'support': 9226.0}  | {'precision': 0.8781614785992218, 'recall': 0.8972914768491675, 'f1-score': 0.8876234175918718, 'support': 12073.0} | 0.8557   | {'precision': 0.8141631929204045, 'recall': 0.8227271144393651, 'f1-score': 0.8179268525460208, 'support': 27619.0} | {'precision': 0.8595604907302502, 'recall': 0.8557152684746008, 'f1-score': 0.8571647777542455, 'support': 27619.0} |
-| 0.0026        | 44.0  | 3564 | 1.1342          | {'precision': 0.6240409207161125, 'recall': 0.6439539347408829, 'f1-score': 0.6338410674223639, 'support': 4168.0}   | {'precision': 0.799826313504125, 'recall': 0.8559479553903345, 'f1-score': 0.8269360269360269, 'support': 2152.0}  | {'precision': 0.9584583429494576, 'recall': 0.9002818122696726, 'f1-score': 0.9284596467695059, 'support': 9226.0} | {'precision': 0.8793424568790995, 'recall': 0.8994450426571688, 'f1-score': 0.8892801572352798, 'support': 12073.0} | 0.8578   | {'precision': 0.8154170085121986, 'recall': 0.8249071862645148, 'f1-score': 0.819629224590794, 'support': 27619.0}  | {'precision': 0.861047356463257, 'recall': 0.8577790651363192, 'f1-score': 0.8589617270132784, 'support': 27619.0}  |
-| 0.0026        | 45.0  | 3645 | 1.1367          | {'precision': 0.6169934640522876, 'recall': 0.6794625719769674, 'f1-score': 0.6467229961178351, 'support': 4168.0}   | {'precision': 0.812694185530404, 'recall': 0.8508364312267658, 'f1-score': 0.831328036322361, 'support': 2152.0}   | {'precision': 0.9527514014414826, 'recall': 0.9026663776284414, 'f1-score': 0.927032893638337, 'support': 9226.0}  | {'precision': 0.8909846281678437, 'recall': 0.8881802368922389, 'f1-score': 0.8895802223328355, 'support': 12073.0} | 0.8586   | {'precision': 0.8183559197980044, 'recall': 0.8302864044311034, 'f1-score': 0.8236660371028421, 'support': 27619.0} | {'precision': 0.864169176689991, 'recall': 0.8586118251928021, 'f1-score': 0.8609025266271941, 'support': 27619.0}  |
-| 0.0026        | 46.0  | 3726 | 1.1422          | {'precision': 0.6169026169026169, 'recall': 0.6900191938579654, 'f1-score': 0.6514156285390714, 'support': 4168.0}   | {'precision': 0.8026828212894851, 'recall': 0.8619888475836431, 'f1-score': 0.8312794084696392, 'support': 2152.0} | {'precision': 0.9538074548364966, 'recall': 0.9041838283112942, 'f1-score': 0.9283329623859337, 'support': 9226.0} | {'precision': 0.8952941176470588, 'recall': 0.8824650045556199, 'f1-score': 0.8888332707629416, 'support': 12073.0} | 0.8591   | {'precision': 0.8171717526689144, 'recall': 0.8346642185771307, 'f1-score': 0.8249653175393965, 'support': 27619.0} | {'precision': 0.8656119699967246, 'recall': 0.8590825156595098, 'f1-score': 0.8617146752478776, 'support': 27619.0} |
-| 0.0026        | 47.0  | 3807 | 1.1345          | {'precision': 0.6162966156499246, 'recall': 0.6859404990403071, 'f1-score': 0.6492562734188714, 'support': 4168.0}   | {'precision': 0.8003449762828806, 'recall': 0.862453531598513, 'f1-score': 0.8302393200626258, 'support': 2152.0}  | {'precision': 0.9542955326460482, 'recall': 0.9029915456319099, 'f1-score': 0.927934952105146, 'support': 9226.0}  | {'precision': 0.8938060514625765, 'recall': 0.8832932990971589, 'f1-score': 0.8885185802366272, 'support': 12073.0} | 0.8585   | {'precision': 0.8161857940103575, 'recall': 0.8336697188419722, 'f1-score': 0.8239872814558176, 'support': 27619.0} | {'precision': 0.8648509260469159, 'recall': 0.858466997356892, 'f1-score': 0.8610372515914226, 'support': 27619.0}  |
-| 0.0026        | 48.0  | 3888 | 1.1346          | {'precision': 0.6188230008984726, 'recall': 0.6609884836852208, 'f1-score': 0.6392111368909513, 'support': 4168.0}   | {'precision': 0.8088363954505686, 'recall': 0.8592007434944238, 'f1-score': 0.8332582244254167, 'support': 2152.0} | {'precision': 0.9490855723639647, 'recall': 0.9112291350531108, 'f1-score': 0.9297721742977217, 'support': 9226.0} | {'precision': 0.8901272560924894, 'recall': 0.886440818355007, 'f1-score': 0.8882802124833998, 'support': 12073.0}  | 0.8586   | {'precision': 0.8167180562013739, 'recall': 0.8294647951469407, 'f1-score': 0.8226304370243724, 'support': 27619.0} | {'precision': 0.8625453508160694, 'recall': 0.8585756182338246, 'f1-score': 0.8602660778054183, 'support': 27619.0} |
-| 0.0026        | 49.0  | 3969 | 1.1303          | {'precision': 0.6245327102803738, 'recall': 0.6413147792706334, 'f1-score': 0.6328125, 'support': 4168.0}            | {'precision': 0.810989010989011, 'recall': 0.8573420074349443, 'f1-score': 0.8335215721707703, 'support': 2152.0}  | {'precision': 0.9477242000901307, 'recall': 0.9117710817255582, 'f1-score': 0.9294000662910176, 'support': 9226.0} | {'precision': 0.8852149655398753, 'recall': 0.893646980866396, 'f1-score': 0.8894109888298091, 'support': 12073.0}  | 0.8588   | {'precision': 0.8171152217248476, 'recall': 0.826018712324383, 'f1-score': 0.8212862818228992, 'support': 27619.0}  | {'precision': 0.8609726795717226, 'recall': 0.8587928599876896, 'f1-score': 0.8596909664743367, 'support': 27619.0} |
-| 0.0024        | 50.0  | 4050 | 1.1263          | {'precision': 0.6273854961832062, 'recall': 0.6309980806142035, 'f1-score': 0.6291866028708135, 'support': 4168.0}   | {'precision': 0.8152077807250221, 'recall': 0.8568773234200744, 'f1-score': 0.8355233348436791, 'support': 2152.0} | {'precision': 0.9466531895777179, 'recall': 0.9136137004118795, 'f1-score': 0.9298400441257586, 'support': 9226.0} | {'precision': 0.8827175597422723, 'recall': 0.8964631823076286, 'f1-score': 0.889537272951426, 'support': 12073.0}  | 0.8590   | {'precision': 0.8179910065570546, 'recall': 0.8244880716884464, 'f1-score': 0.8210218136979194, 'support': 27619.0} | {'precision': 0.8602824620016775, 'recall': 0.8590463087005322, 'f1-score': 0.8595019269631762, 'support': 27619.0} |
+| Training Loss | Epoch | Step | Validation Loss | Claim                                                                                                               | Majorclaim                                                                                                          | O                                                                                                                  | Premise                                                                                                             | Accuracy | Macro avg                                                                                                           | Weighted avg                                                                                                        |
+|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:--------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
+| No log        | 1.0   | 81   | 0.5489          | {'precision': 0.43257049448304047, 'recall': 0.496715157203191, 'f1-score': 0.46242900830056793, 'support': 4262.0} | {'precision': 0.6522533495736906, 'recall': 0.49468822170900695, 'f1-score': 0.5626477541371159, 'support': 2165.0} | {'precision': 0.911293908403735, 'recall': 0.8307661126874747, 'f1-score': 0.8691687871077185, 'support': 9868.0}  | {'precision': 0.8377046804810897, 'recall': 0.88672444205844, 'f1-score': 0.8615178272046495, 'support': 13039.0}   | 0.7823   | {'precision': 0.708455608235389, 'recall': 0.6772234834145282, 'f1-score': 0.6889408441875129, 'support': 29334.0}  | {'precision': 0.7899101236188295, 'recall': 0.7823004022635849, 'f1-score': 0.7840489998358311, 'support': 29334.0} |
+| No log        | 2.0   | 162  | 0.5075          | {'precision': 0.5107383923092657, 'recall': 0.5858751759737213, 'f1-score': 0.5457327068079991, 'support': 4262.0}  | {'precision': 0.5687340153452686, 'recall': 0.8217090069284064, 'f1-score': 0.6722085773663329, 'support': 2165.0}  | {'precision': 0.9344863131370977, 'recall': 0.8268139440616133, 'f1-score': 0.8773589977955805, 'support': 9868.0} | {'precision': 0.8834419195931988, 'recall': 0.852749443975765, 'f1-score': 0.8678243902439025, 'support': 13039.0}  | 0.8030   | {'precision': 0.7243501600962077, 'recall': 0.7717868927348766, 'f1-score': 0.7407811680534537, 'support': 29334.0} | {'precision': 0.8232353684753937, 'recall': 0.8029590236585532, 'f1-score': 0.8097969994222006, 'support': 29334.0} |
+| No log        | 3.0   | 243  | 0.5219          | {'precision': 0.5516552511415526, 'recall': 0.45354293758798686, 'f1-score': 0.4978109708987896, 'support': 4262.0} | {'precision': 0.8036105032822757, 'recall': 0.6785219399538106, 'f1-score': 0.7357876283496118, 'support': 2165.0}  | {'precision': 0.9331699710403207, 'recall': 0.8490068909606809, 'f1-score': 0.8891011355194736, 'support': 9868.0} | {'precision': 0.8191560170394037, 'recall': 0.9438607255157604, 'f1-score': 0.8770979581655561, 'support': 13039.0} | 0.8211   | {'precision': 0.7768979356258882, 'recall': 0.7312331235045597, 'f1-score': 0.7499494232333578, 'support': 29334.0} | {'precision': 0.8174973750724106, 'recall': 0.821129065248517, 'f1-score': 0.815598992812927, 'support': 29334.0}   |
+| No log        | 4.0   | 324  | 0.4725          | {'precision': 0.5851569933396765, 'recall': 0.5771938057250118, 'f1-score': 0.5811481218993623, 'support': 4262.0}  | {'precision': 0.7335329341317365, 'recall': 0.792147806004619, 'f1-score': 0.761714412613813, 'support': 2165.0}    | {'precision': 0.9085720215857203, 'recall': 0.8872111876773409, 'f1-score': 0.8977645611156685, 'support': 9868.0} | {'precision': 0.8851474612344178, 'recall': 0.8930899608865711, 'f1-score': 0.8891009734682191, 'support': 13039.0} | 0.8378   | {'precision': 0.7781023525728877, 'recall': 0.7874106900733857, 'f1-score': 0.7824320172742658, 'support': 29334.0} | {'precision': 0.8382513248807655, 'recall': 0.8377650507943001, 'f1-score': 0.8378705011585708, 'support': 29334.0} |
+| No log        | 5.0   | 405  | 0.5539          | {'precision': 0.5784176029962547, 'recall': 0.5797747536367902, 'f1-score': 0.5790953831731895, 'support': 4262.0}  | {'precision': 0.8008497079129049, 'recall': 0.6965357967667436, 'f1-score': 0.7450592885375493, 'support': 2165.0}  | {'precision': 0.9040794979079498, 'recall': 0.8758613700851237, 'f1-score': 0.8897467572575665, 'support': 9868.0} | {'precision': 0.8672442910639547, 'recall': 0.905820998542833, 'f1-score': 0.8861129867206842, 'support': 13039.0}  | 0.8329   | {'precision': 0.787647774970266, 'recall': 0.7644982297578727, 'f1-score': 0.7750036039222473, 'support': 29334.0}  | {'precision': 0.8327711951367025, 'recall': 0.8329242517215518, 'f1-score': 0.8323176558681596, 'support': 29334.0} |
+| No log        | 6.0   | 486  | 0.5790          | {'precision': 0.5325670498084292, 'recall': 0.6848897231346786, 'f1-score': 0.5991994252283692, 'support': 4262.0}  | {'precision': 0.7400087834870444, 'recall': 0.7782909930715936, 'f1-score': 0.7586672669968483, 'support': 2165.0}  | {'precision': 0.9212211784799317, 'recall': 0.8745439805431698, 'f1-score': 0.8972759409440632, 'support': 9868.0} | {'precision': 0.9062909567496723, 'recall': 0.8485313290896541, 'f1-score': 0.8764605695726225, 'support': 13039.0} | 0.8283   | {'precision': 0.7750219921312693, 'recall': 0.796564006459774, 'f1-score': 0.7829008006854759, 'support': 29334.0}  | {'precision': 0.8447418748493872, 'recall': 0.8283220835890094, 'f1-score': 0.8344852708551485, 'support': 29334.0} |
+| 0.3561        | 7.0   | 567  | 0.7058          | {'precision': 0.5955997904662127, 'recall': 0.5335523228531206, 'f1-score': 0.5628712871287128, 'support': 4262.0}  | {'precision': 0.8422198041349293, 'recall': 0.7150115473441109, 'f1-score': 0.7734199350487135, 'support': 2165.0}  | {'precision': 0.9193378321383383, 'recall': 0.8835630320226996, 'f1-score': 0.9010954940057875, 'support': 9868.0} | {'precision': 0.848316189939411, 'recall': 0.9234603880665695, 'f1-score': 0.8842947894099071, 'support': 13039.0}  | 0.8380   | {'precision': 0.8013684041697228, 'recall': 0.7638968225716252, 'f1-score': 0.7804203763982802, 'support': 29334.0} | {'precision': 0.8350403187795808, 'recall': 0.838003681734506, 'f1-score': 0.835063123988816, 'support': 29334.0}   |
+| 0.3561        | 8.0   | 648  | 0.6876          | {'precision': 0.5858841386288894, 'recall': 0.5434068512435476, 'f1-score': 0.5638466220328667, 'support': 4262.0}  | {'precision': 0.8025641025641026, 'recall': 0.7228637413394919, 'f1-score': 0.7606318347509112, 'support': 2165.0}  | {'precision': 0.8864763037874281, 'recall': 0.9060599918929875, 'f1-score': 0.896161170692593, 'support': 9868.0}  | {'precision': 0.8807043836642937, 'recall': 0.9013728046629342, 'f1-score': 0.8909187386294724, 'support': 13039.0} | 0.8378   | {'precision': 0.7889072321611785, 'recall': 0.7684258472847404, 'f1-score': 0.7778895915264609, 'support': 29334.0} | {'precision': 0.8340438435010799, 'recall': 0.8377650507943001, 'f1-score': 0.8355454452418354, 'support': 29334.0} |
+| 0.3561        | 9.0   | 729  | 0.6963          | {'precision': 0.5602836879432624, 'recall': 0.6302205537306429, 'f1-score': 0.5931978798586572, 'support': 4262.0}  | {'precision': 0.8248823836905385, 'recall': 0.7288683602771363, 'f1-score': 0.7739087788131438, 'support': 2165.0}  | {'precision': 0.927653083460449, 'recall': 0.8627888123226591, 'f1-score': 0.8940459939094823, 'support': 9868.0}  | {'precision': 0.8708454160160607, 'recall': 0.8982283917478334, 'f1-score': 0.8843249773482331, 'support': 13039.0} | 0.8349   | {'precision': 0.7959161427775777, 'recall': 0.7800265295195679, 'f1-score': 0.786369407482379, 'support': 29334.0}  | {'precision': 0.8414411074427396, 'recall': 0.8348673893775141, 'f1-score': 0.8371473756606818, 'support': 29334.0} |
+| 0.3561        | 10.0  | 810  | 0.7715          | {'precision': 0.5701775147928994, 'recall': 0.5652275926794932, 'f1-score': 0.5676917638741604, 'support': 4262.0}  | {'precision': 0.7745940783190067, 'recall': 0.7491916859122402, 'f1-score': 0.7616811458088754, 'support': 2165.0}  | {'precision': 0.9296124365756234, 'recall': 0.8726185650587759, 'f1-score': 0.9002143118498772, 'support': 9868.0} | {'precision': 0.8669284467713787, 'recall': 0.9143339213129841, 'f1-score': 0.8900003732596766, 'support': 13039.0} | 0.8374   | {'precision': 0.785328119114727, 'recall': 0.7753429412408733, 'f1-score': 0.7798968986981474, 'support': 29334.0}  | {'precision': 0.8380850988337167, 'recall': 0.8373900593168337, 'f1-score': 0.8371368267053725, 'support': 29334.0} |
+| 0.3561        | 11.0  | 891  | 0.7798          | {'precision': 0.5522299306243805, 'recall': 0.6536837165649929, 'f1-score': 0.5986891586977544, 'support': 4262.0}  | {'precision': 0.7361830742659758, 'recall': 0.7875288683602771, 'f1-score': 0.760990850256639, 'support': 2165.0}   | {'precision': 0.9179415855354659, 'recall': 0.8694770976895014, 'f1-score': 0.8930523028883683, 'support': 9868.0} | {'precision': 0.8987802946301283, 'recall': 0.8703121405015722, 'f1-score': 0.8843171634521723, 'support': 13039.0} | 0.8324   | {'precision': 0.7762837212639876, 'recall': 0.795250455779086, 'f1-score': 0.7842623688237336, 'support': 29334.0}  | {'precision': 0.8428746215263233, 'recall': 0.83244698984114, 'f1-score': 0.8366540534646059, 'support': 29334.0}   |
+| 0.3561        | 12.0  | 972  | 0.8434          | {'precision': 0.5933806146572104, 'recall': 0.5889253871421868, 'f1-score': 0.5911446066886481, 'support': 4262.0}  | {'precision': 0.7994011976047904, 'recall': 0.7399538106235566, 'f1-score': 0.7685296234108899, 'support': 2165.0}  | {'precision': 0.9005203550658096, 'recall': 0.8944061613295501, 'f1-score': 0.8974528445777621, 'support': 9868.0} | {'precision': 0.8794646214001053, 'recall': 0.8970013037809648, 'f1-score': 0.8881464044346572, 'support': 13039.0} | 0.8398   | {'precision': 0.7931916971819789, 'recall': 0.7800716657190646, 'f1-score': 0.7863183697779894, 'support': 29334.0} | {'precision': 0.8390729472526346, 'recall': 0.8397763687188927, 'f1-score': 0.8392967405095946, 'support': 29334.0} |
+| 0.0633        | 13.0  | 1053 | 0.9362          | {'precision': 0.5771842462652784, 'recall': 0.5983106522759268, 'f1-score': 0.5875576036866359, 'support': 4262.0}  | {'precision': 0.7786116322701688, 'recall': 0.766743648960739, 'f1-score': 0.7726320688852689, 'support': 2165.0}   | {'precision': 0.9130388953304522, 'recall': 0.8777867855695176, 'f1-score': 0.8950658744510462, 'support': 9868.0} | {'precision': 0.8741821463488004, 'recall': 0.891479407930056, 'f1-score': 0.8827460510328068, 'support': 13039.0}  | 0.8351   | {'precision': 0.785754230053675, 'recall': 0.7835801236840598, 'f1-score': 0.7845003995139396, 'support': 29334.0}  | {'precision': 0.8370485534468686, 'recall': 0.835071930183405, 'f1-score': 0.83587491458883, 'support': 29334.0}    |
+| 0.0633        | 14.0  | 1134 | 1.0311          | {'precision': 0.6124338624338624, 'recall': 0.5431722196152041, 'f1-score': 0.5757274309873166, 'support': 4262.0}  | {'precision': 0.7854137447405329, 'recall': 0.7759815242494227, 'f1-score': 0.7806691449814126, 'support': 2165.0}  | {'precision': 0.916153682869879, 'recall': 0.8747466558573166, 'f1-score': 0.894971487817522, 'support': 9868.0}   | {'precision': 0.8590723933395269, 'recall': 0.9219265281079837, 'f1-score': 0.8893903521751998, 'support': 13039.0} | 0.8403   | {'precision': 0.7932684208459503, 'recall': 0.7789567319574817, 'f1-score': 0.7851896039903627, 'support': 29334.0} | {'precision': 0.8370035916809992, 'recall': 0.8402536305993046, 'f1-score': 0.8376709093048489, 'support': 29334.0} |
+| 0.0633        | 15.0  | 1215 | 1.0063          | {'precision': 0.5736224028906955, 'recall': 0.5959643359924918, 'f1-score': 0.5845799769850402, 'support': 4262.0}  | {'precision': 0.8367459878251245, 'recall': 0.6983833718244804, 'f1-score': 0.7613293051359518, 'support': 2165.0}  | {'precision': 0.9253507550605119, 'recall': 0.8755573571139035, 'f1-score': 0.8997656860192659, 'support': 9868.0} | {'precision': 0.8641912512716174, 'recall': 0.9121098243730348, 'f1-score': 0.8875041976045669, 'support': 13039.0} | 0.8381   | {'precision': 0.7999775992619873, 'recall': 0.7705037223259776, 'f1-score': 0.7832947914362062, 'support': 29334.0} | {'precision': 0.8405224217982303, 'recall': 0.8381059521374514, 'f1-score': 0.8383041122838222, 'support': 29334.0} |
+| 0.0633        | 16.0  | 1296 | 0.9864          | {'precision': 0.6114068441064638, 'recall': 0.5659314875645237, 'f1-score': 0.587790910198611, 'support': 4262.0}   | {'precision': 0.8076540755467196, 'recall': 0.7505773672055427, 'f1-score': 0.7780703854440987, 'support': 2165.0}  | {'precision': 0.9003660024400163, 'recall': 0.8974462910417511, 'f1-score': 0.8989037758830695, 'support': 9868.0} | {'precision': 0.8745292075917583, 'recall': 0.908198481478641, 'f1-score': 0.89104589917231, 'support': 13039.0}    | 0.8432   | {'precision': 0.7984890324212395, 'recall': 0.7805384068226147, 'f1-score': 0.7889527426745223, 'support': 29334.0} | {'precision': 0.8400553996388973, 'recall': 0.8432194722847208, 'f1-score': 0.8412905564694496, 'support': 29334.0} |
+| 0.0633        | 17.0  | 1377 | 1.0474          | {'precision': 0.5777574788764558, 'recall': 0.5936180197090568, 'f1-score': 0.5855803726420553, 'support': 4262.0}  | {'precision': 0.7891123099558607, 'recall': 0.7431870669745958, 'f1-score': 0.7654614652711702, 'support': 2165.0}  | {'precision': 0.9293800539083558, 'recall': 0.8735306039724362, 'f1-score': 0.9005902941022829, 'support': 9868.0} | {'precision': 0.869437724507001, 'recall': 0.9095789554413682, 'f1-score': 0.8890554722638682, 'support': 13039.0}  | 0.8393   | {'precision': 0.7914218918119184, 'recall': 0.7799786615243642, 'f1-score': 0.7851719010698441, 'support': 29334.0} | {'precision': 0.8412951315142951, 'recall': 0.8392650167041659, 'f1-score': 0.8397213794764584, 'support': 29334.0} |
+| 0.0633        | 18.0  | 1458 | 1.0609          | {'precision': 0.5889078083191438, 'recall': 0.5680431722196152, 'f1-score': 0.5782873522035114, 'support': 4262.0}  | {'precision': 0.7991159135559921, 'recall': 0.751501154734411, 'f1-score': 0.7745774815520113, 'support': 2165.0}   | {'precision': 0.9093172857439302, 'recall': 0.8881232265910012, 'f1-score': 0.8985953040090229, 'support': 9868.0} | {'precision': 0.8732747804265998, 'recall': 0.9074315514993481, 'f1-score': 0.8900255754475703, 'support': 13039.0} | 0.8401   | {'precision': 0.7926539470114164, 'recall': 0.7787747762610939, 'f1-score': 0.7853714283030289, 'support': 29334.0} | {'precision': 0.8386099362381009, 'recall': 0.8401172700620441, 'f1-score': 0.8390946642419506, 'support': 29334.0} |
+| 0.0173        | 19.0  | 1539 | 1.0791          | {'precision': 0.586526726873322, 'recall': 0.5638198029094322, 'f1-score': 0.5749491565976791, 'support': 4262.0}   | {'precision': 0.7679227941176471, 'recall': 0.771824480369515, 'f1-score': 0.7698686938493434, 'support': 2165.0}   | {'precision': 0.9245000534702171, 'recall': 0.8760640453992704, 'f1-score': 0.8996305739112337, 'support': 9868.0} | {'precision': 0.8675419401896426, 'recall': 0.912186517370964, 'f1-score': 0.8893042730569367, 'support': 13039.0}  | 0.8391   | {'precision': 0.7866228786627072, 'recall': 0.7809737115122954, 'f1-score': 0.7834381743537983, 'support': 29334.0} | {'precision': 0.8385210215100449, 'recall': 0.839060475898275, 'f1-score': 0.8382897643467849, 'support': 29334.0}  |
+| 0.0173        | 20.0  | 1620 | 1.0670          | {'precision': 0.5894120517199317, 'recall': 0.5668700140778977, 'f1-score': 0.5779213012797513, 'support': 4262.0}  | {'precision': 0.7822390174775626, 'recall': 0.7648960739030023, 'f1-score': 0.7734703409621673, 'support': 2165.0}  | {'precision': 0.9166666666666666, 'recall': 0.882853668423186, 'f1-score': 0.8994424943217014, 'support': 9868.0}  | {'precision': 0.8707947700896136, 'recall': 0.9091954904517218, 'f1-score': 0.889580910216486, 'support': 13039.0}  | 0.8399   | {'precision': 0.7897781264884436, 'recall': 0.780953811713952, 'f1-score': 0.7851037616950265, 'support': 29334.0}  | {'precision': 0.8388075717984049, 'recall': 0.8399468193904684, 'f1-score': 0.8390471090378641, 'support': 29334.0} |
 
 
 ### Framework versions

meta_data/README_s42_e20.md

@@ -0,0 +1,100 @@
+---
+license: apache-2.0
+base_model: allenai/longformer-base-4096
+tags:
+- generated_from_trainer
+datasets:
+- essays_su_g
+metrics:
+- accuracy
+model-index:
+- name: longformer-simple
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: essays_su_g
+      type: essays_su_g
+      config: simple
+      split: train[0%:20%]
+      args: simple
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8399468193904684
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# longformer-simple
+
+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: 1.0670
+- Claim: {'precision': 0.5894120517199317, 'recall': 0.5668700140778977, 'f1-score': 0.5779213012797513, 'support': 4262.0}
+- Majorclaim: {'precision': 0.7822390174775626, 'recall': 0.7648960739030023, 'f1-score': 0.7734703409621673, 'support': 2165.0}
+- O: {'precision': 0.9166666666666666, 'recall': 0.882853668423186, 'f1-score': 0.8994424943217014, 'support': 9868.0}
+- Premise: {'precision': 0.8707947700896136, 'recall': 0.9091954904517218, 'f1-score': 0.889580910216486, 'support': 13039.0}
+- Accuracy: 0.8399
+- Macro avg: {'precision': 0.7897781264884436, 'recall': 0.780953811713952, 'f1-score': 0.7851037616950265, 'support': 29334.0}
+- Weighted avg: {'precision': 0.8388075717984049, 'recall': 0.8399468193904684, 'f1-score': 0.8390471090378641, 'support': 29334.0}
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Claim                                                                                                               | Majorclaim                                                                                                          | O                                                                                                                  | Premise                                                                                                             | Accuracy | Macro avg                                                                                                           | Weighted avg                                                                                                        |
+|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:--------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
+| No log        | 1.0   | 81   | 0.5489          | {'precision': 0.43257049448304047, 'recall': 0.496715157203191, 'f1-score': 0.46242900830056793, 'support': 4262.0} | {'precision': 0.6522533495736906, 'recall': 0.49468822170900695, 'f1-score': 0.5626477541371159, 'support': 2165.0} | {'precision': 0.911293908403735, 'recall': 0.8307661126874747, 'f1-score': 0.8691687871077185, 'support': 9868.0}  | {'precision': 0.8377046804810897, 'recall': 0.88672444205844, 'f1-score': 0.8615178272046495, 'support': 13039.0}   | 0.7823   | {'precision': 0.708455608235389, 'recall': 0.6772234834145282, 'f1-score': 0.6889408441875129, 'support': 29334.0}  | {'precision': 0.7899101236188295, 'recall': 0.7823004022635849, 'f1-score': 0.7840489998358311, 'support': 29334.0} |
+| No log        | 2.0   | 162  | 0.5075          | {'precision': 0.5107383923092657, 'recall': 0.5858751759737213, 'f1-score': 0.5457327068079991, 'support': 4262.0}  | {'precision': 0.5687340153452686, 'recall': 0.8217090069284064, 'f1-score': 0.6722085773663329, 'support': 2165.0}  | {'precision': 0.9344863131370977, 'recall': 0.8268139440616133, 'f1-score': 0.8773589977955805, 'support': 9868.0} | {'precision': 0.8834419195931988, 'recall': 0.852749443975765, 'f1-score': 0.8678243902439025, 'support': 13039.0}  | 0.8030   | {'precision': 0.7243501600962077, 'recall': 0.7717868927348766, 'f1-score': 0.7407811680534537, 'support': 29334.0} | {'precision': 0.8232353684753937, 'recall': 0.8029590236585532, 'f1-score': 0.8097969994222006, 'support': 29334.0} |
+| No log        | 3.0   | 243  | 0.5219          | {'precision': 0.5516552511415526, 'recall': 0.45354293758798686, 'f1-score': 0.4978109708987896, 'support': 4262.0} | {'precision': 0.8036105032822757, 'recall': 0.6785219399538106, 'f1-score': 0.7357876283496118, 'support': 2165.0}  | {'precision': 0.9331699710403207, 'recall': 0.8490068909606809, 'f1-score': 0.8891011355194736, 'support': 9868.0} | {'precision': 0.8191560170394037, 'recall': 0.9438607255157604, 'f1-score': 0.8770979581655561, 'support': 13039.0} | 0.8211   | {'precision': 0.7768979356258882, 'recall': 0.7312331235045597, 'f1-score': 0.7499494232333578, 'support': 29334.0} | {'precision': 0.8174973750724106, 'recall': 0.821129065248517, 'f1-score': 0.815598992812927, 'support': 29334.0}   |
+| No log        | 4.0   | 324  | 0.4725          | {'precision': 0.5851569933396765, 'recall': 0.5771938057250118, 'f1-score': 0.5811481218993623, 'support': 4262.0}  | {'precision': 0.7335329341317365, 'recall': 0.792147806004619, 'f1-score': 0.761714412613813, 'support': 2165.0}    | {'precision': 0.9085720215857203, 'recall': 0.8872111876773409, 'f1-score': 0.8977645611156685, 'support': 9868.0} | {'precision': 0.8851474612344178, 'recall': 0.8930899608865711, 'f1-score': 0.8891009734682191, 'support': 13039.0} | 0.8378   | {'precision': 0.7781023525728877, 'recall': 0.7874106900733857, 'f1-score': 0.7824320172742658, 'support': 29334.0} | {'precision': 0.8382513248807655, 'recall': 0.8377650507943001, 'f1-score': 0.8378705011585708, 'support': 29334.0} |
+| No log        | 5.0   | 405  | 0.5539          | {'precision': 0.5784176029962547, 'recall': 0.5797747536367902, 'f1-score': 0.5790953831731895, 'support': 4262.0}  | {'precision': 0.8008497079129049, 'recall': 0.6965357967667436, 'f1-score': 0.7450592885375493, 'support': 2165.0}  | {'precision': 0.9040794979079498, 'recall': 0.8758613700851237, 'f1-score': 0.8897467572575665, 'support': 9868.0} | {'precision': 0.8672442910639547, 'recall': 0.905820998542833, 'f1-score': 0.8861129867206842, 'support': 13039.0}  | 0.8329   | {'precision': 0.787647774970266, 'recall': 0.7644982297578727, 'f1-score': 0.7750036039222473, 'support': 29334.0}  | {'precision': 0.8327711951367025, 'recall': 0.8329242517215518, 'f1-score': 0.8323176558681596, 'support': 29334.0} |
+| No log        | 6.0   | 486  | 0.5790          | {'precision': 0.5325670498084292, 'recall': 0.6848897231346786, 'f1-score': 0.5991994252283692, 'support': 4262.0}  | {'precision': 0.7400087834870444, 'recall': 0.7782909930715936, 'f1-score': 0.7586672669968483, 'support': 2165.0}  | {'precision': 0.9212211784799317, 'recall': 0.8745439805431698, 'f1-score': 0.8972759409440632, 'support': 9868.0} | {'precision': 0.9062909567496723, 'recall': 0.8485313290896541, 'f1-score': 0.8764605695726225, 'support': 13039.0} | 0.8283   | {'precision': 0.7750219921312693, 'recall': 0.796564006459774, 'f1-score': 0.7829008006854759, 'support': 29334.0}  | {'precision': 0.8447418748493872, 'recall': 0.8283220835890094, 'f1-score': 0.8344852708551485, 'support': 29334.0} |
+| 0.3561        | 7.0   | 567  | 0.7058          | {'precision': 0.5955997904662127, 'recall': 0.5335523228531206, 'f1-score': 0.5628712871287128, 'support': 4262.0}  | {'precision': 0.8422198041349293, 'recall': 0.7150115473441109, 'f1-score': 0.7734199350487135, 'support': 2165.0}  | {'precision': 0.9193378321383383, 'recall': 0.8835630320226996, 'f1-score': 0.9010954940057875, 'support': 9868.0} | {'precision': 0.848316189939411, 'recall': 0.9234603880665695, 'f1-score': 0.8842947894099071, 'support': 13039.0}  | 0.8380   | {'precision': 0.8013684041697228, 'recall': 0.7638968225716252, 'f1-score': 0.7804203763982802, 'support': 29334.0} | {'precision': 0.8350403187795808, 'recall': 0.838003681734506, 'f1-score': 0.835063123988816, 'support': 29334.0}   |
+| 0.3561        | 8.0   | 648  | 0.6876          | {'precision': 0.5858841386288894, 'recall': 0.5434068512435476, 'f1-score': 0.5638466220328667, 'support': 4262.0}  | {'precision': 0.8025641025641026, 'recall': 0.7228637413394919, 'f1-score': 0.7606318347509112, 'support': 2165.0}  | {'precision': 0.8864763037874281, 'recall': 0.9060599918929875, 'f1-score': 0.896161170692593, 'support': 9868.0}  | {'precision': 0.8807043836642937, 'recall': 0.9013728046629342, 'f1-score': 0.8909187386294724, 'support': 13039.0} | 0.8378   | {'precision': 0.7889072321611785, 'recall': 0.7684258472847404, 'f1-score': 0.7778895915264609, 'support': 29334.0} | {'precision': 0.8340438435010799, 'recall': 0.8377650507943001, 'f1-score': 0.8355454452418354, 'support': 29334.0} |
+| 0.3561        | 9.0   | 729  | 0.6963          | {'precision': 0.5602836879432624, 'recall': 0.6302205537306429, 'f1-score': 0.5931978798586572, 'support': 4262.0}  | {'precision': 0.8248823836905385, 'recall': 0.7288683602771363, 'f1-score': 0.7739087788131438, 'support': 2165.0}  | {'precision': 0.927653083460449, 'recall': 0.8627888123226591, 'f1-score': 0.8940459939094823, 'support': 9868.0}  | {'precision': 0.8708454160160607, 'recall': 0.8982283917478334, 'f1-score': 0.8843249773482331, 'support': 13039.0} | 0.8349   | {'precision': 0.7959161427775777, 'recall': 0.7800265295195679, 'f1-score': 0.786369407482379, 'support': 29334.0}  | {'precision': 0.8414411074427396, 'recall': 0.8348673893775141, 'f1-score': 0.8371473756606818, 'support': 29334.0} |
+| 0.3561        | 10.0  | 810  | 0.7715          | {'precision': 0.5701775147928994, 'recall': 0.5652275926794932, 'f1-score': 0.5676917638741604, 'support': 4262.0}  | {'precision': 0.7745940783190067, 'recall': 0.7491916859122402, 'f1-score': 0.7616811458088754, 'support': 2165.0}  | {'precision': 0.9296124365756234, 'recall': 0.8726185650587759, 'f1-score': 0.9002143118498772, 'support': 9868.0} | {'precision': 0.8669284467713787, 'recall': 0.9143339213129841, 'f1-score': 0.8900003732596766, 'support': 13039.0} | 0.8374   | {'precision': 0.785328119114727, 'recall': 0.7753429412408733, 'f1-score': 0.7798968986981474, 'support': 29334.0}  | {'precision': 0.8380850988337167, 'recall': 0.8373900593168337, 'f1-score': 0.8371368267053725, 'support': 29334.0} |
+| 0.3561        | 11.0  | 891  | 0.7798          | {'precision': 0.5522299306243805, 'recall': 0.6536837165649929, 'f1-score': 0.5986891586977544, 'support': 4262.0}  | {'precision': 0.7361830742659758, 'recall': 0.7875288683602771, 'f1-score': 0.760990850256639, 'support': 2165.0}   | {'precision': 0.9179415855354659, 'recall': 0.8694770976895014, 'f1-score': 0.8930523028883683, 'support': 9868.0} | {'precision': 0.8987802946301283, 'recall': 0.8703121405015722, 'f1-score': 0.8843171634521723, 'support': 13039.0} | 0.8324   | {'precision': 0.7762837212639876, 'recall': 0.795250455779086, 'f1-score': 0.7842623688237336, 'support': 29334.0}  | {'precision': 0.8428746215263233, 'recall': 0.83244698984114, 'f1-score': 0.8366540534646059, 'support': 29334.0}   |
+| 0.3561        | 12.0  | 972  | 0.8434          | {'precision': 0.5933806146572104, 'recall': 0.5889253871421868, 'f1-score': 0.5911446066886481, 'support': 4262.0}  | {'precision': 0.7994011976047904, 'recall': 0.7399538106235566, 'f1-score': 0.7685296234108899, 'support': 2165.0}  | {'precision': 0.9005203550658096, 'recall': 0.8944061613295501, 'f1-score': 0.8974528445777621, 'support': 9868.0} | {'precision': 0.8794646214001053, 'recall': 0.8970013037809648, 'f1-score': 0.8881464044346572, 'support': 13039.0} | 0.8398   | {'precision': 0.7931916971819789, 'recall': 0.7800716657190646, 'f1-score': 0.7863183697779894, 'support': 29334.0} | {'precision': 0.8390729472526346, 'recall': 0.8397763687188927, 'f1-score': 0.8392967405095946, 'support': 29334.0} |
+| 0.0633        | 13.0  | 1053 | 0.9362          | {'precision': 0.5771842462652784, 'recall': 0.5983106522759268, 'f1-score': 0.5875576036866359, 'support': 4262.0}  | {'precision': 0.7786116322701688, 'recall': 0.766743648960739, 'f1-score': 0.7726320688852689, 'support': 2165.0}   | {'precision': 0.9130388953304522, 'recall': 0.8777867855695176, 'f1-score': 0.8950658744510462, 'support': 9868.0} | {'precision': 0.8741821463488004, 'recall': 0.891479407930056, 'f1-score': 0.8827460510328068, 'support': 13039.0}  | 0.8351   | {'precision': 0.785754230053675, 'recall': 0.7835801236840598, 'f1-score': 0.7845003995139396, 'support': 29334.0}  | {'precision': 0.8370485534468686, 'recall': 0.835071930183405, 'f1-score': 0.83587491458883, 'support': 29334.0}    |
+| 0.0633        | 14.0  | 1134 | 1.0311          | {'precision': 0.6124338624338624, 'recall': 0.5431722196152041, 'f1-score': 0.5757274309873166, 'support': 4262.0}  | {'precision': 0.7854137447405329, 'recall': 0.7759815242494227, 'f1-score': 0.7806691449814126, 'support': 2165.0}  | {'precision': 0.916153682869879, 'recall': 0.8747466558573166, 'f1-score': 0.894971487817522, 'support': 9868.0}   | {'precision': 0.8590723933395269, 'recall': 0.9219265281079837, 'f1-score': 0.8893903521751998, 'support': 13039.0} | 0.8403   | {'precision': 0.7932684208459503, 'recall': 0.7789567319574817, 'f1-score': 0.7851896039903627, 'support': 29334.0} | {'precision': 0.8370035916809992, 'recall': 0.8402536305993046, 'f1-score': 0.8376709093048489, 'support': 29334.0} |
+| 0.0633        | 15.0  | 1215 | 1.0063          | {'precision': 0.5736224028906955, 'recall': 0.5959643359924918, 'f1-score': 0.5845799769850402, 'support': 4262.0}  | {'precision': 0.8367459878251245, 'recall': 0.6983833718244804, 'f1-score': 0.7613293051359518, 'support': 2165.0}  | {'precision': 0.9253507550605119, 'recall': 0.8755573571139035, 'f1-score': 0.8997656860192659, 'support': 9868.0} | {'precision': 0.8641912512716174, 'recall': 0.9121098243730348, 'f1-score': 0.8875041976045669, 'support': 13039.0} | 0.8381   | {'precision': 0.7999775992619873, 'recall': 0.7705037223259776, 'f1-score': 0.7832947914362062, 'support': 29334.0} | {'precision': 0.8405224217982303, 'recall': 0.8381059521374514, 'f1-score': 0.8383041122838222, 'support': 29334.0} |
+| 0.0633        | 16.0  | 1296 | 0.9864          | {'precision': 0.6114068441064638, 'recall': 0.5659314875645237, 'f1-score': 0.587790910198611, 'support': 4262.0}   | {'precision': 0.8076540755467196, 'recall': 0.7505773672055427, 'f1-score': 0.7780703854440987, 'support': 2165.0}  | {'precision': 0.9003660024400163, 'recall': 0.8974462910417511, 'f1-score': 0.8989037758830695, 'support': 9868.0} | {'precision': 0.8745292075917583, 'recall': 0.908198481478641, 'f1-score': 0.89104589917231, 'support': 13039.0}    | 0.8432   | {'precision': 0.7984890324212395, 'recall': 0.7805384068226147, 'f1-score': 0.7889527426745223, 'support': 29334.0} | {'precision': 0.8400553996388973, 'recall': 0.8432194722847208, 'f1-score': 0.8412905564694496, 'support': 29334.0} |
+| 0.0633        | 17.0  | 1377 | 1.0474          | {'precision': 0.5777574788764558, 'recall': 0.5936180197090568, 'f1-score': 0.5855803726420553, 'support': 4262.0}  | {'precision': 0.7891123099558607, 'recall': 0.7431870669745958, 'f1-score': 0.7654614652711702, 'support': 2165.0}  | {'precision': 0.9293800539083558, 'recall': 0.8735306039724362, 'f1-score': 0.9005902941022829, 'support': 9868.0} | {'precision': 0.869437724507001, 'recall': 0.9095789554413682, 'f1-score': 0.8890554722638682, 'support': 13039.0}  | 0.8393   | {'precision': 0.7914218918119184, 'recall': 0.7799786615243642, 'f1-score': 0.7851719010698441, 'support': 29334.0} | {'precision': 0.8412951315142951, 'recall': 0.8392650167041659, 'f1-score': 0.8397213794764584, 'support': 29334.0} |
+| 0.0633        | 18.0  | 1458 | 1.0609          | {'precision': 0.5889078083191438, 'recall': 0.5680431722196152, 'f1-score': 0.5782873522035114, 'support': 4262.0}  | {'precision': 0.7991159135559921, 'recall': 0.751501154734411, 'f1-score': 0.7745774815520113, 'support': 2165.0}   | {'precision': 0.9093172857439302, 'recall': 0.8881232265910012, 'f1-score': 0.8985953040090229, 'support': 9868.0} | {'precision': 0.8732747804265998, 'recall': 0.9074315514993481, 'f1-score': 0.8900255754475703, 'support': 13039.0} | 0.8401   | {'precision': 0.7926539470114164, 'recall': 0.7787747762610939, 'f1-score': 0.7853714283030289, 'support': 29334.0} | {'precision': 0.8386099362381009, 'recall': 0.8401172700620441, 'f1-score': 0.8390946642419506, 'support': 29334.0} |
+| 0.0173        | 19.0  | 1539 | 1.0791          | {'precision': 0.586526726873322, 'recall': 0.5638198029094322, 'f1-score': 0.5749491565976791, 'support': 4262.0}   | {'precision': 0.7679227941176471, 'recall': 0.771824480369515, 'f1-score': 0.7698686938493434, 'support': 2165.0}   | {'precision': 0.9245000534702171, 'recall': 0.8760640453992704, 'f1-score': 0.8996305739112337, 'support': 9868.0} | {'precision': 0.8675419401896426, 'recall': 0.912186517370964, 'f1-score': 0.8893042730569367, 'support': 13039.0}  | 0.8391   | {'precision': 0.7866228786627072, 'recall': 0.7809737115122954, 'f1-score': 0.7834381743537983, 'support': 29334.0} | {'precision': 0.8385210215100449, 'recall': 0.839060475898275, 'f1-score': 0.8382897643467849, 'support': 29334.0}  |
+| 0.0173        | 20.0  | 1620 | 1.0670          | {'precision': 0.5894120517199317, 'recall': 0.5668700140778977, 'f1-score': 0.5779213012797513, 'support': 4262.0}  | {'precision': 0.7822390174775626, 'recall': 0.7648960739030023, 'f1-score': 0.7734703409621673, 'support': 2165.0}  | {'precision': 0.9166666666666666, 'recall': 0.882853668423186, 'f1-score': 0.8994424943217014, 'support': 9868.0}  | {'precision': 0.8707947700896136, 'recall': 0.9091954904517218, 'f1-score': 0.889580910216486, 'support': 13039.0}  | 0.8399   | {'precision': 0.7897781264884436, 'recall': 0.780953811713952, 'f1-score': 0.7851037616950265, 'support': 29334.0}  | {'precision': 0.8388075717984049, 'recall': 0.8399468193904684, 'f1-score': 0.8390471090378641, 'support': 29334.0} |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

model.safetensors

@@ -1,3 +1,3 @@
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 size 592324828