trainer: training complete at 2024-03-02 11:43:30.031283.

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

README.md CHANGED Viewed

@@ -17,12 +17,12 @@ model-index:
       name: essays_su_g
       type: essays_su_g
       config: full_labels
-      split: train[60%:80%]
       args: full_labels
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8488955223880597
 ---
 <!-- 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: 0.6893
-- B-claim: {'precision': 0.6103151862464183, 'recall': 0.6283185840707964, 'f1-score': 0.6191860465116279, 'support': 339.0}
-- B-majorclaim: {'precision': 0.7816091954022989, 'recall': 0.85, 'f1-score': 0.8143712574850299, 'support': 160.0}
-- B-premise: {'precision': 0.761252446183953, 'recall': 0.8267800212539851, 'f1-score': 0.792664289353031, 'support': 941.0}
-- I-claim: {'precision': 0.636103781882146, 'recall': 0.6157939548744147, 'f1-score': 0.6257841228639411, 'support': 4698.0}
-- I-majorclaim: {'precision': 0.8445692883895131, 'recall': 0.8895463510848126, 'f1-score': 0.866474543707973, 'support': 2028.0}
-- I-premise: {'precision': 0.8711272247857613, 'recall': 0.8892402933853711, 'f1-score': 0.8800905730744897, 'support': 14861.0}
-- O: {'precision': 0.9305019305019305, 'recall': 0.897450587224291, 'f1-score': 0.9136774569845436, 'support': 10473.0}
-- Accuracy: 0.8489
-- Macro avg: {'precision': 0.7764970076274315, 'recall': 0.7995899702705245, 'f1-score': 0.7874640414258051, 'support': 33500.0}
-- Weighted avg: {'precision': 0.8489690555547813, 'recall': 0.8488955223880597, 'f1-score': 0.8486929780465652, 'support': 33500.0}
 ## 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   | 0.7635          | {'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': 0.8299319727891157, 'recall': 0.12964930924548354, 'f1-score': 0.22426470588235295, 'support': 941.0} | {'precision': 0.423873640600725, 'recall': 0.348446147296722, 'f1-score': 0.38247663551401867, 'support': 4698.0}   | {'precision': 0.5125673249551167, 'recall': 0.28155818540433925, 'f1-score': 0.3634627625716104, 'support': 2028.0} | {'precision': 0.8110747093209996, 'recall': 0.8496063521970257, 'f1-score': 0.8298935191271198, 'support': 14861.0} | {'precision': 0.7380952380952381, 'recall': 0.9027976701995608, 'f1-score': 0.8121805609242796, 'support': 10473.0} | 0.7287   | {'precision': 0.47364898368017067, 'recall': 0.3588653806204473, 'f1-score': 0.3731825977170545, 'support': 33500.0} | {'precision': 0.7043362259324342, 'recall': 0.7286865671641791, 'f1-score': 0.7040007584084623, 'support': 33500.0} |
-| No log        | 2.0   | 82   | 0.5587          | {'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': 0.5819477434679335, 'recall': 0.7810839532412327, 'f1-score': 0.6669691470054446, 'support': 941.0}   | {'precision': 0.559799275160301, 'recall': 0.4274159216687952, 'f1-score': 0.48473144236572113, 'support': 4698.0}  | {'precision': 0.6312089971883786, 'recall': 0.6642011834319527, 'f1-score': 0.6472849591542528, 'support': 2028.0}  | {'precision': 0.8200934579439252, 'recall': 0.9211358589596932, 'f1-score': 0.8676829461540899, 'support': 14861.0} | {'precision': 0.9105252442996743, 'recall': 0.8541010216747827, 'f1-score': 0.8814110459673844, 'support': 10473.0} | 0.7977   | {'precision': 0.5005106740086018, 'recall': 0.5211339912823509, 'f1-score': 0.506868505806699, 'support': 33500.0}   | {'precision': 0.7815218337211824, 'recall': 0.7977313432835821, 'f1-score': 0.7863652038192075, 'support': 33500.0} |
-| No log        | 3.0   | 123  | 0.5104          | {'precision': 0.4175824175824176, 'recall': 0.22418879056047197, 'f1-score': 0.29174664107485604, 'support': 339.0} | {'precision': 0.8823529411764706, 'recall': 0.09375, 'f1-score': 0.1694915254237288, 'support': 160.0} | {'precision': 0.6546521374685667, 'recall': 0.8299681190223167, 'f1-score': 0.731958762886598, 'support': 941.0}    | {'precision': 0.629277566539924, 'recall': 0.35227756492124307, 'f1-score': 0.45169213973799127, 'support': 4698.0} | {'precision': 0.7788510421962379, 'recall': 0.7554240631163708, 'f1-score': 0.7669586983729662, 'support': 2028.0}  | {'precision': 0.7908845678318535, 'recall': 0.9469753044882578, 'f1-score': 0.8619200734956362, 'support': 14861.0} | {'precision': 0.9332098384274982, 'recall': 0.8658455074954645, 'f1-score': 0.8982664685487864, 'support': 10473.0} | 0.8119   | {'precision': 0.7266872158889954, 'recall': 0.5812041928005893, 'f1-score': 0.5960049013629376, 'support': 33500.0}  | {'precision': 0.804819781883149, 'recall': 0.8119402985074626, 'f1-score': 0.7972768597429257, 'support': 33500.0}  |
-| No log        | 4.0   | 164  | 0.4638          | {'precision': 0.6144200626959248, 'recall': 0.5781710914454278, 'f1-score': 0.5957446808510639, 'support': 339.0}   | {'precision': 0.7910447761194029, 'recall': 0.6625, 'f1-score': 0.7210884353741497, 'support': 160.0}  | {'precision': 0.7529411764705882, 'recall': 0.8161530286928799, 'f1-score': 0.7832738398776133, 'support': 941.0}   | {'precision': 0.6121971950701233, 'recall': 0.6132396764580673, 'f1-score': 0.6127179923436835, 'support': 4698.0}  | {'precision': 0.7631464580617123, 'recall': 0.8658777120315582, 'f1-score': 0.8112728112728113, 'support': 2028.0}  | {'precision': 0.8770213344204376, 'recall': 0.8685821950070655, 'f1-score': 0.8727813651577132, 'support': 14861.0} | {'precision': 0.9097262667443214, 'recall': 0.8948725293612145, 'f1-score': 0.9022382671480144, 'support': 10473.0} | 0.8354   | {'precision': 0.7600710385117873, 'recall': 0.7570566047137447, 'f1-score': 0.7570167702892928, 'support': 33500.0}  | {'precision': 0.8366601162482339, 'recall': 0.8354328358208956, 'f1-score': 0.8357536689114934, 'support': 33500.0} |
-| No log        | 5.0   | 205  | 0.4939          | {'precision': 0.6254295532646048, 'recall': 0.5368731563421829, 'f1-score': 0.5777777777777778, 'support': 339.0}   | {'precision': 0.7636363636363637, 'recall': 0.7875, 'f1-score': 0.7753846153846152, 'support': 160.0}  | {'precision': 0.7188898836168308, 'recall': 0.8533475026567482, 'f1-score': 0.7803692905733722, 'support': 941.0}   | {'precision': 0.6303191489361702, 'recall': 0.5549169859514687, 'f1-score': 0.5902196060674665, 'support': 4698.0}  | {'precision': 0.8303317535545024, 'recall': 0.863905325443787, 'f1-score': 0.8467858869018849, 'support': 2028.0}   | {'precision': 0.8650767507740957, 'recall': 0.8835879146759976, 'f1-score': 0.8742343541944074, 'support': 14861.0} | {'precision': 0.904970481812988, 'recall': 0.9074763678029218, 'f1-score': 0.9062216924910609, 'support': 10473.0}  | 0.8390   | {'precision': 0.7626648479422222, 'recall': 0.7696581789818724, 'f1-score': 0.7644276033415122, 'support': 33500.0}  | {'precision': 0.8355072066989216, 'recall': 0.8389552238805971, 'f1-score': 0.8366342005564686, 'support': 33500.0} |
-| No log        | 6.0   | 246  | 0.4979          | {'precision': 0.6232876712328768, 'recall': 0.5368731563421829, 'f1-score': 0.5768621236133122, 'support': 339.0}   | {'precision': 0.782051282051282, 'recall': 0.7625, 'f1-score': 0.7721518987341772, 'support': 160.0}   | {'precision': 0.7490530303030303, 'recall': 0.8405951115834219, 'f1-score': 0.7921882824236354, 'support': 941.0}   | {'precision': 0.6594274432379073, 'recall': 0.5687526607066837, 'f1-score': 0.6107428571428571, 'support': 4698.0}  | {'precision': 0.8388861263053208, 'recall': 0.8318540433925049, 'f1-score': 0.8353552859618717, 'support': 2028.0}  | {'precision': 0.8607000386050702, 'recall': 0.9001413094677343, 'f1-score': 0.8799789494457783, 'support': 14861.0} | {'precision': 0.9164661726494081, 'recall': 0.9092905566695312, 'f1-score': 0.912864263803681, 'support': 10473.0}  | 0.8464   | {'precision': 0.7756959663406994, 'recall': 0.7642866911660084, 'f1-score': 0.7685919515893305, 'support': 33500.0}  | {'precision': 0.8426730244638024, 'recall': 0.8463880597014926, 'f1-score': 0.843752680680015, 'support': 33500.0}  |
-| No log        | 7.0   | 287  | 0.5638          | {'precision': 0.6418439716312057, 'recall': 0.5339233038348082, 'f1-score': 0.5829307568438002, 'support': 339.0}   | {'precision': 0.7758620689655172, 'recall': 0.84375, 'f1-score': 0.8083832335329341, 'support': 160.0} | {'precision': 0.7203463203463204, 'recall': 0.8841657810839533, 'f1-score': 0.7938931297709925, 'support': 941.0}   | {'precision': 0.7018554062699937, 'recall': 0.4670072371221797, 'f1-score': 0.560838445807771, 'support': 4698.0}   | {'precision': 0.8422548555187115, 'recall': 0.8767258382642998, 'f1-score': 0.8591447209470888, 'support': 2028.0}  | {'precision': 0.834623927006423, 'recall': 0.9356032568467801, 'f1-score': 0.882233502538071, 'support': 14861.0}   | {'precision': 0.9340538376863805, 'recall': 0.8912441516279958, 'f1-score': 0.9121469754715138, 'support': 10473.0} | 0.8465   | {'precision': 0.7786914839177931, 'recall': 0.7760599383971453, 'f1-score': 0.7713672521303102, 'support': 33500.0}  | {'precision': 0.8421095669207056, 'recall': 0.8465074626865672, 'f1-score': 0.8392525416975183, 'support': 33500.0} |
-| No log        | 8.0   | 328  | 0.5493          | {'precision': 0.5994550408719346, 'recall': 0.6489675516224189, 'f1-score': 0.623229461756374, 'support': 339.0}    | {'precision': 0.7687861271676301, 'recall': 0.83125, 'f1-score': 0.7987987987987989, 'support': 160.0} | {'precision': 0.7347504621072088, 'recall': 0.844845908607864, 'f1-score': 0.7859614434008898, 'support': 941.0}    | {'precision': 0.6259211096662332, 'recall': 0.6147296722009365, 'f1-score': 0.620274914089347, 'support': 4698.0}   | {'precision': 0.8396803008932769, 'recall': 0.8806706114398422, 'f1-score': 0.8596871239470517, 'support': 2028.0}  | {'precision': 0.8634082763115021, 'recall': 0.8915281609582127, 'f1-score': 0.8772429318678407, 'support': 14861.0} | {'precision': 0.9433210784313726, 'recall': 0.8819822400458321, 'f1-score': 0.9116210214655811, 'support': 10473.0} | 0.8450   | {'precision': 0.7679031993498798, 'recall': 0.7991391635535867, 'f1-score': 0.782402242189412, 'support': 33500.0}   | {'precision': 0.8469129043625616, 'recall': 0.8450149253731343, 'f1-score': 0.8453815974816967, 'support': 33500.0} |
-| No log        | 9.0   | 369  | 0.5795          | {'precision': 0.6209150326797386, 'recall': 0.56047197640118, 'f1-score': 0.5891472868217054, 'support': 339.0}     | {'precision': 0.810126582278481, 'recall': 0.8, 'f1-score': 0.8050314465408804, 'support': 160.0}      | {'precision': 0.7478591817316841, 'recall': 0.8352816153028693, 'f1-score': 0.7891566265060241, 'support': 941.0}   | {'precision': 0.6493925117778329, 'recall': 0.5574712643678161, 'f1-score': 0.5999312793494446, 'support': 4698.0}  | {'precision': 0.8825079030558483, 'recall': 0.8259368836291914, 'f1-score': 0.8532857870606215, 'support': 2028.0}  | {'precision': 0.8624886112195757, 'recall': 0.8917973218491353, 'f1-score': 0.8768981374268038, 'support': 14861.0} | {'precision': 0.8974550898203593, 'recall': 0.9158789267640599, 'f1-score': 0.9065734133547564, 'support': 10473.0} | 0.8431   | {'precision': 0.7815349875090741, 'recall': 0.7695482840448931, 'f1-score': 0.7742891395800339, 'support': 33500.0}  | {'precision': 0.8388330863882018, 'recall': 0.8430746268656717, 'f1-score': 0.840184765735164, 'support': 33500.0}  |
-| No log        | 10.0  | 410  | 0.5960          | {'precision': 0.6303630363036303, 'recall': 0.5634218289085545, 'f1-score': 0.5950155763239875, 'support': 339.0}   | {'precision': 0.8, 'recall': 0.825, 'f1-score': 0.8123076923076924, 'support': 160.0}                  | {'precision': 0.7326642335766423, 'recall': 0.8533475026567482, 'f1-score': 0.7884143348060874, 'support': 941.0}   | {'precision': 0.666921508664628, 'recall': 0.5570455512984248, 'f1-score': 0.6070517281373231, 'support': 4698.0}   | {'precision': 0.8839779005524862, 'recall': 0.8678500986193294, 'f1-score': 0.8758397611346106, 'support': 2028.0}  | {'precision': 0.851998491704374, 'recall': 0.9122535495592491, 'f1-score': 0.8810970656094628, 'support': 14861.0}  | {'precision': 0.9333267385498071, 'recall': 0.900887997708393, 'f1-score': 0.9168205227869012, 'support': 10473.0}  | 0.8506   | {'precision': 0.7856074156216526, 'recall': 0.7828295041072427, 'f1-score': 0.7823638115865806, 'support': 33500.0}  | {'precision': 0.8475616436173209, 'recall': 0.8505970149253731, 'f1-score': 0.8476881875144826, 'support': 33500.0} |
-| No log        | 11.0  | 451  | 0.5954          | {'precision': 0.6235294117647059, 'recall': 0.6253687315634219, 'f1-score': 0.6244477172312225, 'support': 339.0}   | {'precision': 0.7861271676300579, 'recall': 0.85, 'f1-score': 0.8168168168168167, 'support': 160.0}    | {'precision': 0.7670286278381047, 'recall': 0.8257173219978746, 'f1-score': 0.7952917093142272, 'support': 941.0}   | {'precision': 0.6513114392770554, 'recall': 0.6289910600255428, 'f1-score': 0.639956686518679, 'support': 4698.0}   | {'precision': 0.8176156583629893, 'recall': 0.9063116370808678, 'f1-score': 0.8596819457436857, 'support': 2028.0}  | {'precision': 0.8765022242878959, 'recall': 0.8882982302671422, 'f1-score': 0.8823608047590401, 'support': 14861.0} | {'precision': 0.9289099526066351, 'recall': 0.8983099398453165, 'f1-score': 0.9133537206931702, 'support': 10473.0} | 0.8516   | {'precision': 0.7787177831096349, 'recall': 0.8032852743971665, 'f1-score': 0.7902727715824059, 'support': 33500.0}  | {'precision': 0.8516743266232883, 'recall': 0.8515522388059702, 'f1-score': 0.8513139373395039, 'support': 33500.0} |
-| No log        | 12.0  | 492  | 0.6606          | {'precision': 0.5913978494623656, 'recall': 0.6489675516224189, 'f1-score': 0.6188466947960619, 'support': 339.0}   | {'precision': 0.7771428571428571, 'recall': 0.85, 'f1-score': 0.8119402985074626, 'support': 160.0}    | {'precision': 0.7609126984126984, 'recall': 0.8150903294367694, 'f1-score': 0.7870702924576707, 'support': 941.0}   | {'precision': 0.6260370134014039, 'recall': 0.6264367816091954, 'f1-score': 0.6262368337057134, 'support': 4698.0}  | {'precision': 0.827490774907749, 'recall': 0.8846153846153846, 'f1-score': 0.8551000953288845, 'support': 2028.0}   | {'precision': 0.8761073825503356, 'recall': 0.8784065675257385, 'f1-score': 0.8772554685662445, 'support': 14861.0} | {'precision': 0.9252161949685535, 'recall': 0.8989783252172252, 'f1-score': 0.9119085670008232, 'support': 10473.0} | 0.8456   | {'precision': 0.7691863958351375, 'recall': 0.8003564200038189, 'f1-score': 0.784051178623266, 'support': 33500.0}   | {'precision': 0.8468579038739062, 'recall': 0.8456417910447761, 'f1-score': 0.8460850209295142, 'support': 33500.0} |
-| 0.3295        | 13.0  | 533  | 0.6498          | {'precision': 0.6098901098901099, 'recall': 0.6548672566371682, 'f1-score': 0.631578947368421, 'support': 339.0}    | {'precision': 0.7771428571428571, 'recall': 0.85, 'f1-score': 0.8119402985074626, 'support': 160.0}    | {'precision': 0.7704590818363274, 'recall': 0.820403825717322, 'f1-score': 0.7946474523932063, 'support': 941.0}    | {'precision': 0.6348204570184983, 'recall': 0.6209025117071094, 'f1-score': 0.6277843538146992, 'support': 4698.0}  | {'precision': 0.8270746407046824, 'recall': 0.8796844181459567, 'f1-score': 0.8525686977299881, 'support': 2028.0}  | {'precision': 0.8729010420123449, 'recall': 0.8850010093533409, 'f1-score': 0.8789093825180433, 'support': 14861.0} | {'precision': 0.9270216962524654, 'recall': 0.8975460708488494, 'f1-score': 0.912045796342114, 'support': 10473.0}  | 0.8473   | {'precision': 0.7741871264081837, 'recall': 0.8012007274871067, 'f1-score': 0.7870678469534192, 'support': 33500.0}  | {'precision': 0.8476618534036751, 'recall': 0.8472537313432836, 'f1-score': 0.8472670786725544, 'support': 33500.0} |
-| 0.3295        | 14.0  | 574  | 0.6825          | {'precision': 0.6203966005665722, 'recall': 0.6460176991150443, 'f1-score': 0.6329479768786126, 'support': 339.0}   | {'precision': 0.8023952095808383, 'recall': 0.8375, 'f1-score': 0.819571865443425, 'support': 160.0}   | {'precision': 0.7741935483870968, 'recall': 0.8161530286928799, 'f1-score': 0.7946197620279358, 'support': 941.0}   | {'precision': 0.6377252007814196, 'recall': 0.6253724989357173, 'f1-score': 0.631488447071467, 'support': 4698.0}   | {'precision': 0.8424041646947468, 'recall': 0.8777120315581854, 'f1-score': 0.859695725670128, 'support': 2028.0}   | {'precision': 0.8764517420905086, 'recall': 0.8835879146759976, 'f1-score': 0.880005361391281, 'support': 14861.0}  | {'precision': 0.9212521874392378, 'recall': 0.904802826315287, 'f1-score': 0.9129534177946914, 'support': 10473.0}  | 0.8491   | {'precision': 0.7821169505057742, 'recall': 0.7987351427561588, 'f1-score': 0.790183222325363, 'support': 33500.0}   | {'precision': 0.8491004760503732, 'recall': 0.8491343283582089, 'f1-score': 0.8490374488030293, 'support': 33500.0} |
-| 0.3295        | 15.0  | 615  | 0.6853          | {'precision': 0.6056338028169014, 'recall': 0.6342182890855457, 'f1-score': 0.6195965417867435, 'support': 339.0}   | {'precision': 0.7894736842105263, 'recall': 0.84375, 'f1-score': 0.8157099697885197, 'support': 160.0} | {'precision': 0.7644749754661433, 'recall': 0.8278427205100957, 'f1-score': 0.7948979591836736, 'support': 941.0}   | {'precision': 0.6346823324630113, 'recall': 0.6209025117071094, 'f1-score': 0.6277168065418549, 'support': 4698.0}  | {'precision': 0.8516405135520685, 'recall': 0.8831360946745562, 'f1-score': 0.8671023965141612, 'support': 2028.0}  | {'precision': 0.8722053181637783, 'recall': 0.8872888769261826, 'f1-score': 0.879682444377731, 'support': 14861.0}  | {'precision': 0.9284868810416256, 'recall': 0.8987873579681085, 'f1-score': 0.9133957595458736, 'support': 10473.0} | 0.8488   | {'precision': 0.778085358244865, 'recall': 0.7994179786959427, 'f1-score': 0.7883002682483654, 'support': 33500.0}   | {'precision': 0.8491267909945652, 'recall': 0.8488358208955223, 'f1-score': 0.8488061974719241, 'support': 33500.0} |
-| 0.3295        | 16.0  | 656  | 0.6893          | {'precision': 0.6103151862464183, 'recall': 0.6283185840707964, 'f1-score': 0.6191860465116279, 'support': 339.0}   | {'precision': 0.7816091954022989, 'recall': 0.85, 'f1-score': 0.8143712574850299, 'support': 160.0}    | {'precision': 0.761252446183953, 'recall': 0.8267800212539851, 'f1-score': 0.792664289353031, 'support': 941.0}     | {'precision': 0.636103781882146, 'recall': 0.6157939548744147, 'f1-score': 0.6257841228639411, 'support': 4698.0}   | {'precision': 0.8445692883895131, 'recall': 0.8895463510848126, 'f1-score': 0.866474543707973, 'support': 2028.0}   | {'precision': 0.8711272247857613, 'recall': 0.8892402933853711, 'f1-score': 0.8800905730744897, 'support': 14861.0} | {'precision': 0.9305019305019305, 'recall': 0.897450587224291, 'f1-score': 0.9136774569845436, 'support': 10473.0}  | 0.8489   | {'precision': 0.7764970076274315, 'recall': 0.7995899702705245, 'f1-score': 0.7874640414258051, 'support': 33500.0}  | {'precision': 0.8489690555547813, 'recall': 0.8488955223880597, 'f1-score': 0.8486929780465652, 'support': 33500.0} |
 ### Framework versions

       name: essays_su_g
       type: essays_su_g
       config: full_labels
+      split: train[80%:100%]
       args: full_labels
     metrics:
     - name: Accuracy
       type: accuracy
+      value: 0.8485100836380752
 ---
 <!-- 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: 0.6830
+- B-claim: {'precision': 0.5970695970695971, 'recall': 0.6014760147601476, 'f1-score': 0.5992647058823529, 'support': 271.0}
+- B-majorclaim: {'precision': 0.6627218934911243, 'recall': 0.8057553956834532, 'f1-score': 0.7272727272727272, 'support': 139.0}
+- B-premise: {'precision': 0.7686567164179104, 'recall': 0.8135860979462876, 'f1-score': 0.7904834996162702, 'support': 633.0}
+- I-claim: {'precision': 0.6353591160220995, 'recall': 0.6035991002249438, 'f1-score': 0.6190720328120995, 'support': 4001.0}
+- I-majorclaim: {'precision': 0.783796740172579, 'recall': 0.812220566318927, 'f1-score': 0.7977555501341791, 'support': 2013.0}
+- I-premise: {'precision': 0.8706603131381893, 'recall': 0.9026111503175723, 'f1-score': 0.8863478863478863, 'support': 11336.0}
+- O: {'precision': 0.9430536761389264, 'recall': 0.9064600043355734, 'f1-score': 0.92439482701448, 'support': 9226.0}
+- Accuracy: 0.8485
+- Macro avg: {'precision': 0.751616864635775, 'recall': 0.7779583327981293, 'f1-score': 0.7635130327257136, 'support': 27619.0}
+- Weighted avg: {'precision': 0.848356460858747, 'recall': 0.8485100836380752, 'f1-score': 0.8480670241145107, 'support': 27619.0}
 ## 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   | 0.6934          | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 271.0}                                                  | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 139.0}                                               | {'precision': 0.780952380952381, 'recall': 0.12954186413902052, 'f1-score': 0.22222222222222218, 'support': 633.0} | {'precision': 0.42653061224489797, 'recall': 0.26118470382404396, 'f1-score': 0.3239807781739265, 'support': 4001.0} | {'precision': 0.5735174654752234, 'recall': 0.35072031793343267, 'f1-score': 0.43526510480887787, 'support': 2013.0} | {'precision': 0.7484180515958556, 'recall': 0.9494530698659139, 'f1-score': 0.8370338686471983, 'support': 11336.0} | {'precision': 0.8500846381718155, 'recall': 0.8709083026230219, 'f1-score': 0.8603704893457543, 'support': 9226.0} | 0.7470   | {'precision': 0.48278616406288194, 'recall': 0.3659726083407761, 'f1-score': 0.3826960661711399, 'support': 27619.0} | {'precision': 0.7126373293529855, 'recall': 0.7469857706651218, 'f1-score': 0.7147071394985115, 'support': 27619.0} |
+| No log        | 2.0   | 82   | 0.5074          | {'precision': 0.15789473684210525, 'recall': 0.02214022140221402, 'f1-score': 0.038834951456310676, 'support': 271.0} | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 139.0}                                               | {'precision': 0.5579937304075235, 'recall': 0.8436018957345972, 'f1-score': 0.6716981132075472, 'support': 633.0}  | {'precision': 0.5924329501915708, 'recall': 0.3091727068232942, 'f1-score': 0.4063064542617836, 'support': 4001.0}   | {'precision': 0.6722197208464655, 'recall': 0.741679085941381, 'f1-score': 0.7052432687765706, 'support': 2013.0}    | {'precision': 0.7885760494008675, 'recall': 0.9462773465067043, 'f1-score': 0.8602590320381731, 'support': 11336.0} | {'precision': 0.928374655647383, 'recall': 0.8766529373509646, 'f1-score': 0.9017727728843795, 'support': 9226.0}  | 0.7996   | {'precision': 0.5282131204765593, 'recall': 0.5342177419655937, 'f1-score': 0.5120163703749664, 'support': 27619.0}  | {'precision': 0.7829387271741762, 'recall': 0.7996306890184294, 'f1-score': 0.7803558416622501, 'support': 27619.0} |
+| No log        | 3.0   | 123  | 0.4456          | {'precision': 0.4748427672955975, 'recall': 0.5571955719557196, 'f1-score': 0.5127334465195247, 'support': 271.0}     | {'precision': 0.6712328767123288, 'recall': 0.35251798561151076, 'f1-score': 0.4622641509433962, 'support': 139.0} | {'precision': 0.7294117647058823, 'recall': 0.7835703001579779, 'f1-score': 0.7555217060167556, 'support': 633.0}  | {'precision': 0.5786846103755156, 'recall': 0.6663334166458386, 'f1-score': 0.6194237918215614, 'support': 4001.0}   | {'precision': 0.7035775127768313, 'recall': 0.8206656731246895, 'f1-score': 0.7576243980738363, 'support': 2013.0}   | {'precision': 0.8988648090815273, 'recall': 0.8451834862385321, 'f1-score': 0.8711979995453512, 'support': 11336.0} | {'precision': 0.9345198119543318, 'recall': 0.9049425536527206, 'f1-score': 0.9194933920704845, 'support': 9226.0} | 0.8307   | {'precision': 0.7130191647002879, 'recall': 0.704344141055284, 'f1-score': 0.6997512692844158, 'support': 27619.0}   | {'precision': 0.8409693083395489, 'recall': 0.8307324667801151, 'f1-score': 0.8343535169045084, 'support': 27619.0} |
+| No log        | 4.0   | 164  | 0.4313          | {'precision': 0.5757575757575758, 'recall': 0.5608856088560885, 'f1-score': 0.5682242990654206, 'support': 271.0}     | {'precision': 0.6643835616438356, 'recall': 0.697841726618705, 'f1-score': 0.6807017543859649, 'support': 139.0}   | {'precision': 0.7650695517774343, 'recall': 0.7819905213270142, 'f1-score': 0.7734375, 'support': 633.0}           | {'precision': 0.650827067669173, 'recall': 0.540864783804049, 'f1-score': 0.5907725907725908, 'support': 4001.0}     | {'precision': 0.7433227704843821, 'recall': 0.8156979632389468, 'f1-score': 0.7778304121269539, 'support': 2013.0}   | {'precision': 0.8642255892255892, 'recall': 0.9056986591390261, 'f1-score': 0.8844762232942798, 'support': 11336.0} | {'precision': 0.925120244862265, 'recall': 0.917298937784522, 'f1-score': 0.921192990094699, 'support': 9226.0}    | 0.8429   | {'precision': 0.7412437659171793, 'recall': 0.7457540286811932, 'f1-score': 0.7423765385342728, 'support': 27619.0}  | {'precision': 0.8387326527993001, 'recall': 0.8428980049965603, 'f1-score': 0.8397478190947073, 'support': 27619.0} |
+| No log        | 5.0   | 205  | 0.4380          | {'precision': 0.5848375451263538, 'recall': 0.5977859778597786, 'f1-score': 0.5912408759124088, 'support': 271.0}     | {'precision': 0.654320987654321, 'recall': 0.762589928057554, 'f1-score': 0.7043189368770765, 'support': 139.0}    | {'precision': 0.7932148626817448, 'recall': 0.7756714060031595, 'f1-score': 0.7843450479233227, 'support': 633.0}  | {'precision': 0.6200329179402775, 'recall': 0.6590852286928268, 'f1-score': 0.6389629270656652, 'support': 4001.0}   | {'precision': 0.7448522829006267, 'recall': 0.8266269249875807, 'f1-score': 0.7836119613845066, 'support': 2013.0}   | {'precision': 0.8884649511978705, 'recall': 0.8832921665490473, 'f1-score': 0.8858710076970716, 'support': 11336.0} | {'precision': 0.9446842344388914, 'recall': 0.9014740949490571, 'f1-score': 0.922573488630061, 'support': 9226.0}  | 0.8469   | {'precision': 0.7472011117057266, 'recall': 0.7723608181570006, 'f1-score': 0.7587034636414446, 'support': 27619.0}  | {'precision': 0.851550794162027, 'recall': 0.846880770484087, 'f1-score': 0.8487785699607272, 'support': 27619.0}   |
+| No log        | 6.0   | 246  | 0.4586          | {'precision': 0.5868055555555556, 'recall': 0.6236162361623616, 'f1-score': 0.6046511627906976, 'support': 271.0}     | {'precision': 0.6733333333333333, 'recall': 0.7266187050359713, 'f1-score': 0.698961937716263, 'support': 139.0}   | {'precision': 0.7458893871449925, 'recall': 0.7883096366508688, 'f1-score': 0.7665130568356375, 'support': 633.0}  | {'precision': 0.6227261989133003, 'recall': 0.6588352911772057, 'f1-score': 0.640272042749575, 'support': 4001.0}    | {'precision': 0.8159871244635193, 'recall': 0.7555886736214605, 'f1-score': 0.7846272891410886, 'support': 2013.0}   | {'precision': 0.8951378809869376, 'recall': 0.870501058574453, 'f1-score': 0.8826475849731664, 'support': 11336.0}  | {'precision': 0.9149185390267277, 'recall': 0.9312811619336657, 'f1-score': 0.923027340602675, 'support': 9226.0}  | 0.8467   | {'precision': 0.750685431346338, 'recall': 0.7649643947365695, 'f1-score': 0.7572429164013005, 'support': 27619.0}   | {'precision': 0.8489516884853674, 'recall': 0.846735942648177, 'f1-score': 0.8475667251954796, 'support': 27619.0}  |
+| No log        | 7.0   | 287  | 0.5199          | {'precision': 0.6106194690265486, 'recall': 0.5092250922509225, 'f1-score': 0.5553319919517101, 'support': 271.0}     | {'precision': 0.6687898089171974, 'recall': 0.7553956834532374, 'f1-score': 0.7094594594594595, 'support': 139.0}  | {'precision': 0.7169811320754716, 'recall': 0.8404423380726699, 'f1-score': 0.7738181818181818, 'support': 633.0}  | {'precision': 0.6686178861788618, 'recall': 0.5138715321169708, 'f1-score': 0.58111927642736, 'support': 4001.0}     | {'precision': 0.825, 'recall': 0.7704918032786885, 'f1-score': 0.7968147957873105, 'support': 2013.0}                | {'precision': 0.8428010576075635, 'recall': 0.9279287226534932, 'f1-score': 0.8833186379476844, 'support': 11336.0} | {'precision': 0.9325458158533892, 'recall': 0.9155647084326902, 'f1-score': 0.9239772478669874, 'support': 9226.0} | 0.8454   | {'precision': 0.752193595665576, 'recall': 0.747559982894096, 'f1-score': 0.7462627987512419, 'support': 27619.0}    | {'precision': 0.8402119687481008, 'recall': 0.8453600782070314, 'f1-score': 0.8402149723478831, 'support': 27619.0} |
+| No log        | 8.0   | 328  | 0.5409          | {'precision': 0.5830258302583026, 'recall': 0.5830258302583026, 'f1-score': 0.5830258302583026, 'support': 271.0}     | {'precision': 0.6145251396648045, 'recall': 0.7913669064748201, 'f1-score': 0.6918238993710691, 'support': 139.0}  | {'precision': 0.7553956834532374, 'recall': 0.8293838862559242, 'f1-score': 0.7906626506024096, 'support': 633.0}  | {'precision': 0.6144920061887571, 'recall': 0.5956010997250687, 'f1-score': 0.604899098870415, 'support': 4001.0}    | {'precision': 0.7724268177525968, 'recall': 0.8127173373075013, 'f1-score': 0.7920600338900993, 'support': 2013.0}   | {'precision': 0.8602069139540752, 'recall': 0.9021700776287932, 'f1-score': 0.8806889128094725, 'support': 11336.0} | {'precision': 0.9516823844452207, 'recall': 0.8859744201170605, 'f1-score': 0.9176536626438395, 'support': 9226.0} | 0.8405   | {'precision': 0.7359649679595704, 'recall': 0.7714627939667815, 'f1-score': 0.751544869777944, 'support': 27619.0}   | {'precision': 0.842412448619121, 'recall': 0.8404721387450668, 'f1-score': 0.8406905872698305, 'support': 27619.0}  |
+| No log        | 9.0   | 369  | 0.5502          | {'precision': 0.5793103448275863, 'recall': 0.6199261992619927, 'f1-score': 0.5989304812834225, 'support': 271.0}     | {'precision': 0.6503067484662577, 'recall': 0.762589928057554, 'f1-score': 0.7019867549668876, 'support': 139.0}   | {'precision': 0.7593423019431988, 'recall': 0.8025276461295419, 'f1-score': 0.7803379416282642, 'support': 633.0}  | {'precision': 0.6140224934194783, 'recall': 0.6413396650837291, 'f1-score': 0.6273838630806847, 'support': 4001.0}   | {'precision': 0.7911111111111111, 'recall': 0.7958271236959762, 'f1-score': 0.7934621099554235, 'support': 2013.0}   | {'precision': 0.8799437510986113, 'recall': 0.8832039520112914, 'f1-score': 0.8815708373690234, 'support': 11336.0} | {'precision': 0.9401009534492428, 'recall': 0.9084110123563841, 'f1-score': 0.9239843448541977, 'support': 9226.0} | 0.8452   | {'precision': 0.7448768149022124, 'recall': 0.7734036466566385, 'f1-score': 0.7582366190197004, 'support': 27619.0}  | {'precision': 0.8481724117610957, 'recall': 0.8451790434121438, 'f1-score': 0.8464972981637662, 'support': 27619.0} |
+| No log        | 10.0  | 410  | 0.6131          | {'precision': 0.5976095617529881, 'recall': 0.5535055350553506, 'f1-score': 0.5747126436781611, 'support': 271.0}     | {'precision': 0.6494252873563219, 'recall': 0.8129496402877698, 'f1-score': 0.7220447284345047, 'support': 139.0}  | {'precision': 0.7667682926829268, 'recall': 0.7946287519747235, 'f1-score': 0.7804499612102405, 'support': 633.0}  | {'precision': 0.6487764182424917, 'recall': 0.583104223944014, 'f1-score': 0.6141898117678031, 'support': 4001.0}    | {'precision': 0.7791783380018674, 'recall': 0.829110779930452, 'f1-score': 0.8033694344163658, 'support': 2013.0}    | {'precision': 0.8636249476768523, 'recall': 0.9100211714890614, 'f1-score': 0.8862162278252652, 'support': 11336.0} | {'precision': 0.9387916431394693, 'recall': 0.901040537611099, 'f1-score': 0.919528787124606, 'support': 9226.0}   | 0.8471   | {'precision': 0.7491677841218453, 'recall': 0.7691943771846387, 'f1-score': 0.7572159420652781, 'support': 27619.0}  | {'precision': 0.8455473111155869, 'recall': 0.8471342191969297, 'f1-score': 0.845592238174344, 'support': 27619.0}  |
+| No log        | 11.0  | 451  | 0.6233          | {'precision': 0.5868055555555556, 'recall': 0.6236162361623616, 'f1-score': 0.6046511627906976, 'support': 271.0}     | {'precision': 0.6549707602339181, 'recall': 0.8057553956834532, 'f1-score': 0.7225806451612903, 'support': 139.0}  | {'precision': 0.7620481927710844, 'recall': 0.7993680884676145, 'f1-score': 0.7802621434078643, 'support': 633.0}  | {'precision': 0.6177835051546392, 'recall': 0.599100224943764, 'f1-score': 0.6082984392843548, 'support': 4001.0}    | {'precision': 0.7816593886462883, 'recall': 0.8002980625931445, 'f1-score': 0.7908689248895435, 'support': 2013.0}   | {'precision': 0.8624830852503383, 'recall': 0.8996118560338744, 'f1-score': 0.8806563039723663, 'support': 11336.0} | {'precision': 0.9492612530065284, 'recall': 0.8983308042488619, 'f1-score': 0.9230940580275101, 'support': 9226.0} | 0.8429   | {'precision': 0.7450016772311931, 'recall': 0.7751543811618677, 'f1-score': 0.758630239647661, 'support': 27619.0}   | {'precision': 0.8440807587297484, 'recall': 0.8429342119555379, 'f1-score': 0.8430287828720368, 'support': 27619.0} |
+| No log        | 12.0  | 492  | 0.6488          | {'precision': 0.5888888888888889, 'recall': 0.5867158671586716, 'f1-score': 0.5878003696857672, 'support': 271.0}     | {'precision': 0.6728395061728395, 'recall': 0.7841726618705036, 'f1-score': 0.7242524916943521, 'support': 139.0}  | {'precision': 0.7496382054992764, 'recall': 0.8183254344391785, 'f1-score': 0.782477341389728, 'support': 633.0}   | {'precision': 0.6320602474448628, 'recall': 0.5873531617095726, 'f1-score': 0.6088871615494235, 'support': 4001.0}   | {'precision': 0.7818969667790082, 'recall': 0.8067560854446101, 'f1-score': 0.7941320293398534, 'support': 2013.0}   | {'precision': 0.8592370481425954, 'recall': 0.9100211714890614, 'f1-score': 0.8839002656156285, 'support': 11336.0} | {'precision': 0.948821161587119, 'recall': 0.8942120095382614, 'f1-score': 0.9207075498019084, 'support': 9226.0}  | 0.8446   | {'precision': 0.7476260035020843, 'recall': 0.7696509130928371, 'f1-score': 0.7574510298680944, 'support': 27619.0}  | {'precision': 0.8445128868904818, 'recall': 0.844563525109526, 'f1-score': 0.8437799966523624, 'support': 27619.0}  |
+| 0.3135        | 13.0  | 533  | 0.6540          | {'precision': 0.5909090909090909, 'recall': 0.5756457564575646, 'f1-score': 0.5831775700934578, 'support': 271.0}     | {'precision': 0.675, 'recall': 0.7769784172661871, 'f1-score': 0.7224080267558529, 'support': 139.0}               | {'precision': 0.7463976945244957, 'recall': 0.8183254344391785, 'f1-score': 0.7807083647324792, 'support': 633.0}  | {'precision': 0.6368118323746919, 'recall': 0.5811047238190452, 'f1-score': 0.6076842655514898, 'support': 4001.0}   | {'precision': 0.7928642220019821, 'recall': 0.7948335817188277, 'f1-score': 0.7938476804763087, 'support': 2013.0}   | {'precision': 0.8642820903094875, 'recall': 0.9016407904022583, 'f1-score': 0.8825662723426302, 'support': 11336.0} | {'precision': 0.9345991561181435, 'recall': 0.9123130283980057, 'f1-score': 0.9233216322948662, 'support': 9226.0} | 0.8453   | {'precision': 0.7486948694625559, 'recall': 0.7658345332144382, 'f1-score': 0.756244830321012, 'support': 27619.0}   | {'precision': 0.8432768932468896, 'recall': 0.8452514573300989, 'f1-score': 0.8438155256232617, 'support': 27619.0} |
+| 0.3135        | 14.0  | 574  | 0.6714          | {'precision': 0.6029411764705882, 'recall': 0.6051660516605166, 'f1-score': 0.6040515653775324, 'support': 271.0}     | {'precision': 0.6608187134502924, 'recall': 0.8129496402877698, 'f1-score': 0.7290322580645162, 'support': 139.0}  | {'precision': 0.7786259541984732, 'recall': 0.8056872037914692, 'f1-score': 0.7919254658385093, 'support': 633.0}  | {'precision': 0.6342872144919927, 'recall': 0.6038490377405649, 'f1-score': 0.6186939820742638, 'support': 4001.0}   | {'precision': 0.78125, 'recall': 0.819672131147541, 'f1-score': 0.8, 'support': 2013.0}                              | {'precision': 0.8721188321666382, 'recall': 0.9011997177134792, 'f1-score': 0.8864208242950109, 'support': 11336.0} | {'precision': 0.9428314202115687, 'recall': 0.9080858443529157, 'f1-score': 0.9251325088339223, 'support': 9226.0} | 0.8489   | {'precision': 0.7532676158556504, 'recall': 0.7795156609563223, 'f1-score': 0.7650366577833936, 'support': 27619.0}  | {'precision': 0.8488164759222332, 'recall': 0.8489445671458055, 'f1-score': 0.8485410728467069, 'support': 27619.0} |
+| 0.3135        | 15.0  | 615  | 0.6882          | {'precision': 0.5955882352941176, 'recall': 0.5977859778597786, 'f1-score': 0.5966850828729282, 'support': 271.0}     | {'precision': 0.6511627906976745, 'recall': 0.8057553956834532, 'f1-score': 0.7202572347266881, 'support': 139.0}  | {'precision': 0.7690014903129657, 'recall': 0.8151658767772512, 'f1-score': 0.7914110429447854, 'support': 633.0}  | {'precision': 0.6307486631016043, 'recall': 0.5896025993501625, 'f1-score': 0.6094819790724713, 'support': 4001.0}   | {'precision': 0.7757889778615167, 'recall': 0.8181818181818182, 'f1-score': 0.7964216634429401, 'support': 2013.0}   | {'precision': 0.8646648162166709, 'recall': 0.9068454481298518, 'f1-score': 0.8852529601722283, 'support': 11336.0} | {'precision': 0.948583180987203, 'recall': 0.8998482549317147, 'f1-score': 0.9235732562020248, 'support': 9226.0}  | 0.8464   | {'precision': 0.7479340220673932, 'recall': 0.7761693387020043, 'f1-score': 0.7604404599191524, 'support': 27619.0}  | {'precision': 0.84642642314945, 'recall': 0.8464462869763568, 'f1-score': 0.8458173441573364, 'support': 27619.0}   |
+| 0.3135        | 16.0  | 656  | 0.6830          | {'precision': 0.5970695970695971, 'recall': 0.6014760147601476, 'f1-score': 0.5992647058823529, 'support': 271.0}     | {'precision': 0.6627218934911243, 'recall': 0.8057553956834532, 'f1-score': 0.7272727272727272, 'support': 139.0}  | {'precision': 0.7686567164179104, 'recall': 0.8135860979462876, 'f1-score': 0.7904834996162702, 'support': 633.0}  | {'precision': 0.6353591160220995, 'recall': 0.6035991002249438, 'f1-score': 0.6190720328120995, 'support': 4001.0}   | {'precision': 0.783796740172579, 'recall': 0.812220566318927, 'f1-score': 0.7977555501341791, 'support': 2013.0}     | {'precision': 0.8706603131381893, 'recall': 0.9026111503175723, 'f1-score': 0.8863478863478863, 'support': 11336.0} | {'precision': 0.9430536761389264, 'recall': 0.9064600043355734, 'f1-score': 0.92439482701448, 'support': 9226.0}   | 0.8485   | {'precision': 0.751616864635775, 'recall': 0.7779583327981293, 'f1-score': 0.7635130327257136, 'support': 27619.0}   | {'precision': 0.848356460858747, 'recall': 0.8485100836380752, 'f1-score': 0.8480670241145107, 'support': 27619.0}  |
 ### Framework versions

meta_data/README_s42_e16.md CHANGED Viewed

@@ -17,12 +17,12 @@ model-index:
       name: essays_su_g
       type: essays_su_g
       config: full_labels
-      split: train[60%:80%]
       args: full_labels
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8488955223880597
 ---
 <!-- 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: 0.6893
-- B-claim: {'precision': 0.6103151862464183, 'recall': 0.6283185840707964, 'f1-score': 0.6191860465116279, 'support': 339.0}
-- B-majorclaim: {'precision': 0.7816091954022989, 'recall': 0.85, 'f1-score': 0.8143712574850299, 'support': 160.0}
-- B-premise: {'precision': 0.761252446183953, 'recall': 0.8267800212539851, 'f1-score': 0.792664289353031, 'support': 941.0}
-- I-claim: {'precision': 0.636103781882146, 'recall': 0.6157939548744147, 'f1-score': 0.6257841228639411, 'support': 4698.0}
-- I-majorclaim: {'precision': 0.8445692883895131, 'recall': 0.8895463510848126, 'f1-score': 0.866474543707973, 'support': 2028.0}
-- I-premise: {'precision': 0.8711272247857613, 'recall': 0.8892402933853711, 'f1-score': 0.8800905730744897, 'support': 14861.0}
-- O: {'precision': 0.9305019305019305, 'recall': 0.897450587224291, 'f1-score': 0.9136774569845436, 'support': 10473.0}
-- Accuracy: 0.8489
-- Macro avg: {'precision': 0.7764970076274315, 'recall': 0.7995899702705245, 'f1-score': 0.7874640414258051, 'support': 33500.0}
-- Weighted avg: {'precision': 0.8489690555547813, 'recall': 0.8488955223880597, 'f1-score': 0.8486929780465652, 'support': 33500.0}
 ## 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   | 0.7635          | {'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': 0.8299319727891157, 'recall': 0.12964930924548354, 'f1-score': 0.22426470588235295, 'support': 941.0} | {'precision': 0.423873640600725, 'recall': 0.348446147296722, 'f1-score': 0.38247663551401867, 'support': 4698.0}   | {'precision': 0.5125673249551167, 'recall': 0.28155818540433925, 'f1-score': 0.3634627625716104, 'support': 2028.0} | {'precision': 0.8110747093209996, 'recall': 0.8496063521970257, 'f1-score': 0.8298935191271198, 'support': 14861.0} | {'precision': 0.7380952380952381, 'recall': 0.9027976701995608, 'f1-score': 0.8121805609242796, 'support': 10473.0} | 0.7287   | {'precision': 0.47364898368017067, 'recall': 0.3588653806204473, 'f1-score': 0.3731825977170545, 'support': 33500.0} | {'precision': 0.7043362259324342, 'recall': 0.7286865671641791, 'f1-score': 0.7040007584084623, 'support': 33500.0} |
-| No log        | 2.0   | 82   | 0.5587          | {'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': 0.5819477434679335, 'recall': 0.7810839532412327, 'f1-score': 0.6669691470054446, 'support': 941.0}   | {'precision': 0.559799275160301, 'recall': 0.4274159216687952, 'f1-score': 0.48473144236572113, 'support': 4698.0}  | {'precision': 0.6312089971883786, 'recall': 0.6642011834319527, 'f1-score': 0.6472849591542528, 'support': 2028.0}  | {'precision': 0.8200934579439252, 'recall': 0.9211358589596932, 'f1-score': 0.8676829461540899, 'support': 14861.0} | {'precision': 0.9105252442996743, 'recall': 0.8541010216747827, 'f1-score': 0.8814110459673844, 'support': 10473.0} | 0.7977   | {'precision': 0.5005106740086018, 'recall': 0.5211339912823509, 'f1-score': 0.506868505806699, 'support': 33500.0}   | {'precision': 0.7815218337211824, 'recall': 0.7977313432835821, 'f1-score': 0.7863652038192075, 'support': 33500.0} |
-| No log        | 3.0   | 123  | 0.5104          | {'precision': 0.4175824175824176, 'recall': 0.22418879056047197, 'f1-score': 0.29174664107485604, 'support': 339.0} | {'precision': 0.8823529411764706, 'recall': 0.09375, 'f1-score': 0.1694915254237288, 'support': 160.0} | {'precision': 0.6546521374685667, 'recall': 0.8299681190223167, 'f1-score': 0.731958762886598, 'support': 941.0}    | {'precision': 0.629277566539924, 'recall': 0.35227756492124307, 'f1-score': 0.45169213973799127, 'support': 4698.0} | {'precision': 0.7788510421962379, 'recall': 0.7554240631163708, 'f1-score': 0.7669586983729662, 'support': 2028.0}  | {'precision': 0.7908845678318535, 'recall': 0.9469753044882578, 'f1-score': 0.8619200734956362, 'support': 14861.0} | {'precision': 0.9332098384274982, 'recall': 0.8658455074954645, 'f1-score': 0.8982664685487864, 'support': 10473.0} | 0.8119   | {'precision': 0.7266872158889954, 'recall': 0.5812041928005893, 'f1-score': 0.5960049013629376, 'support': 33500.0}  | {'precision': 0.804819781883149, 'recall': 0.8119402985074626, 'f1-score': 0.7972768597429257, 'support': 33500.0}  |
-| No log        | 4.0   | 164  | 0.4638          | {'precision': 0.6144200626959248, 'recall': 0.5781710914454278, 'f1-score': 0.5957446808510639, 'support': 339.0}   | {'precision': 0.7910447761194029, 'recall': 0.6625, 'f1-score': 0.7210884353741497, 'support': 160.0}  | {'precision': 0.7529411764705882, 'recall': 0.8161530286928799, 'f1-score': 0.7832738398776133, 'support': 941.0}   | {'precision': 0.6121971950701233, 'recall': 0.6132396764580673, 'f1-score': 0.6127179923436835, 'support': 4698.0}  | {'precision': 0.7631464580617123, 'recall': 0.8658777120315582, 'f1-score': 0.8112728112728113, 'support': 2028.0}  | {'precision': 0.8770213344204376, 'recall': 0.8685821950070655, 'f1-score': 0.8727813651577132, 'support': 14861.0} | {'precision': 0.9097262667443214, 'recall': 0.8948725293612145, 'f1-score': 0.9022382671480144, 'support': 10473.0} | 0.8354   | {'precision': 0.7600710385117873, 'recall': 0.7570566047137447, 'f1-score': 0.7570167702892928, 'support': 33500.0}  | {'precision': 0.8366601162482339, 'recall': 0.8354328358208956, 'f1-score': 0.8357536689114934, 'support': 33500.0} |
-| No log        | 5.0   | 205  | 0.4939          | {'precision': 0.6254295532646048, 'recall': 0.5368731563421829, 'f1-score': 0.5777777777777778, 'support': 339.0}   | {'precision': 0.7636363636363637, 'recall': 0.7875, 'f1-score': 0.7753846153846152, 'support': 160.0}  | {'precision': 0.7188898836168308, 'recall': 0.8533475026567482, 'f1-score': 0.7803692905733722, 'support': 941.0}   | {'precision': 0.6303191489361702, 'recall': 0.5549169859514687, 'f1-score': 0.5902196060674665, 'support': 4698.0}  | {'precision': 0.8303317535545024, 'recall': 0.863905325443787, 'f1-score': 0.8467858869018849, 'support': 2028.0}   | {'precision': 0.8650767507740957, 'recall': 0.8835879146759976, 'f1-score': 0.8742343541944074, 'support': 14861.0} | {'precision': 0.904970481812988, 'recall': 0.9074763678029218, 'f1-score': 0.9062216924910609, 'support': 10473.0}  | 0.8390   | {'precision': 0.7626648479422222, 'recall': 0.7696581789818724, 'f1-score': 0.7644276033415122, 'support': 33500.0}  | {'precision': 0.8355072066989216, 'recall': 0.8389552238805971, 'f1-score': 0.8366342005564686, 'support': 33500.0} |
-| No log        | 6.0   | 246  | 0.4979          | {'precision': 0.6232876712328768, 'recall': 0.5368731563421829, 'f1-score': 0.5768621236133122, 'support': 339.0}   | {'precision': 0.782051282051282, 'recall': 0.7625, 'f1-score': 0.7721518987341772, 'support': 160.0}   | {'precision': 0.7490530303030303, 'recall': 0.8405951115834219, 'f1-score': 0.7921882824236354, 'support': 941.0}   | {'precision': 0.6594274432379073, 'recall': 0.5687526607066837, 'f1-score': 0.6107428571428571, 'support': 4698.0}  | {'precision': 0.8388861263053208, 'recall': 0.8318540433925049, 'f1-score': 0.8353552859618717, 'support': 2028.0}  | {'precision': 0.8607000386050702, 'recall': 0.9001413094677343, 'f1-score': 0.8799789494457783, 'support': 14861.0} | {'precision': 0.9164661726494081, 'recall': 0.9092905566695312, 'f1-score': 0.912864263803681, 'support': 10473.0}  | 0.8464   | {'precision': 0.7756959663406994, 'recall': 0.7642866911660084, 'f1-score': 0.7685919515893305, 'support': 33500.0}  | {'precision': 0.8426730244638024, 'recall': 0.8463880597014926, 'f1-score': 0.843752680680015, 'support': 33500.0}  |
-| No log        | 7.0   | 287  | 0.5638          | {'precision': 0.6418439716312057, 'recall': 0.5339233038348082, 'f1-score': 0.5829307568438002, 'support': 339.0}   | {'precision': 0.7758620689655172, 'recall': 0.84375, 'f1-score': 0.8083832335329341, 'support': 160.0} | {'precision': 0.7203463203463204, 'recall': 0.8841657810839533, 'f1-score': 0.7938931297709925, 'support': 941.0}   | {'precision': 0.7018554062699937, 'recall': 0.4670072371221797, 'f1-score': 0.560838445807771, 'support': 4698.0}   | {'precision': 0.8422548555187115, 'recall': 0.8767258382642998, 'f1-score': 0.8591447209470888, 'support': 2028.0}  | {'precision': 0.834623927006423, 'recall': 0.9356032568467801, 'f1-score': 0.882233502538071, 'support': 14861.0}   | {'precision': 0.9340538376863805, 'recall': 0.8912441516279958, 'f1-score': 0.9121469754715138, 'support': 10473.0} | 0.8465   | {'precision': 0.7786914839177931, 'recall': 0.7760599383971453, 'f1-score': 0.7713672521303102, 'support': 33500.0}  | {'precision': 0.8421095669207056, 'recall': 0.8465074626865672, 'f1-score': 0.8392525416975183, 'support': 33500.0} |
-| No log        | 8.0   | 328  | 0.5493          | {'precision': 0.5994550408719346, 'recall': 0.6489675516224189, 'f1-score': 0.623229461756374, 'support': 339.0}    | {'precision': 0.7687861271676301, 'recall': 0.83125, 'f1-score': 0.7987987987987989, 'support': 160.0} | {'precision': 0.7347504621072088, 'recall': 0.844845908607864, 'f1-score': 0.7859614434008898, 'support': 941.0}    | {'precision': 0.6259211096662332, 'recall': 0.6147296722009365, 'f1-score': 0.620274914089347, 'support': 4698.0}   | {'precision': 0.8396803008932769, 'recall': 0.8806706114398422, 'f1-score': 0.8596871239470517, 'support': 2028.0}  | {'precision': 0.8634082763115021, 'recall': 0.8915281609582127, 'f1-score': 0.8772429318678407, 'support': 14861.0} | {'precision': 0.9433210784313726, 'recall': 0.8819822400458321, 'f1-score': 0.9116210214655811, 'support': 10473.0} | 0.8450   | {'precision': 0.7679031993498798, 'recall': 0.7991391635535867, 'f1-score': 0.782402242189412, 'support': 33500.0}   | {'precision': 0.8469129043625616, 'recall': 0.8450149253731343, 'f1-score': 0.8453815974816967, 'support': 33500.0} |
-| No log        | 9.0   | 369  | 0.5795          | {'precision': 0.6209150326797386, 'recall': 0.56047197640118, 'f1-score': 0.5891472868217054, 'support': 339.0}     | {'precision': 0.810126582278481, 'recall': 0.8, 'f1-score': 0.8050314465408804, 'support': 160.0}      | {'precision': 0.7478591817316841, 'recall': 0.8352816153028693, 'f1-score': 0.7891566265060241, 'support': 941.0}   | {'precision': 0.6493925117778329, 'recall': 0.5574712643678161, 'f1-score': 0.5999312793494446, 'support': 4698.0}  | {'precision': 0.8825079030558483, 'recall': 0.8259368836291914, 'f1-score': 0.8532857870606215, 'support': 2028.0}  | {'precision': 0.8624886112195757, 'recall': 0.8917973218491353, 'f1-score': 0.8768981374268038, 'support': 14861.0} | {'precision': 0.8974550898203593, 'recall': 0.9158789267640599, 'f1-score': 0.9065734133547564, 'support': 10473.0} | 0.8431   | {'precision': 0.7815349875090741, 'recall': 0.7695482840448931, 'f1-score': 0.7742891395800339, 'support': 33500.0}  | {'precision': 0.8388330863882018, 'recall': 0.8430746268656717, 'f1-score': 0.840184765735164, 'support': 33500.0}  |
-| No log        | 10.0  | 410  | 0.5960          | {'precision': 0.6303630363036303, 'recall': 0.5634218289085545, 'f1-score': 0.5950155763239875, 'support': 339.0}   | {'precision': 0.8, 'recall': 0.825, 'f1-score': 0.8123076923076924, 'support': 160.0}                  | {'precision': 0.7326642335766423, 'recall': 0.8533475026567482, 'f1-score': 0.7884143348060874, 'support': 941.0}   | {'precision': 0.666921508664628, 'recall': 0.5570455512984248, 'f1-score': 0.6070517281373231, 'support': 4698.0}   | {'precision': 0.8839779005524862, 'recall': 0.8678500986193294, 'f1-score': 0.8758397611346106, 'support': 2028.0}  | {'precision': 0.851998491704374, 'recall': 0.9122535495592491, 'f1-score': 0.8810970656094628, 'support': 14861.0}  | {'precision': 0.9333267385498071, 'recall': 0.900887997708393, 'f1-score': 0.9168205227869012, 'support': 10473.0}  | 0.8506   | {'precision': 0.7856074156216526, 'recall': 0.7828295041072427, 'f1-score': 0.7823638115865806, 'support': 33500.0}  | {'precision': 0.8475616436173209, 'recall': 0.8505970149253731, 'f1-score': 0.8476881875144826, 'support': 33500.0} |
-| No log        | 11.0  | 451  | 0.5954          | {'precision': 0.6235294117647059, 'recall': 0.6253687315634219, 'f1-score': 0.6244477172312225, 'support': 339.0}   | {'precision': 0.7861271676300579, 'recall': 0.85, 'f1-score': 0.8168168168168167, 'support': 160.0}    | {'precision': 0.7670286278381047, 'recall': 0.8257173219978746, 'f1-score': 0.7952917093142272, 'support': 941.0}   | {'precision': 0.6513114392770554, 'recall': 0.6289910600255428, 'f1-score': 0.639956686518679, 'support': 4698.0}   | {'precision': 0.8176156583629893, 'recall': 0.9063116370808678, 'f1-score': 0.8596819457436857, 'support': 2028.0}  | {'precision': 0.8765022242878959, 'recall': 0.8882982302671422, 'f1-score': 0.8823608047590401, 'support': 14861.0} | {'precision': 0.9289099526066351, 'recall': 0.8983099398453165, 'f1-score': 0.9133537206931702, 'support': 10473.0} | 0.8516   | {'precision': 0.7787177831096349, 'recall': 0.8032852743971665, 'f1-score': 0.7902727715824059, 'support': 33500.0}  | {'precision': 0.8516743266232883, 'recall': 0.8515522388059702, 'f1-score': 0.8513139373395039, 'support': 33500.0} |
-| No log        | 12.0  | 492  | 0.6606          | {'precision': 0.5913978494623656, 'recall': 0.6489675516224189, 'f1-score': 0.6188466947960619, 'support': 339.0}   | {'precision': 0.7771428571428571, 'recall': 0.85, 'f1-score': 0.8119402985074626, 'support': 160.0}    | {'precision': 0.7609126984126984, 'recall': 0.8150903294367694, 'f1-score': 0.7870702924576707, 'support': 941.0}   | {'precision': 0.6260370134014039, 'recall': 0.6264367816091954, 'f1-score': 0.6262368337057134, 'support': 4698.0}  | {'precision': 0.827490774907749, 'recall': 0.8846153846153846, 'f1-score': 0.8551000953288845, 'support': 2028.0}   | {'precision': 0.8761073825503356, 'recall': 0.8784065675257385, 'f1-score': 0.8772554685662445, 'support': 14861.0} | {'precision': 0.9252161949685535, 'recall': 0.8989783252172252, 'f1-score': 0.9119085670008232, 'support': 10473.0} | 0.8456   | {'precision': 0.7691863958351375, 'recall': 0.8003564200038189, 'f1-score': 0.784051178623266, 'support': 33500.0}   | {'precision': 0.8468579038739062, 'recall': 0.8456417910447761, 'f1-score': 0.8460850209295142, 'support': 33500.0} |
-| 0.3295        | 13.0  | 533  | 0.6498          | {'precision': 0.6098901098901099, 'recall': 0.6548672566371682, 'f1-score': 0.631578947368421, 'support': 339.0}    | {'precision': 0.7771428571428571, 'recall': 0.85, 'f1-score': 0.8119402985074626, 'support': 160.0}    | {'precision': 0.7704590818363274, 'recall': 0.820403825717322, 'f1-score': 0.7946474523932063, 'support': 941.0}    | {'precision': 0.6348204570184983, 'recall': 0.6209025117071094, 'f1-score': 0.6277843538146992, 'support': 4698.0}  | {'precision': 0.8270746407046824, 'recall': 0.8796844181459567, 'f1-score': 0.8525686977299881, 'support': 2028.0}  | {'precision': 0.8729010420123449, 'recall': 0.8850010093533409, 'f1-score': 0.8789093825180433, 'support': 14861.0} | {'precision': 0.9270216962524654, 'recall': 0.8975460708488494, 'f1-score': 0.912045796342114, 'support': 10473.0}  | 0.8473   | {'precision': 0.7741871264081837, 'recall': 0.8012007274871067, 'f1-score': 0.7870678469534192, 'support': 33500.0}  | {'precision': 0.8476618534036751, 'recall': 0.8472537313432836, 'f1-score': 0.8472670786725544, 'support': 33500.0} |
-| 0.3295        | 14.0  | 574  | 0.6825          | {'precision': 0.6203966005665722, 'recall': 0.6460176991150443, 'f1-score': 0.6329479768786126, 'support': 339.0}   | {'precision': 0.8023952095808383, 'recall': 0.8375, 'f1-score': 0.819571865443425, 'support': 160.0}   | {'precision': 0.7741935483870968, 'recall': 0.8161530286928799, 'f1-score': 0.7946197620279358, 'support': 941.0}   | {'precision': 0.6377252007814196, 'recall': 0.6253724989357173, 'f1-score': 0.631488447071467, 'support': 4698.0}   | {'precision': 0.8424041646947468, 'recall': 0.8777120315581854, 'f1-score': 0.859695725670128, 'support': 2028.0}   | {'precision': 0.8764517420905086, 'recall': 0.8835879146759976, 'f1-score': 0.880005361391281, 'support': 14861.0}  | {'precision': 0.9212521874392378, 'recall': 0.904802826315287, 'f1-score': 0.9129534177946914, 'support': 10473.0}  | 0.8491   | {'precision': 0.7821169505057742, 'recall': 0.7987351427561588, 'f1-score': 0.790183222325363, 'support': 33500.0}   | {'precision': 0.8491004760503732, 'recall': 0.8491343283582089, 'f1-score': 0.8490374488030293, 'support': 33500.0} |
-| 0.3295        | 15.0  | 615  | 0.6853          | {'precision': 0.6056338028169014, 'recall': 0.6342182890855457, 'f1-score': 0.6195965417867435, 'support': 339.0}   | {'precision': 0.7894736842105263, 'recall': 0.84375, 'f1-score': 0.8157099697885197, 'support': 160.0} | {'precision': 0.7644749754661433, 'recall': 0.8278427205100957, 'f1-score': 0.7948979591836736, 'support': 941.0}   | {'precision': 0.6346823324630113, 'recall': 0.6209025117071094, 'f1-score': 0.6277168065418549, 'support': 4698.0}  | {'precision': 0.8516405135520685, 'recall': 0.8831360946745562, 'f1-score': 0.8671023965141612, 'support': 2028.0}  | {'precision': 0.8722053181637783, 'recall': 0.8872888769261826, 'f1-score': 0.879682444377731, 'support': 14861.0}  | {'precision': 0.9284868810416256, 'recall': 0.8987873579681085, 'f1-score': 0.9133957595458736, 'support': 10473.0} | 0.8488   | {'precision': 0.778085358244865, 'recall': 0.7994179786959427, 'f1-score': 0.7883002682483654, 'support': 33500.0}   | {'precision': 0.8491267909945652, 'recall': 0.8488358208955223, 'f1-score': 0.8488061974719241, 'support': 33500.0} |
-| 0.3295        | 16.0  | 656  | 0.6893          | {'precision': 0.6103151862464183, 'recall': 0.6283185840707964, 'f1-score': 0.6191860465116279, 'support': 339.0}   | {'precision': 0.7816091954022989, 'recall': 0.85, 'f1-score': 0.8143712574850299, 'support': 160.0}    | {'precision': 0.761252446183953, 'recall': 0.8267800212539851, 'f1-score': 0.792664289353031, 'support': 941.0}     | {'precision': 0.636103781882146, 'recall': 0.6157939548744147, 'f1-score': 0.6257841228639411, 'support': 4698.0}   | {'precision': 0.8445692883895131, 'recall': 0.8895463510848126, 'f1-score': 0.866474543707973, 'support': 2028.0}   | {'precision': 0.8711272247857613, 'recall': 0.8892402933853711, 'f1-score': 0.8800905730744897, 'support': 14861.0} | {'precision': 0.9305019305019305, 'recall': 0.897450587224291, 'f1-score': 0.9136774569845436, 'support': 10473.0}  | 0.8489   | {'precision': 0.7764970076274315, 'recall': 0.7995899702705245, 'f1-score': 0.7874640414258051, 'support': 33500.0}  | {'precision': 0.8489690555547813, 'recall': 0.8488955223880597, 'f1-score': 0.8486929780465652, 'support': 33500.0} |
 ### Framework versions

       name: essays_su_g
       type: essays_su_g
       config: full_labels
+      split: train[80%:100%]
       args: full_labels
     metrics:
     - name: Accuracy
       type: accuracy
+      value: 0.8485100836380752
 ---
 <!-- 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: 0.6830
+- B-claim: {'precision': 0.5970695970695971, 'recall': 0.6014760147601476, 'f1-score': 0.5992647058823529, 'support': 271.0}
+- B-majorclaim: {'precision': 0.6627218934911243, 'recall': 0.8057553956834532, 'f1-score': 0.7272727272727272, 'support': 139.0}
+- B-premise: {'precision': 0.7686567164179104, 'recall': 0.8135860979462876, 'f1-score': 0.7904834996162702, 'support': 633.0}
+- I-claim: {'precision': 0.6353591160220995, 'recall': 0.6035991002249438, 'f1-score': 0.6190720328120995, 'support': 4001.0}
+- I-majorclaim: {'precision': 0.783796740172579, 'recall': 0.812220566318927, 'f1-score': 0.7977555501341791, 'support': 2013.0}
+- I-premise: {'precision': 0.8706603131381893, 'recall': 0.9026111503175723, 'f1-score': 0.8863478863478863, 'support': 11336.0}
+- O: {'precision': 0.9430536761389264, 'recall': 0.9064600043355734, 'f1-score': 0.92439482701448, 'support': 9226.0}
+- Accuracy: 0.8485
+- Macro avg: {'precision': 0.751616864635775, 'recall': 0.7779583327981293, 'f1-score': 0.7635130327257136, 'support': 27619.0}
+- Weighted avg: {'precision': 0.848356460858747, 'recall': 0.8485100836380752, 'f1-score': 0.8480670241145107, 'support': 27619.0}
 ## 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   | 0.6934          | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 271.0}                                                  | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 139.0}                                               | {'precision': 0.780952380952381, 'recall': 0.12954186413902052, 'f1-score': 0.22222222222222218, 'support': 633.0} | {'precision': 0.42653061224489797, 'recall': 0.26118470382404396, 'f1-score': 0.3239807781739265, 'support': 4001.0} | {'precision': 0.5735174654752234, 'recall': 0.35072031793343267, 'f1-score': 0.43526510480887787, 'support': 2013.0} | {'precision': 0.7484180515958556, 'recall': 0.9494530698659139, 'f1-score': 0.8370338686471983, 'support': 11336.0} | {'precision': 0.8500846381718155, 'recall': 0.8709083026230219, 'f1-score': 0.8603704893457543, 'support': 9226.0} | 0.7470   | {'precision': 0.48278616406288194, 'recall': 0.3659726083407761, 'f1-score': 0.3826960661711399, 'support': 27619.0} | {'precision': 0.7126373293529855, 'recall': 0.7469857706651218, 'f1-score': 0.7147071394985115, 'support': 27619.0} |
+| No log        | 2.0   | 82   | 0.5074          | {'precision': 0.15789473684210525, 'recall': 0.02214022140221402, 'f1-score': 0.038834951456310676, 'support': 271.0} | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 139.0}                                               | {'precision': 0.5579937304075235, 'recall': 0.8436018957345972, 'f1-score': 0.6716981132075472, 'support': 633.0}  | {'precision': 0.5924329501915708, 'recall': 0.3091727068232942, 'f1-score': 0.4063064542617836, 'support': 4001.0}   | {'precision': 0.6722197208464655, 'recall': 0.741679085941381, 'f1-score': 0.7052432687765706, 'support': 2013.0}    | {'precision': 0.7885760494008675, 'recall': 0.9462773465067043, 'f1-score': 0.8602590320381731, 'support': 11336.0} | {'precision': 0.928374655647383, 'recall': 0.8766529373509646, 'f1-score': 0.9017727728843795, 'support': 9226.0}  | 0.7996   | {'precision': 0.5282131204765593, 'recall': 0.5342177419655937, 'f1-score': 0.5120163703749664, 'support': 27619.0}  | {'precision': 0.7829387271741762, 'recall': 0.7996306890184294, 'f1-score': 0.7803558416622501, 'support': 27619.0} |
+| No log        | 3.0   | 123  | 0.4456          | {'precision': 0.4748427672955975, 'recall': 0.5571955719557196, 'f1-score': 0.5127334465195247, 'support': 271.0}     | {'precision': 0.6712328767123288, 'recall': 0.35251798561151076, 'f1-score': 0.4622641509433962, 'support': 139.0} | {'precision': 0.7294117647058823, 'recall': 0.7835703001579779, 'f1-score': 0.7555217060167556, 'support': 633.0}  | {'precision': 0.5786846103755156, 'recall': 0.6663334166458386, 'f1-score': 0.6194237918215614, 'support': 4001.0}   | {'precision': 0.7035775127768313, 'recall': 0.8206656731246895, 'f1-score': 0.7576243980738363, 'support': 2013.0}   | {'precision': 0.8988648090815273, 'recall': 0.8451834862385321, 'f1-score': 0.8711979995453512, 'support': 11336.0} | {'precision': 0.9345198119543318, 'recall': 0.9049425536527206, 'f1-score': 0.9194933920704845, 'support': 9226.0} | 0.8307   | {'precision': 0.7130191647002879, 'recall': 0.704344141055284, 'f1-score': 0.6997512692844158, 'support': 27619.0}   | {'precision': 0.8409693083395489, 'recall': 0.8307324667801151, 'f1-score': 0.8343535169045084, 'support': 27619.0} |
+| No log        | 4.0   | 164  | 0.4313          | {'precision': 0.5757575757575758, 'recall': 0.5608856088560885, 'f1-score': 0.5682242990654206, 'support': 271.0}     | {'precision': 0.6643835616438356, 'recall': 0.697841726618705, 'f1-score': 0.6807017543859649, 'support': 139.0}   | {'precision': 0.7650695517774343, 'recall': 0.7819905213270142, 'f1-score': 0.7734375, 'support': 633.0}           | {'precision': 0.650827067669173, 'recall': 0.540864783804049, 'f1-score': 0.5907725907725908, 'support': 4001.0}     | {'precision': 0.7433227704843821, 'recall': 0.8156979632389468, 'f1-score': 0.7778304121269539, 'support': 2013.0}   | {'precision': 0.8642255892255892, 'recall': 0.9056986591390261, 'f1-score': 0.8844762232942798, 'support': 11336.0} | {'precision': 0.925120244862265, 'recall': 0.917298937784522, 'f1-score': 0.921192990094699, 'support': 9226.0}    | 0.8429   | {'precision': 0.7412437659171793, 'recall': 0.7457540286811932, 'f1-score': 0.7423765385342728, 'support': 27619.0}  | {'precision': 0.8387326527993001, 'recall': 0.8428980049965603, 'f1-score': 0.8397478190947073, 'support': 27619.0} |
+| No log        | 5.0   | 205  | 0.4380          | {'precision': 0.5848375451263538, 'recall': 0.5977859778597786, 'f1-score': 0.5912408759124088, 'support': 271.0}     | {'precision': 0.654320987654321, 'recall': 0.762589928057554, 'f1-score': 0.7043189368770765, 'support': 139.0}    | {'precision': 0.7932148626817448, 'recall': 0.7756714060031595, 'f1-score': 0.7843450479233227, 'support': 633.0}  | {'precision': 0.6200329179402775, 'recall': 0.6590852286928268, 'f1-score': 0.6389629270656652, 'support': 4001.0}   | {'precision': 0.7448522829006267, 'recall': 0.8266269249875807, 'f1-score': 0.7836119613845066, 'support': 2013.0}   | {'precision': 0.8884649511978705, 'recall': 0.8832921665490473, 'f1-score': 0.8858710076970716, 'support': 11336.0} | {'precision': 0.9446842344388914, 'recall': 0.9014740949490571, 'f1-score': 0.922573488630061, 'support': 9226.0}  | 0.8469   | {'precision': 0.7472011117057266, 'recall': 0.7723608181570006, 'f1-score': 0.7587034636414446, 'support': 27619.0}  | {'precision': 0.851550794162027, 'recall': 0.846880770484087, 'f1-score': 0.8487785699607272, 'support': 27619.0}   |
+| No log        | 6.0   | 246  | 0.4586          | {'precision': 0.5868055555555556, 'recall': 0.6236162361623616, 'f1-score': 0.6046511627906976, 'support': 271.0}     | {'precision': 0.6733333333333333, 'recall': 0.7266187050359713, 'f1-score': 0.698961937716263, 'support': 139.0}   | {'precision': 0.7458893871449925, 'recall': 0.7883096366508688, 'f1-score': 0.7665130568356375, 'support': 633.0}  | {'precision': 0.6227261989133003, 'recall': 0.6588352911772057, 'f1-score': 0.640272042749575, 'support': 4001.0}    | {'precision': 0.8159871244635193, 'recall': 0.7555886736214605, 'f1-score': 0.7846272891410886, 'support': 2013.0}   | {'precision': 0.8951378809869376, 'recall': 0.870501058574453, 'f1-score': 0.8826475849731664, 'support': 11336.0}  | {'precision': 0.9149185390267277, 'recall': 0.9312811619336657, 'f1-score': 0.923027340602675, 'support': 9226.0}  | 0.8467   | {'precision': 0.750685431346338, 'recall': 0.7649643947365695, 'f1-score': 0.7572429164013005, 'support': 27619.0}   | {'precision': 0.8489516884853674, 'recall': 0.846735942648177, 'f1-score': 0.8475667251954796, 'support': 27619.0}  |
+| No log        | 7.0   | 287  | 0.5199          | {'precision': 0.6106194690265486, 'recall': 0.5092250922509225, 'f1-score': 0.5553319919517101, 'support': 271.0}     | {'precision': 0.6687898089171974, 'recall': 0.7553956834532374, 'f1-score': 0.7094594594594595, 'support': 139.0}  | {'precision': 0.7169811320754716, 'recall': 0.8404423380726699, 'f1-score': 0.7738181818181818, 'support': 633.0}  | {'precision': 0.6686178861788618, 'recall': 0.5138715321169708, 'f1-score': 0.58111927642736, 'support': 4001.0}     | {'precision': 0.825, 'recall': 0.7704918032786885, 'f1-score': 0.7968147957873105, 'support': 2013.0}                | {'precision': 0.8428010576075635, 'recall': 0.9279287226534932, 'f1-score': 0.8833186379476844, 'support': 11336.0} | {'precision': 0.9325458158533892, 'recall': 0.9155647084326902, 'f1-score': 0.9239772478669874, 'support': 9226.0} | 0.8454   | {'precision': 0.752193595665576, 'recall': 0.747559982894096, 'f1-score': 0.7462627987512419, 'support': 27619.0}    | {'precision': 0.8402119687481008, 'recall': 0.8453600782070314, 'f1-score': 0.8402149723478831, 'support': 27619.0} |
+| No log        | 8.0   | 328  | 0.5409          | {'precision': 0.5830258302583026, 'recall': 0.5830258302583026, 'f1-score': 0.5830258302583026, 'support': 271.0}     | {'precision': 0.6145251396648045, 'recall': 0.7913669064748201, 'f1-score': 0.6918238993710691, 'support': 139.0}  | {'precision': 0.7553956834532374, 'recall': 0.8293838862559242, 'f1-score': 0.7906626506024096, 'support': 633.0}  | {'precision': 0.6144920061887571, 'recall': 0.5956010997250687, 'f1-score': 0.604899098870415, 'support': 4001.0}    | {'precision': 0.7724268177525968, 'recall': 0.8127173373075013, 'f1-score': 0.7920600338900993, 'support': 2013.0}   | {'precision': 0.8602069139540752, 'recall': 0.9021700776287932, 'f1-score': 0.8806889128094725, 'support': 11336.0} | {'precision': 0.9516823844452207, 'recall': 0.8859744201170605, 'f1-score': 0.9176536626438395, 'support': 9226.0} | 0.8405   | {'precision': 0.7359649679595704, 'recall': 0.7714627939667815, 'f1-score': 0.751544869777944, 'support': 27619.0}   | {'precision': 0.842412448619121, 'recall': 0.8404721387450668, 'f1-score': 0.8406905872698305, 'support': 27619.0}  |
+| No log        | 9.0   | 369  | 0.5502          | {'precision': 0.5793103448275863, 'recall': 0.6199261992619927, 'f1-score': 0.5989304812834225, 'support': 271.0}     | {'precision': 0.6503067484662577, 'recall': 0.762589928057554, 'f1-score': 0.7019867549668876, 'support': 139.0}   | {'precision': 0.7593423019431988, 'recall': 0.8025276461295419, 'f1-score': 0.7803379416282642, 'support': 633.0}  | {'precision': 0.6140224934194783, 'recall': 0.6413396650837291, 'f1-score': 0.6273838630806847, 'support': 4001.0}   | {'precision': 0.7911111111111111, 'recall': 0.7958271236959762, 'f1-score': 0.7934621099554235, 'support': 2013.0}   | {'precision': 0.8799437510986113, 'recall': 0.8832039520112914, 'f1-score': 0.8815708373690234, 'support': 11336.0} | {'precision': 0.9401009534492428, 'recall': 0.9084110123563841, 'f1-score': 0.9239843448541977, 'support': 9226.0} | 0.8452   | {'precision': 0.7448768149022124, 'recall': 0.7734036466566385, 'f1-score': 0.7582366190197004, 'support': 27619.0}  | {'precision': 0.8481724117610957, 'recall': 0.8451790434121438, 'f1-score': 0.8464972981637662, 'support': 27619.0} |
+| No log        | 10.0  | 410  | 0.6131          | {'precision': 0.5976095617529881, 'recall': 0.5535055350553506, 'f1-score': 0.5747126436781611, 'support': 271.0}     | {'precision': 0.6494252873563219, 'recall': 0.8129496402877698, 'f1-score': 0.7220447284345047, 'support': 139.0}  | {'precision': 0.7667682926829268, 'recall': 0.7946287519747235, 'f1-score': 0.7804499612102405, 'support': 633.0}  | {'precision': 0.6487764182424917, 'recall': 0.583104223944014, 'f1-score': 0.6141898117678031, 'support': 4001.0}    | {'precision': 0.7791783380018674, 'recall': 0.829110779930452, 'f1-score': 0.8033694344163658, 'support': 2013.0}    | {'precision': 0.8636249476768523, 'recall': 0.9100211714890614, 'f1-score': 0.8862162278252652, 'support': 11336.0} | {'precision': 0.9387916431394693, 'recall': 0.901040537611099, 'f1-score': 0.919528787124606, 'support': 9226.0}   | 0.8471   | {'precision': 0.7491677841218453, 'recall': 0.7691943771846387, 'f1-score': 0.7572159420652781, 'support': 27619.0}  | {'precision': 0.8455473111155869, 'recall': 0.8471342191969297, 'f1-score': 0.845592238174344, 'support': 27619.0}  |
+| No log        | 11.0  | 451  | 0.6233          | {'precision': 0.5868055555555556, 'recall': 0.6236162361623616, 'f1-score': 0.6046511627906976, 'support': 271.0}     | {'precision': 0.6549707602339181, 'recall': 0.8057553956834532, 'f1-score': 0.7225806451612903, 'support': 139.0}  | {'precision': 0.7620481927710844, 'recall': 0.7993680884676145, 'f1-score': 0.7802621434078643, 'support': 633.0}  | {'precision': 0.6177835051546392, 'recall': 0.599100224943764, 'f1-score': 0.6082984392843548, 'support': 4001.0}    | {'precision': 0.7816593886462883, 'recall': 0.8002980625931445, 'f1-score': 0.7908689248895435, 'support': 2013.0}   | {'precision': 0.8624830852503383, 'recall': 0.8996118560338744, 'f1-score': 0.8806563039723663, 'support': 11336.0} | {'precision': 0.9492612530065284, 'recall': 0.8983308042488619, 'f1-score': 0.9230940580275101, 'support': 9226.0} | 0.8429   | {'precision': 0.7450016772311931, 'recall': 0.7751543811618677, 'f1-score': 0.758630239647661, 'support': 27619.0}   | {'precision': 0.8440807587297484, 'recall': 0.8429342119555379, 'f1-score': 0.8430287828720368, 'support': 27619.0} |
+| No log        | 12.0  | 492  | 0.6488          | {'precision': 0.5888888888888889, 'recall': 0.5867158671586716, 'f1-score': 0.5878003696857672, 'support': 271.0}     | {'precision': 0.6728395061728395, 'recall': 0.7841726618705036, 'f1-score': 0.7242524916943521, 'support': 139.0}  | {'precision': 0.7496382054992764, 'recall': 0.8183254344391785, 'f1-score': 0.782477341389728, 'support': 633.0}   | {'precision': 0.6320602474448628, 'recall': 0.5873531617095726, 'f1-score': 0.6088871615494235, 'support': 4001.0}   | {'precision': 0.7818969667790082, 'recall': 0.8067560854446101, 'f1-score': 0.7941320293398534, 'support': 2013.0}   | {'precision': 0.8592370481425954, 'recall': 0.9100211714890614, 'f1-score': 0.8839002656156285, 'support': 11336.0} | {'precision': 0.948821161587119, 'recall': 0.8942120095382614, 'f1-score': 0.9207075498019084, 'support': 9226.0}  | 0.8446   | {'precision': 0.7476260035020843, 'recall': 0.7696509130928371, 'f1-score': 0.7574510298680944, 'support': 27619.0}  | {'precision': 0.8445128868904818, 'recall': 0.844563525109526, 'f1-score': 0.8437799966523624, 'support': 27619.0}  |
+| 0.3135        | 13.0  | 533  | 0.6540          | {'precision': 0.5909090909090909, 'recall': 0.5756457564575646, 'f1-score': 0.5831775700934578, 'support': 271.0}     | {'precision': 0.675, 'recall': 0.7769784172661871, 'f1-score': 0.7224080267558529, 'support': 139.0}               | {'precision': 0.7463976945244957, 'recall': 0.8183254344391785, 'f1-score': 0.7807083647324792, 'support': 633.0}  | {'precision': 0.6368118323746919, 'recall': 0.5811047238190452, 'f1-score': 0.6076842655514898, 'support': 4001.0}   | {'precision': 0.7928642220019821, 'recall': 0.7948335817188277, 'f1-score': 0.7938476804763087, 'support': 2013.0}   | {'precision': 0.8642820903094875, 'recall': 0.9016407904022583, 'f1-score': 0.8825662723426302, 'support': 11336.0} | {'precision': 0.9345991561181435, 'recall': 0.9123130283980057, 'f1-score': 0.9233216322948662, 'support': 9226.0} | 0.8453   | {'precision': 0.7486948694625559, 'recall': 0.7658345332144382, 'f1-score': 0.756244830321012, 'support': 27619.0}   | {'precision': 0.8432768932468896, 'recall': 0.8452514573300989, 'f1-score': 0.8438155256232617, 'support': 27619.0} |
+| 0.3135        | 14.0  | 574  | 0.6714          | {'precision': 0.6029411764705882, 'recall': 0.6051660516605166, 'f1-score': 0.6040515653775324, 'support': 271.0}     | {'precision': 0.6608187134502924, 'recall': 0.8129496402877698, 'f1-score': 0.7290322580645162, 'support': 139.0}  | {'precision': 0.7786259541984732, 'recall': 0.8056872037914692, 'f1-score': 0.7919254658385093, 'support': 633.0}  | {'precision': 0.6342872144919927, 'recall': 0.6038490377405649, 'f1-score': 0.6186939820742638, 'support': 4001.0}   | {'precision': 0.78125, 'recall': 0.819672131147541, 'f1-score': 0.8, 'support': 2013.0}                              | {'precision': 0.8721188321666382, 'recall': 0.9011997177134792, 'f1-score': 0.8864208242950109, 'support': 11336.0} | {'precision': 0.9428314202115687, 'recall': 0.9080858443529157, 'f1-score': 0.9251325088339223, 'support': 9226.0} | 0.8489   | {'precision': 0.7532676158556504, 'recall': 0.7795156609563223, 'f1-score': 0.7650366577833936, 'support': 27619.0}  | {'precision': 0.8488164759222332, 'recall': 0.8489445671458055, 'f1-score': 0.8485410728467069, 'support': 27619.0} |
+| 0.3135        | 15.0  | 615  | 0.6882          | {'precision': 0.5955882352941176, 'recall': 0.5977859778597786, 'f1-score': 0.5966850828729282, 'support': 271.0}     | {'precision': 0.6511627906976745, 'recall': 0.8057553956834532, 'f1-score': 0.7202572347266881, 'support': 139.0}  | {'precision': 0.7690014903129657, 'recall': 0.8151658767772512, 'f1-score': 0.7914110429447854, 'support': 633.0}  | {'precision': 0.6307486631016043, 'recall': 0.5896025993501625, 'f1-score': 0.6094819790724713, 'support': 4001.0}   | {'precision': 0.7757889778615167, 'recall': 0.8181818181818182, 'f1-score': 0.7964216634429401, 'support': 2013.0}   | {'precision': 0.8646648162166709, 'recall': 0.9068454481298518, 'f1-score': 0.8852529601722283, 'support': 11336.0} | {'precision': 0.948583180987203, 'recall': 0.8998482549317147, 'f1-score': 0.9235732562020248, 'support': 9226.0}  | 0.8464   | {'precision': 0.7479340220673932, 'recall': 0.7761693387020043, 'f1-score': 0.7604404599191524, 'support': 27619.0}  | {'precision': 0.84642642314945, 'recall': 0.8464462869763568, 'f1-score': 0.8458173441573364, 'support': 27619.0}   |
+| 0.3135        | 16.0  | 656  | 0.6830          | {'precision': 0.5970695970695971, 'recall': 0.6014760147601476, 'f1-score': 0.5992647058823529, 'support': 271.0}     | {'precision': 0.6627218934911243, 'recall': 0.8057553956834532, 'f1-score': 0.7272727272727272, 'support': 139.0}  | {'precision': 0.7686567164179104, 'recall': 0.8135860979462876, 'f1-score': 0.7904834996162702, 'support': 633.0}  | {'precision': 0.6353591160220995, 'recall': 0.6035991002249438, 'f1-score': 0.6190720328120995, 'support': 4001.0}   | {'precision': 0.783796740172579, 'recall': 0.812220566318927, 'f1-score': 0.7977555501341791, 'support': 2013.0}     | {'precision': 0.8706603131381893, 'recall': 0.9026111503175723, 'f1-score': 0.8863478863478863, 'support': 11336.0} | {'precision': 0.9430536761389264, 'recall': 0.9064600043355734, 'f1-score': 0.92439482701448, 'support': 9226.0}   | 0.8485   | {'precision': 0.751616864635775, 'recall': 0.7779583327981293, 'f1-score': 0.7635130327257136, 'support': 27619.0}   | {'precision': 0.848356460858747, 'recall': 0.8485100836380752, 'f1-score': 0.8480670241145107, 'support': 27619.0}  |
 ### Framework versions

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
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