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Theoreticallyhugo
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longformer-full_labels

Token Classification
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Safetensors
longformer
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trainer: training complete at 2024-04-23 12:07:52.344026.

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  1. README.md +36 -66
  2. meta_data/README_s42_e20.md +103 -0
  3. model.safetensors +1 -1
README.md CHANGED
@@ -17,12 +17,12 @@ model-index:
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  name: essays_su_g
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  type: essays_su_g
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  config: full_labels
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- split: train[80%:100%]
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  args: full_labels
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8508273290126362
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  ---
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  <!-- 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. -->
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  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.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.2444
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- - B-claim: {'precision': 0.6226415094339622, 'recall': 0.6088560885608856, 'f1-score': 0.6156716417910446, 'support': 271.0}
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- - B-majorclaim: {'precision': 0.7248322147651006, 'recall': 0.7769784172661871, 'f1-score': 0.75, 'support': 139.0}
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- - B-premise: {'precision': 0.7849462365591398, 'recall': 0.8072669826224329, 'f1-score': 0.7959501557632399, 'support': 633.0}
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- - I-claim: {'precision': 0.6374740124740125, 'recall': 0.6130967258185454, 'f1-score': 0.6250477767868517, 'support': 4001.0}
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- - I-majorclaim: {'precision': 0.8101010101010101, 'recall': 0.7968206656731247, 'f1-score': 0.8034059604307539, 'support': 2013.0}
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- - I-premise: {'precision': 0.8720684108034883, 'recall': 0.9086097388849682, 'f1-score': 0.8899641422214541, 'support': 11336.0}
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- - O: {'precision': 0.9375210319685923, 'recall': 0.9059180576631259, 'f1-score': 0.9214486522242435, 'support': 9226.0}
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- - Accuracy: 0.8508
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- - Macro avg: {'precision': 0.7699406323007579, 'recall': 0.7739352394984671, 'f1-score': 0.7716411898882268, 'support': 27619.0}
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- - Weighted avg: {'precision': 0.8502466381007031, 'recall': 0.8508273290126362, 'f1-score': 0.8502452876077368, 'support': 27619.0}
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  ## Model description
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@@ -67,62 +67,32 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 50
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | B-claim | B-majorclaim | B-premise | I-claim | I-majorclaim | I-premise | O | Accuracy | Macro avg | Weighted avg |
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- |:-------------:|:-----:|:----:|:---------------:|:------------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:--------:|:---------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
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- | No log | 1.0 | 81 | 0.5656 | {'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': 0.6075949367088608, 'recall': 0.7582938388625592, 'f1-score': 0.6746310611384398, 'support': 633.0} | {'precision': 0.550587343690792, 'recall': 0.3631592101974506, 'f1-score': 0.4376506024096386, 'support': 4001.0} | {'precision': 0.5483008781977854, 'recall': 0.7133631395926477, 'f1-score': 0.620034542314335, 'support': 2013.0} | {'precision': 0.8396186972154862, 'recall': 0.8857621736062103, 'f1-score': 0.8620734063103671, 'support': 11336.0} | {'precision': 0.8630878069080317, 'recall': 0.8991979189247779, 'f1-score': 0.8807729058286443, 'support': 9226.0} | 0.7859 | {'precision': 0.48702709467442235, 'recall': 0.5171108973119495, 'f1-score': 0.49645178828591785, 'support': 27619.0} | {'precision': 0.766573839857488, 'recall': 0.785908251565951, 'f1-score': 0.7721020318885458, 'support': 27619.0} |
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- | No log | 2.0 | 162 | 0.4831 | {'precision': 0.4624277456647399, 'recall': 0.2952029520295203, 'f1-score': 0.36036036036036034, 'support': 271.0} | {'precision': 0.723404255319149, 'recall': 0.4892086330935252, 'f1-score': 0.5836909871244635, 'support': 139.0} | {'precision': 0.6654040404040404, 'recall': 0.8325434439178515, 'f1-score': 0.7396491228070177, 'support': 633.0} | {'precision': 0.5973520249221184, 'recall': 0.3834041489627593, 'f1-score': 0.46704216775764956, 'support': 4001.0} | {'precision': 0.8348157560355781, 'recall': 0.6527570789865872, 'f1-score': 0.7326456649010316, 'support': 2013.0} | {'precision': 0.8045344983428744, 'recall': 0.9422194777699365, 'f1-score': 0.8679505932065659, 'support': 11336.0} | {'precision': 0.9143513454386348, 'recall': 0.9060264469976155, 'f1-score': 0.9101698606271778, 'support': 9226.0} | 0.8169 | {'precision': 0.7146128094467336, 'recall': 0.6430517402511137, 'f1-score': 0.6659298223977524, 'support': 27619.0} | {'precision': 0.8064582361050344, 'recall': 0.8169376154096818, 'f1-score': 0.8047632099274016, 'support': 27619.0} |
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- | No log | 3.0 | 243 | 0.4284 | {'precision': 0.59765625, 'recall': 0.5645756457564576, 'f1-score': 0.5806451612903225, 'support': 271.0} | {'precision': 0.6708860759493671, 'recall': 0.762589928057554, 'f1-score': 0.7138047138047138, 'support': 139.0} | {'precision': 0.7420289855072464, 'recall': 0.8088467614533965, 'f1-score': 0.7739984882842026, 'support': 633.0} | {'precision': 0.6068103870651641, 'recall': 0.6190952261934516, 'f1-score': 0.6128912532475566, 'support': 4001.0} | {'precision': 0.8009779951100244, 'recall': 0.8137108792846498, 'f1-score': 0.8072942336126171, 'support': 2013.0} | {'precision': 0.8951789627465303, 'recall': 0.8648553281580804, 'f1-score': 0.8797559224694903, 'support': 11336.0} | {'precision': 0.912356930902925, 'recall': 0.933123780619987, 'f1-score': 0.9226235130211126, 'support': 9226.0} | 0.8436 | {'precision': 0.7465565124687511, 'recall': 0.7666853642176539, 'f1-score': 0.7558590408185736, 'support': 27619.0} | {'precision': 0.8447189682878564, 'recall': 0.8435859372171332, 'f1-score': 0.8439412578936614, 'support': 27619.0} |
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- | No log | 4.0 | 324 | 0.4826 | {'precision': 0.5501519756838906, 'recall': 0.6678966789667896, 'f1-score': 0.6033333333333333, 'support': 271.0} | {'precision': 0.6474358974358975, 'recall': 0.7266187050359713, 'f1-score': 0.6847457627118644, 'support': 139.0} | {'precision': 0.7881219903691814, 'recall': 0.7756714060031595, 'f1-score': 0.7818471337579618, 'support': 633.0} | {'precision': 0.550733024691358, 'recall': 0.7135716070982254, 'f1-score': 0.6216657593903103, 'support': 4001.0} | {'precision': 0.7960279119699409, 'recall': 0.7367113760556383, 'f1-score': 0.7652218782249742, 'support': 2013.0} | {'precision': 0.8853883758826725, 'recall': 0.8627381792519407, 'f1-score': 0.8739165400768475, 'support': 11336.0} | {'precision': 0.9497505345687812, 'recall': 0.8665727292434424, 'f1-score': 0.9062570845613239, 'support': 9226.0} | 0.8286 | {'precision': 0.7382299586573888, 'recall': 0.7642543830935953, 'f1-score': 0.7481410702938023, 'support': 27619.0} | {'precision': 0.8451795530099128, 'recall': 0.8286324631594192, 'f1-score': 0.8345383371838407, 'support': 27619.0} |
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- | No log | 5.0 | 405 | 0.5134 | {'precision': 0.6147540983606558, 'recall': 0.5535055350553506, 'f1-score': 0.5825242718446603, 'support': 271.0} | {'precision': 0.7094594594594594, 'recall': 0.7553956834532374, 'f1-score': 0.7317073170731707, 'support': 139.0} | {'precision': 0.7607726597325408, 'recall': 0.8088467614533965, 'f1-score': 0.7840735068912711, 'support': 633.0} | {'precision': 0.6132413793103448, 'recall': 0.5556110972256936, 'f1-score': 0.5830055074744296, 'support': 4001.0} | {'precision': 0.8393726338561385, 'recall': 0.7709885742672627, 'f1-score': 0.803728638011393, 'support': 2013.0} | {'precision': 0.8523512002630713, 'recall': 0.9146083274523642, 'f1-score': 0.8823829787234042, 'support': 11336.0} | {'precision': 0.9415657245401525, 'recall': 0.9099284630392369, 'f1-score': 0.9254767941792524, 'support': 9226.0} | 0.8438 | {'precision': 0.7616453079317661, 'recall': 0.7526977774209346, 'f1-score': 0.7561284305996544, 'support': 27619.0} | {'precision': 0.8414191958613282, 'recall': 0.8438031789709982, 'f1-score': 0.8417228378374912, 'support': 27619.0} |
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- | No log | 6.0 | 486 | 0.5017 | {'precision': 0.587360594795539, 'recall': 0.5830258302583026, 'f1-score': 0.5851851851851851, 'support': 271.0} | {'precision': 0.6611111111111111, 'recall': 0.8561151079136691, 'f1-score': 0.7460815047021944, 'support': 139.0} | {'precision': 0.7574850299401198, 'recall': 0.7993680884676145, 'f1-score': 0.7778631821675633, 'support': 633.0} | {'precision': 0.6059138414478715, 'recall': 0.5941014746313422, 'f1-score': 0.5999495204442201, 'support': 4001.0} | {'precision': 0.7888138862102217, 'recall': 0.8127173373075013, 'f1-score': 0.800587227795449, 'support': 2013.0} | {'precision': 0.8729593608891977, 'recall': 0.8868207480592801, 'f1-score': 0.8798354629791703, 'support': 11336.0} | {'precision': 0.9391478473690066, 'recall': 0.9150227617602428, 'f1-score': 0.9269283557507548, 'support': 9226.0} | 0.8433 | {'precision': 0.744684524537581, 'recall': 0.7781673354854218, 'f1-score': 0.7594900627177908, 'support': 27619.0} | {'precision': 0.8437360576786502, 'recall': 0.843296281545313, 'f1-score': 0.8433438519855446, 'support': 27619.0} |
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- | 0.4085 | 7.0 | 567 | 0.6029 | {'precision': 0.6016260162601627, 'recall': 0.5461254612546126, 'f1-score': 0.5725338491295938, 'support': 271.0} | {'precision': 0.722972972972973, 'recall': 0.7697841726618705, 'f1-score': 0.745644599303136, 'support': 139.0} | {'precision': 0.760932944606414, 'recall': 0.8246445497630331, 'f1-score': 0.7915087187263078, 'support': 633.0} | {'precision': 0.6368731563421829, 'recall': 0.5396150962259435, 'f1-score': 0.5842240562846706, 'support': 4001.0} | {'precision': 0.8213333333333334, 'recall': 0.7650273224043715, 'f1-score': 0.7921810699588476, 'support': 2013.0} | {'precision': 0.8598256203890007, 'recall': 0.9047282992237121, 'f1-score': 0.8817056396148556, 'support': 11336.0} | {'precision': 0.9214637277979885, 'recall': 0.9334489486234554, 'f1-score': 0.9274176179194485, 'support': 9226.0} | 0.8452 | {'precision': 0.7607182531002935, 'recall': 0.7547676928795714, 'f1-score': 0.7564593644195513, 'support': 27619.0} | {'precision': 0.8398235103191511, 'recall': 0.8452152503711213, 'f1-score': 0.8415705604110203, 'support': 27619.0} |
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- | 0.4085 | 8.0 | 648 | 0.6411 | {'precision': 0.5202492211838006, 'recall': 0.6162361623616236, 'f1-score': 0.5641891891891891, 'support': 271.0} | {'precision': 0.7372262773722628, 'recall': 0.7266187050359713, 'f1-score': 0.7318840579710144, 'support': 139.0} | {'precision': 0.7351664254703328, 'recall': 0.8025276461295419, 'f1-score': 0.7673716012084594, 'support': 633.0} | {'precision': 0.5665832005463237, 'recall': 0.6220944763809048, 'f1-score': 0.5930426495115559, 'support': 4001.0} | {'precision': 0.852199413489736, 'recall': 0.7218082463984103, 'f1-score': 0.7816030123722432, 'support': 2013.0} | {'precision': 0.8652567975830816, 'recall': 0.8842625264643613, 'f1-score': 0.8746564286025915, 'support': 11336.0} | {'precision': 0.9473085239558439, 'recall': 0.9022328202904835, 'f1-score': 0.924221395658691, 'support': 9226.0} | 0.8351 | {'precision': 0.7462842656573401, 'recall': 0.7536829404373281, 'f1-score': 0.7481383335019636, 'support': 27619.0} | {'precision': 0.8414359188593861, 'recall': 0.835149715775372, 'f1-score': 0.8374117728187233, 'support': 27619.0} |
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- | 0.4085 | 9.0 | 729 | 0.6282 | {'precision': 0.5723076923076923, 'recall': 0.6863468634686347, 'f1-score': 0.6241610738255032, 'support': 271.0} | {'precision': 0.696969696969697, 'recall': 0.8273381294964028, 'f1-score': 0.756578947368421, 'support': 139.0} | {'precision': 0.791869918699187, 'recall': 0.7693522906793049, 'f1-score': 0.780448717948718, 'support': 633.0} | {'precision': 0.5933972310969116, 'recall': 0.69632591852037, 'f1-score': 0.640754369825207, 'support': 4001.0} | {'precision': 0.7898586055582643, 'recall': 0.8047690014903129, 'f1-score': 0.797244094488189, 'support': 2013.0} | {'precision': 0.8996028447400019, 'recall': 0.8592095977417078, 'f1-score': 0.8789423814465549, 'support': 11336.0} | {'precision': 0.9435186220780674, 'recall': 0.9143724257533059, 'f1-score': 0.9287169042769858, 'support': 9226.0} | 0.8462 | {'precision': 0.7553606587785459, 'recall': 0.7939591753071484, 'f1-score': 0.7724066413113684, 'support': 27619.0} | {'precision': 0.85521547416283, 'recall': 0.8461566313045368, 'f1-score': 0.8497367665000708, 'support': 27619.0} |
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- | 0.4085 | 10.0 | 810 | 0.7146 | {'precision': 0.5602836879432624, 'recall': 0.5830258302583026, 'f1-score': 0.5714285714285714, 'support': 271.0} | {'precision': 0.6962025316455697, 'recall': 0.7913669064748201, 'f1-score': 0.7407407407407407, 'support': 139.0} | {'precision': 0.753956834532374, 'recall': 0.8278041074249605, 'f1-score': 0.789156626506024, 'support': 633.0} | {'precision': 0.6039778449144008, 'recall': 0.5996000999750063, 'f1-score': 0.6017810109118275, 'support': 4001.0} | {'precision': 0.7836490528414756, 'recall': 0.7809239940387481, 'f1-score': 0.7822841502861408, 'support': 2013.0} | {'precision': 0.871336484744306, 'recall': 0.894318983768525, 'f1-score': 0.8826781594183972, 'support': 11336.0} | {'precision': 0.9389020403562169, 'recall': 0.9027747669629308, 'f1-score': 0.9204840581311821, 'support': 9226.0} | 0.8411 | {'precision': 0.744044068139658, 'recall': 0.7685449555576133, 'f1-score': 0.7555076167746976, 'support': 27619.0} | {'precision': 0.842161020451525, 'recall': 0.8410876570476845, 'f1-score': 0.841386205332122, 'support': 27619.0} |
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- | 0.4085 | 11.0 | 891 | 0.7725 | {'precision': 0.5985401459854015, 'recall': 0.6051660516605166, 'f1-score': 0.6018348623853211, 'support': 271.0} | {'precision': 0.768, 'recall': 0.6906474820143885, 'f1-score': 0.7272727272727274, 'support': 139.0} | {'precision': 0.7928802588996764, 'recall': 0.7740916271721959, 'f1-score': 0.7833733013589128, 'support': 633.0} | {'precision': 0.6056477582363141, 'recall': 0.6110972256935766, 'f1-score': 0.6083602886290123, 'support': 4001.0} | {'precision': 0.8532110091743119, 'recall': 0.6929955290611028, 'f1-score': 0.7648026315789475, 'support': 2013.0} | {'precision': 0.8874030489435678, 'recall': 0.8780875088214538, 'f1-score': 0.882720702345586, 'support': 11336.0} | {'precision': 0.8984865643982292, 'recall': 0.9459137220897463, 'f1-score': 0.921590369079677, 'support': 9226.0} | 0.8426 | {'precision': 0.7720241122339289, 'recall': 0.7425713066447115, 'f1-score': 0.7557078403785977, 'support': 27619.0} | {'precision': 0.8421955187218679, 'recall': 0.8425721423657627, 'f1-score': 0.8415502116531838, 'support': 27619.0} |
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- | 0.4085 | 12.0 | 972 | 0.8827 | {'precision': 0.570446735395189, 'recall': 0.6125461254612546, 'f1-score': 0.5907473309608542, 'support': 271.0} | {'precision': 0.6993464052287581, 'recall': 0.7697841726618705, 'f1-score': 0.7328767123287672, 'support': 139.0} | {'precision': 0.7692307692307693, 'recall': 0.8056872037914692, 'f1-score': 0.7870370370370371, 'support': 633.0} | {'precision': 0.596923828125, 'recall': 0.6110972256935766, 'f1-score': 0.6039273805113003, 'support': 4001.0} | {'precision': 0.7980622131565528, 'recall': 0.7774465971187282, 'f1-score': 0.7876195269250126, 'support': 2013.0} | {'precision': 0.8633629817873782, 'recall': 0.8990825688073395, 'f1-score': 0.8808608098180718, 'support': 11336.0} | {'precision': 0.9433526011560693, 'recall': 0.8844569694342077, 'f1-score': 0.9129559185500112, 'support': 9226.0} | 0.8380 | {'precision': 0.7486750762971024, 'recall': 0.765728694709778, 'f1-score': 0.7565749594472935, 'support': 27619.0} | {'precision': 0.8408692792556519, 'recall': 0.8380100655345958, 'f1-score': 0.8389267473809466, 'support': 27619.0} |
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- | 0.0768 | 13.0 | 1053 | 0.8458 | {'precision': 0.5766666666666667, 'recall': 0.6383763837638377, 'f1-score': 0.6059544658493871, 'support': 271.0} | {'precision': 0.6909090909090909, 'recall': 0.8201438848920863, 'f1-score': 0.75, 'support': 139.0} | {'precision': 0.7835703001579779, 'recall': 0.7835703001579779, 'f1-score': 0.7835703001579779, 'support': 633.0} | {'precision': 0.5962299278566442, 'recall': 0.6403399150212447, 'f1-score': 0.6174981923355025, 'support': 4001.0} | {'precision': 0.7978723404255319, 'recall': 0.7824143070044709, 'f1-score': 0.7900677200902934, 'support': 2013.0} | {'precision': 0.8856045722450437, 'recall': 0.8748235709244884, 'f1-score': 0.8801810597319606, 'support': 11336.0} | {'precision': 0.9216747680070703, 'recall': 0.9042922176457836, 'f1-score': 0.9129007550060182, 'support': 9226.0} | 0.8393 | {'precision': 0.7503610951811466, 'recall': 0.7777086542014128, 'f1-score': 0.7628817847387342, 'support': 27619.0} | {'precision': 0.8429896387826172, 'recall': 0.8392773090988088, 'f1-score': 0.8409296175505384, 'support': 27619.0} |
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90
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100
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101
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102
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103
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104
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113
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114
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116
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117
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118
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119
- | 0.0032 | 44.0 | 3564 | 1.1883 | {'precision': 0.607773851590106, 'recall': 0.6346863468634686, 'f1-score': 0.6209386281588447, 'support': 271.0} | {'precision': 0.7210884353741497, 'recall': 0.762589928057554, 'f1-score': 0.7412587412587414, 'support': 139.0} | {'precision': 0.7928902627511591, 'recall': 0.8104265402843602, 'f1-score': 0.8015625000000001, 'support': 633.0} | {'precision': 0.6292434529582929, 'recall': 0.6485878530367408, 'f1-score': 0.6387692307692308, 'support': 4001.0} | {'precision': 0.8247639034627492, 'recall': 0.7809239940387481, 'f1-score': 0.8022454707833631, 'support': 2013.0} | {'precision': 0.8784236284021636, 'recall': 0.9025229357798165, 'f1-score': 0.8903102292999173, 'support': 11336.0} | {'precision': 0.9432600112803159, 'recall': 0.9063516150010839, 'f1-score': 0.9244375656403737, 'support': 9226.0} | 0.8527 | {'precision': 0.7710633636884195, 'recall': 0.7780127447231102, 'f1-score': 0.774217480844353, 'support': 27619.0} | {'precision': 0.8546658985196848, 'recall': 0.852710090879467, 'f1-score': 0.8534252493103502, 'support': 27619.0} |
120
- | 0.0032 | 45.0 | 3645 | 1.2158 | {'precision': 0.6203007518796992, 'recall': 0.6088560885608856, 'f1-score': 0.6145251396648045, 'support': 271.0} | {'precision': 0.7171052631578947, 'recall': 0.7841726618705036, 'f1-score': 0.7491408934707904, 'support': 139.0} | {'precision': 0.7894736842105263, 'recall': 0.8056872037914692, 'f1-score': 0.7974980453479281, 'support': 633.0} | {'precision': 0.6433658665259826, 'recall': 0.60959760059985, 'f1-score': 0.6260266940451746, 'support': 4001.0} | {'precision': 0.8067560854446101, 'recall': 0.8067560854446101, 'f1-score': 0.8067560854446101, 'support': 2013.0} | {'precision': 0.8726136171650617, 'recall': 0.9112561750176429, 'f1-score': 0.8915163545352551, 'support': 11336.0} | {'precision': 0.9371704252215864, 'recall': 0.9053761109906785, 'f1-score': 0.9209989525332158, 'support': 9226.0} | 0.8519 | {'precision': 0.7695408133721945, 'recall': 0.7759574180393771, 'f1-score': 0.7723517378631113, 'support': 27619.0} | {'precision': 0.8510049283714675, 'recall': 0.8519497447409392, 'f1-score': 0.8511380460445594, 'support': 27619.0} |
121
- | 0.0032 | 46.0 | 3726 | 1.2261 | {'precision': 0.6072727272727273, 'recall': 0.6162361623616236, 'f1-score': 0.6117216117216118, 'support': 271.0} | {'precision': 0.7302631578947368, 'recall': 0.7985611510791367, 'f1-score': 0.7628865979381443, 'support': 139.0} | {'precision': 0.7868098159509203, 'recall': 0.8104265402843602, 'f1-score': 0.798443579766537, 'support': 633.0} | {'precision': 0.6418412205844324, 'recall': 0.6203449137715571, 'f1-score': 0.6309100152516522, 'support': 4001.0} | {'precision': 0.8092860708936596, 'recall': 0.8052657724788872, 'f1-score': 0.8072709163346613, 'support': 2013.0} | {'precision': 0.8734970364098222, 'recall': 0.9100211714890614, 'f1-score': 0.8913851205391861, 'support': 11336.0} | {'precision': 0.941647855530474, 'recall': 0.9042922176457836, 'f1-score': 0.9225920601570274, 'support': 9226.0} | 0.8528 | {'precision': 0.7700882692195389, 'recall': 0.7807354184443444, 'f1-score': 0.775029985958403, 'support': 27619.0} | {'precision': 0.8527040517639436, 'recall': 0.852782504797422, 'f1-score': 0.8524246344518868, 'support': 27619.0} |
122
- | 0.0032 | 47.0 | 3807 | 1.2450 | {'precision': 0.6168582375478927, 'recall': 0.5940959409594095, 'f1-score': 0.6052631578947367, 'support': 271.0} | {'precision': 0.7266666666666667, 'recall': 0.7841726618705036, 'f1-score': 0.754325259515571, 'support': 139.0} | {'precision': 0.7776096822995462, 'recall': 0.8120063191153238, 'f1-score': 0.794435857805255, 'support': 633.0} | {'precision': 0.6448445171849427, 'recall': 0.590852286928268, 'f1-score': 0.6166688404851964, 'support': 4001.0} | {'precision': 0.8082329317269076, 'recall': 0.7998012916045703, 'f1-score': 0.8039950062421973, 'support': 2013.0} | {'precision': 0.865584685809405, 'recall': 0.9174311926605505, 'f1-score': 0.8907541432915078, 'support': 11336.0} | {'precision': 0.9400495830516115, 'recall': 0.9041838283112942, 'f1-score': 0.921767955801105, 'support': 9226.0} | 0.8509 | {'precision': 0.768549472040996, 'recall': 0.7717919316357028, 'f1-score': 0.7696014601479385, 'support': 27619.0} | {'precision': 0.849146002184386, 'recall': 0.8508635359716138, 'f1-score': 0.8493902578577504, 'support': 27619.0} |
123
- | 0.0032 | 48.0 | 3888 | 1.2468 | {'precision': 0.6264591439688716, 'recall': 0.5940959409594095, 'f1-score': 0.6098484848484848, 'support': 271.0} | {'precision': 0.7397260273972602, 'recall': 0.7769784172661871, 'f1-score': 0.7578947368421054, 'support': 139.0} | {'precision': 0.7828746177370031, 'recall': 0.8088467614533965, 'f1-score': 0.7956487956487955, 'support': 633.0} | {'precision': 0.6403927813163482, 'recall': 0.6030992251937016, 'f1-score': 0.6211867679237998, 'support': 4001.0} | {'precision': 0.8106598984771574, 'recall': 0.7933432687531048, 'f1-score': 0.8019081094652273, 'support': 2013.0} | {'precision': 0.8717494089834515, 'recall': 0.9108151023288638, 'f1-score': 0.8908541846419327, 'support': 11336.0} | {'precision': 0.933630289532294, 'recall': 0.9087361803598526, 'f1-score': 0.9210150499835219, 'support': 9226.0} | 0.8509 | {'precision': 0.772213166773198, 'recall': 0.770844985187788, 'f1-score': 0.7711937327648383, 'support': 27619.0} | {'precision': 0.8493445173248085, 'recall': 0.8508635359716138, 'f1-score': 0.8497729521896602, 'support': 27619.0} |
124
- | 0.0032 | 49.0 | 3969 | 1.2472 | {'precision': 0.6197718631178707, 'recall': 0.6014760147601476, 'f1-score': 0.6104868913857678, 'support': 271.0} | {'precision': 0.7297297297297297, 'recall': 0.7769784172661871, 'f1-score': 0.7526132404181185, 'support': 139.0} | {'precision': 0.7822085889570553, 'recall': 0.8056872037914692, 'f1-score': 0.7937743190661478, 'support': 633.0} | {'precision': 0.6380208333333334, 'recall': 0.6123469132716821, 'f1-score': 0.6249202907792375, 'support': 4001.0} | {'precision': 0.8100050530570996, 'recall': 0.7963238946845504, 'f1-score': 0.8031062124248497, 'support': 2013.0} | {'precision': 0.8719336829639655, 'recall': 0.9093154551870148, 'f1-score': 0.8902323171258313, 'support': 11336.0} | {'precision': 0.937633202467751, 'recall': 0.9060264469976155, 'f1-score': 0.9215588997298936, 'support': 9226.0} | 0.8509 | {'precision': 0.7699004219466864, 'recall': 0.7725934779940953, 'f1-score': 0.7709560244185495, 'support': 27619.0} | {'precision': 0.8502347777314452, 'recall': 0.8508997429305912, 'f1-score': 0.8502642809956156, 'support': 27619.0} |
125
- | 0.003 | 50.0 | 4050 | 1.2444 | {'precision': 0.6226415094339622, 'recall': 0.6088560885608856, 'f1-score': 0.6156716417910446, 'support': 271.0} | {'precision': 0.7248322147651006, 'recall': 0.7769784172661871, 'f1-score': 0.75, 'support': 139.0} | {'precision': 0.7849462365591398, 'recall': 0.8072669826224329, 'f1-score': 0.7959501557632399, 'support': 633.0} | {'precision': 0.6374740124740125, 'recall': 0.6130967258185454, 'f1-score': 0.6250477767868517, 'support': 4001.0} | {'precision': 0.8101010101010101, 'recall': 0.7968206656731247, 'f1-score': 0.8034059604307539, 'support': 2013.0} | {'precision': 0.8720684108034883, 'recall': 0.9086097388849682, 'f1-score': 0.8899641422214541, 'support': 11336.0} | {'precision': 0.9375210319685923, 'recall': 0.9059180576631259, 'f1-score': 0.9214486522242435, 'support': 9226.0} | 0.8508 | {'precision': 0.7699406323007579, 'recall': 0.7739352394984671, 'f1-score': 0.7716411898882268, 'support': 27619.0} | {'precision': 0.8502466381007031, 'recall': 0.8508273290126362, 'f1-score': 0.8502452876077368, 'support': 27619.0} |
126
 
127
 
128
  ### Framework versions
 
17
  name: essays_su_g
18
  type: essays_su_g
19
  config: full_labels
20
+ split: train[0%:20%]
21
  args: full_labels
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
+ value: 0.8364696256903252
26
  ---
27
 
28
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
32
 
33
  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.
34
  It achieves the following results on the evaluation set:
35
+ - Loss: 1.0525
36
+ - B-claim: {'precision': 0.5714285714285714, 'recall': 0.5915492957746479, 'f1-score': 0.5813148788927336, 'support': 284.0}
37
+ - B-majorclaim: {'precision': 0.7328767123287672, 'recall': 0.7588652482269503, 'f1-score': 0.7456445993031359, 'support': 141.0}
38
+ - B-premise: {'precision': 0.7592592592592593, 'recall': 0.8107344632768362, 'f1-score': 0.7841530054644807, 'support': 708.0}
39
+ - I-claim: {'precision': 0.5995872033023736, 'recall': 0.5700269806230072, 'f1-score': 0.5844335470891487, 'support': 4077.0}
40
+ - I-majorclaim: {'precision': 0.7741293532338308, 'recall': 0.7687747035573123, 'f1-score': 0.7714427367377293, 'support': 2024.0}
41
+ - I-premise: {'precision': 0.8661675245671502, 'recall': 0.907946370176586, 'f1-score': 0.8865650195577552, 'support': 12232.0}
42
+ - O: {'precision': 0.9227995758218451, 'recall': 0.8818402918524524, 'f1-score': 0.9018551145196393, 'support': 9868.0}
43
+ - Accuracy: 0.8365
44
+ - Macro avg: {'precision': 0.746606885705971, 'recall': 0.7556767647839704, 'f1-score': 0.7507727002235176, 'support': 29334.0}
45
+ - Weighted avg: {'precision': 0.8357427933389249, 'recall': 0.8364696256903252, 'f1-score': 0.8356690155425791, 'support': 29334.0}
46
 
47
  ## Model description
48
 
 
67
  - seed: 42
68
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
69
  - lr_scheduler_type: linear
70
+ - num_epochs: 20
71
 
72
  ### Training results
73
 
74
+ | Training Loss | Epoch | Step | Validation Loss | B-claim | B-majorclaim | B-premise | I-claim | I-majorclaim | I-premise | O | Accuracy | Macro avg | Weighted avg |
75
+ |:-------------:|:-----:|:----:|:---------------:|:------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:--------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
76
+ | No log | 1.0 | 81 | 0.6443 | {'precision': 0.5, 'recall': 0.0035211267605633804, 'f1-score': 0.006993006993006993, 'support': 284.0} | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 141.0} | {'precision': 0.5883777239709443, 'recall': 0.6864406779661016, 'f1-score': 0.6336375488917861, 'support': 708.0} | {'precision': 0.41618672324946954, 'recall': 0.3367672308069659, 'f1-score': 0.37228850325379614, 'support': 4077.0} | {'precision': 0.5611921369689283, 'recall': 0.43725296442687744, 'f1-score': 0.49153013051930017, 'support': 2024.0} | {'precision': 0.7746890504995582, 'recall': 0.9318181818181818, 'f1-score': 0.846019669697532, 'support': 12232.0} | {'precision': 0.9111808904340025, 'recall': 0.8233684637211187, 'f1-score': 0.8650519031141869, 'support': 9868.0} | 0.7591 | {'precision': 0.535946646446129, 'recall': 0.4598812350714013, 'f1-score': 0.4593601089242298, 'support': 29334.0} | {'precision': 0.7451676238152983, 'recall': 0.7591191109292971, 'f1-score': 0.7448054609057474, 'support': 29334.0} |
77
+ | No log | 2.0 | 162 | 0.5139 | {'precision': 0.4420731707317073, 'recall': 0.5105633802816901, 'f1-score': 0.47385620915032683, 'support': 284.0} | {'precision': 0.6274509803921569, 'recall': 0.45390070921985815, 'f1-score': 0.5267489711934156, 'support': 141.0} | {'precision': 0.7261306532663316, 'recall': 0.8163841807909604, 'f1-score': 0.7686170212765958, 'support': 708.0} | {'precision': 0.5221008840353614, 'recall': 0.49251900907530044, 'f1-score': 0.5068787075602675, 'support': 4077.0} | {'precision': 0.5741007194244604, 'recall': 0.7885375494071146, 'f1-score': 0.6644462947543713, 'support': 2024.0} | {'precision': 0.8642982877260361, 'recall': 0.8830935251798561, 'f1-score': 0.8735948241002829, 'support': 12232.0} | {'precision': 0.925979519145147, 'recall': 0.8430279691933522, 'f1-score': 0.8825588796944621, 'support': 9868.0} | 0.8015 | {'precision': 0.668876316388743, 'recall': 0.6840037604497332, 'f1-score': 0.6709572725328175, 'support': 29334.0} | {'precision': 0.8089032379475054, 'recall': 0.8015272380173177, 'f1-score': 0.8031401896750007, 'support': 29334.0} |
78
+ | No log | 3.0 | 243 | 0.5770 | {'precision': 0.4393939393939394, 'recall': 0.4084507042253521, 'f1-score': 0.4233576642335767, 'support': 284.0} | {'precision': 0.7181818181818181, 'recall': 0.5602836879432624, 'f1-score': 0.6294820717131473, 'support': 141.0} | {'precision': 0.6709816612729234, 'recall': 0.8785310734463276, 'f1-score': 0.7608562691131499, 'support': 708.0} | {'precision': 0.5186211141889813, 'recall': 0.41329408879077756, 'f1-score': 0.46000546000546, 'support': 4077.0} | {'precision': 0.7556615017878426, 'recall': 0.6264822134387352, 'f1-score': 0.6850351161534306, 'support': 2024.0} | {'precision': 0.7999862438957287, 'recall': 0.9508665794637018, 'f1-score': 0.8689253296477533, 'support': 12232.0} | {'precision': 0.9404692424419283, 'recall': 0.8164775030401297, 'f1-score': 0.8740981828044481, 'support': 9868.0} | 0.7997 | {'precision': 0.6918993601661659, 'recall': 0.6649122643354695, 'f1-score': 0.6716800133815666, 'support': 29334.0} | {'precision': 0.7980829724295806, 'recall': 0.7996863707643008, 'f1-score': 0.7930703491848509, 'support': 29334.0} |
79
+ | No log | 4.0 | 324 | 0.5089 | {'precision': 0.4666666666666667, 'recall': 0.6654929577464789, 'f1-score': 0.5486211901306242, 'support': 284.0} | {'precision': 0.6477987421383647, 'recall': 0.7304964539007093, 'f1-score': 0.6866666666666668, 'support': 141.0} | {'precision': 0.7981366459627329, 'recall': 0.7259887005649718, 'f1-score': 0.7603550295857988, 'support': 708.0} | {'precision': 0.5201636469900643, 'recall': 0.6548933038999264, 'f1-score': 0.5798045602605862, 'support': 4077.0} | {'precision': 0.7390321121664405, 'recall': 0.8073122529644269, 'f1-score': 0.7716646989374262, 'support': 2024.0} | {'precision': 0.899807994414383, 'recall': 0.842871157619359, 'f1-score': 0.8704094554664417, 'support': 12232.0} | {'precision': 0.9231016731016731, 'recall': 0.8722132144304824, 'f1-score': 0.8969362234264276, 'support': 9868.0} | 0.8191 | {'precision': 0.7135296402057607, 'recall': 0.7570382915894793, 'f1-score': 0.7306368320677102, 'support': 29334.0} | {'precision': 0.835926930625345, 'recall': 0.8190836571896093, 'f1-score': 0.825475128990697, 'support': 29334.0} |
80
+ | No log | 5.0 | 405 | 0.5750 | {'precision': 0.5029585798816568, 'recall': 0.5985915492957746, 'f1-score': 0.5466237942122186, 'support': 284.0} | {'precision': 0.728, 'recall': 0.6453900709219859, 'f1-score': 0.6842105263157895, 'support': 141.0} | {'precision': 0.7608695652173914, 'recall': 0.7909604519774012, 'f1-score': 0.775623268698061, 'support': 708.0} | {'precision': 0.5492530345471522, 'recall': 0.577140053961246, 'f1-score': 0.5628513335725392, 'support': 4077.0} | {'precision': 0.8153946510110893, 'recall': 0.6175889328063241, 'f1-score': 0.7028394714647174, 'support': 2024.0} | {'precision': 0.8660855784469097, 'recall': 0.8935578809679529, 'f1-score': 0.8796072750684049, 'support': 12232.0} | {'precision': 0.9043101670447515, 'recall': 0.8887312525334414, 'f1-score': 0.8964530307676581, 'support': 9868.0} | 0.8224 | {'precision': 0.7324102251641358, 'recall': 0.715994313209161, 'f1-score': 0.7211726714427698, 'support': 29334.0} | {'precision': 0.8246928072651426, 'recall': 0.8223904002181769, 'f1-score': 0.8223802682715222, 'support': 29334.0} |
81
+ | No log | 6.0 | 486 | 0.5503 | {'precision': 0.5160349854227405, 'recall': 0.6232394366197183, 'f1-score': 0.5645933014354066, 'support': 284.0} | {'precision': 0.6923076923076923, 'recall': 0.7659574468085106, 'f1-score': 0.7272727272727273, 'support': 141.0} | {'precision': 0.7780859916782247, 'recall': 0.7923728813559322, 'f1-score': 0.7851644506648006, 'support': 708.0} | {'precision': 0.5575316048853654, 'recall': 0.6382143733137111, 'f1-score': 0.5951509606587375, 'support': 4077.0} | {'precision': 0.7698019801980198, 'recall': 0.7682806324110671, 'f1-score': 0.7690405539070228, 'support': 2024.0} | {'precision': 0.8899397388684298, 'recall': 0.8692773054283846, 'f1-score': 0.8794871794871795, 'support': 12232.0} | {'precision': 0.9260470513767275, 'recall': 0.8895419537900284, 'f1-score': 0.907427508140797, 'support': 9868.0} | 0.8323 | {'precision': 0.7328212921053143, 'recall': 0.763840575675336, 'f1-score': 0.7468766687952387, 'support': 29334.0} | {'precision': 0.8403274341189826, 'recall': 0.8322765391695643, 'f1-score': 0.835690214793681, 'support': 29334.0} |
82
+ | 0.4181 | 7.0 | 567 | 0.6419 | {'precision': 0.5571428571428572, 'recall': 0.5492957746478874, 'f1-score': 0.5531914893617021, 'support': 284.0} | {'precision': 0.7152777777777778, 'recall': 0.7304964539007093, 'f1-score': 0.7228070175438596, 'support': 141.0} | {'precision': 0.7544529262086515, 'recall': 0.8375706214689266, 'f1-score': 0.7938420348058902, 'support': 708.0} | {'precision': 0.6019025655808591, 'recall': 0.5121412803532008, 'f1-score': 0.5534057778955738, 'support': 4077.0} | {'precision': 0.8124655267512411, 'recall': 0.7277667984189723, 'f1-score': 0.7677873338545738, 'support': 2024.0} | {'precision': 0.855129565085619, 'recall': 0.9226618705035972, 'f1-score': 0.8876130554463233, 'support': 12232.0} | {'precision': 0.9203649937785151, 'recall': 0.8994730441832185, 'f1-score': 0.9097990979909799, 'support': 9868.0} | 0.8378 | {'precision': 0.7452480303322171, 'recall': 0.7399151204966445, 'f1-score': 0.7412065438427005, 'support': 29334.0} | {'precision': 0.8329491032454597, 'recall': 0.8377650507943001, 'f1-score': 0.8340655773672634, 'support': 29334.0} |
83
+ | 0.4181 | 8.0 | 648 | 0.6668 | {'precision': 0.5745454545454546, 'recall': 0.5563380281690141, 'f1-score': 0.5652951699463328, 'support': 284.0} | {'precision': 0.7027027027027027, 'recall': 0.7375886524822695, 'f1-score': 0.7197231833910034, 'support': 141.0} | {'precision': 0.7538071065989848, 'recall': 0.8389830508474576, 'f1-score': 0.7941176470588234, 'support': 708.0} | {'precision': 0.6235260281852172, 'recall': 0.5317635516311013, 'f1-score': 0.5740005295207837, 'support': 4077.0} | {'precision': 0.8115154807170016, 'recall': 0.7381422924901185, 'f1-score': 0.773091849935317, 'support': 2024.0} | {'precision': 0.8614178024822965, 'recall': 0.9248691955526488, 'f1-score': 0.8920165582495565, 'support': 12232.0} | {'precision': 0.9189412737799835, 'recall': 0.9006890960680989, 'f1-score': 0.9097236438075741, 'support': 9868.0} | 0.8427 | {'precision': 0.7494936927159488, 'recall': 0.7469105524629585, 'f1-score': 0.7468526545584844, 'support': 29334.0} | {'precision': 0.8381245456177384, 'recall': 0.8426740301356788, 'f1-score': 0.8392138000943469, 'support': 29334.0} |
84
+ | 0.4181 | 9.0 | 729 | 0.7192 | {'precision': 0.5454545454545454, 'recall': 0.6338028169014085, 'f1-score': 0.5863192182410424, 'support': 284.0} | {'precision': 0.6928104575163399, 'recall': 0.75177304964539, 'f1-score': 0.7210884353741497, 'support': 141.0} | {'precision': 0.7757404795486601, 'recall': 0.7768361581920904, 'f1-score': 0.7762879322512349, 'support': 708.0} | {'precision': 0.5975181456333412, 'recall': 0.6259504537650233, 'f1-score': 0.6114039290848108, 'support': 4077.0} | {'precision': 0.7642474427666829, 'recall': 0.775197628458498, 'f1-score': 0.7696835908756438, 'support': 2024.0} | {'precision': 0.893157763146929, 'recall': 0.8761445389143231, 'f1-score': 0.8845693533077462, 'support': 12232.0} | {'precision': 0.9098686220592729, 'recall': 0.9053506282934739, 'f1-score': 0.9076040026413369, 'support': 9868.0} | 0.8389 | {'precision': 0.7398282080179673, 'recall': 0.7635793248814581, 'f1-score': 0.7509937802537092, 'support': 29334.0} | {'precision': 0.8416318009865815, 'recall': 0.8388900252266994, 'f1-score': 0.8401384747371046, 'support': 29334.0} |
85
+ | 0.4181 | 10.0 | 810 | 0.8728 | {'precision': 0.5584905660377358, 'recall': 0.5211267605633803, 'f1-score': 0.5391621129326047, 'support': 284.0} | {'precision': 0.6948051948051948, 'recall': 0.7588652482269503, 'f1-score': 0.7254237288135594, 'support': 141.0} | {'precision': 0.7503201024327785, 'recall': 0.827683615819209, 'f1-score': 0.7871054398925452, 'support': 708.0} | {'precision': 0.5859070464767616, 'recall': 0.4792739759627177, 'f1-score': 0.5272531030760929, 'support': 4077.0} | {'precision': 0.7485322896281801, 'recall': 0.7559288537549407, 'f1-score': 0.7522123893805309, 'support': 2024.0} | {'precision': 0.8385786052009456, 'recall': 0.92797580117724, 'f1-score': 0.8810152126668737, 'support': 12232.0} | {'precision': 0.9320967566981234, 'recall': 0.8707944872314552, 'f1-score': 0.9004034159375491, 'support': 9868.0} | 0.8273 | {'precision': 0.7298186516113886, 'recall': 0.7345212489622704, 'f1-score': 0.7303679146713938, 'support': 29334.0} | {'precision': 0.8231745470223255, 'recall': 0.8273334696938706, 'f1-score': 0.8231582874630071, 'support': 29334.0} |
86
+ | 0.4181 | 11.0 | 891 | 0.7904 | {'precision': 0.5487804878048781, 'recall': 0.6338028169014085, 'f1-score': 0.5882352941176471, 'support': 284.0} | {'precision': 0.6956521739130435, 'recall': 0.7943262411347518, 'f1-score': 0.7417218543046358, 'support': 141.0} | {'precision': 0.7777777777777778, 'recall': 0.7810734463276836, 'f1-score': 0.7794221282593374, 'support': 708.0} | {'precision': 0.600095785440613, 'recall': 0.6146676477802305, 'f1-score': 0.6072943172179812, 'support': 4077.0} | {'precision': 0.7808219178082192, 'recall': 0.7885375494071146, 'f1-score': 0.7846607669616519, 'support': 2024.0} | {'precision': 0.8951898734177215, 'recall': 0.8672334859385219, 'f1-score': 0.8809899510007474, 'support': 12232.0} | {'precision': 0.8980524642289348, 'recall': 0.9158897446291042, 'f1-score': 0.9068834035721453, 'support': 9868.0} | 0.8384 | {'precision': 0.742338640055884, 'recall': 0.7707901331598307, 'f1-score': 0.755601102204878, 'support': 29334.0} | {'precision': 0.8401010980182351, 'recall': 0.8383786732119725, 'f1-score': 0.8390590885154817, 'support': 29334.0} |
87
+ | 0.4181 | 12.0 | 972 | 0.9021 | {'precision': 0.5766423357664233, 'recall': 0.5563380281690141, 'f1-score': 0.5663082437275986, 'support': 284.0} | {'precision': 0.7272727272727273, 'recall': 0.7375886524822695, 'f1-score': 0.7323943661971831, 'support': 141.0} | {'precision': 0.7567221510883483, 'recall': 0.8347457627118644, 'f1-score': 0.793821356615178, 'support': 708.0} | {'precision': 0.6302699423718532, 'recall': 0.5096884964434634, 'f1-score': 0.5636018443178736, 'support': 4077.0} | {'precision': 0.7813152400835073, 'recall': 0.7396245059288538, 'f1-score': 0.7598984771573604, 'support': 2024.0} | {'precision': 0.8537686174213931, 'recall': 0.9278940483976456, 'f1-score': 0.889289352033221, 'support': 12232.0} | {'precision': 0.9143213210094506, 'recall': 0.892176732873936, 'f1-score': 0.9031132994819715, 'support': 9868.0} | 0.8380 | {'precision': 0.7486160478591003, 'recall': 0.7425794610010066, 'f1-score': 0.7440609913614838, 'support': 29334.0} | {'precision': 0.8324430451309904, 'recall': 0.838003681734506, 'f1-score': 0.8335608269497821, 'support': 29334.0} |
88
+ | 0.0774 | 13.0 | 1053 | 0.9174 | {'precision': 0.5379939209726444, 'recall': 0.6232394366197183, 'f1-score': 0.5774877650897227, 'support': 284.0} | {'precision': 0.7013888888888888, 'recall': 0.7163120567375887, 'f1-score': 0.7087719298245613, 'support': 141.0} | {'precision': 0.7626666666666667, 'recall': 0.807909604519774, 'f1-score': 0.784636488340192, 'support': 708.0} | {'precision': 0.5750291715285881, 'recall': 0.6043659553593328, 'f1-score': 0.5893326955273857, 'support': 4077.0} | {'precision': 0.7868589743589743, 'recall': 0.7277667984189723, 'f1-score': 0.7561601642710472, 'support': 2024.0} | {'precision': 0.8721798538290435, 'recall': 0.8975637671680837, 'f1-score': 0.8846897663174859, 'support': 12232.0} | {'precision': 0.9202434336963485, 'recall': 0.8734292663153628, 'f1-score': 0.8962254341270668, 'support': 9868.0} | 0.8313 | {'precision': 0.7366229871344505, 'recall': 0.7500838407341189, 'f1-score': 0.7424720347853516, 'support': 29334.0} | {'precision': 0.8344622887797986, 'recall': 0.8312879252744256, 'f1-score': 0.8324170375280131, 'support': 29334.0} |
89
+ | 0.0774 | 14.0 | 1134 | 0.9774 | {'precision': 0.5398773006134969, 'recall': 0.6197183098591549, 'f1-score': 0.5770491803278688, 'support': 284.0} | {'precision': 0.6871165644171779, 'recall': 0.7943262411347518, 'f1-score': 0.736842105263158, 'support': 141.0} | {'precision': 0.7735334242837654, 'recall': 0.8008474576271186, 'f1-score': 0.7869535045107564, 'support': 708.0} | {'precision': 0.5810174281676872, 'recall': 0.6051017905322541, 'f1-score': 0.5928150907124834, 'support': 4077.0} | {'precision': 0.7494387067804221, 'recall': 0.8246047430830039, 'f1-score': 0.7852270054104916, 'support': 2024.0} | {'precision': 0.8794297680412371, 'recall': 0.8926586003924133, 'f1-score': 0.8859948068808828, 'support': 12232.0} | {'precision': 0.9270302504608046, 'recall': 0.8664369679773004, 'f1-score': 0.8957100204284741, 'support': 9868.0} | 0.8338 | {'precision': 0.733920491823513, 'recall': 0.7719563015151424, 'f1-score': 0.751513101933445, 'support': 29334.0} | {'precision': 0.8382307794620859, 'recall': 0.8338446853480602, 'f1-score': 0.835464012013009, 'support': 29334.0} |
90
+ | 0.0774 | 15.0 | 1215 | 0.9720 | {'precision': 0.5487804878048781, 'recall': 0.6338028169014085, 'f1-score': 0.5882352941176471, 'support': 284.0} | {'precision': 0.7445255474452555, 'recall': 0.723404255319149, 'f1-score': 0.7338129496402878, 'support': 141.0} | {'precision': 0.7593582887700535, 'recall': 0.8022598870056498, 'f1-score': 0.7802197802197803, 'support': 708.0} | {'precision': 0.570828729281768, 'recall': 0.6335540838852097, 'f1-score': 0.6005580097651709, 'support': 4077.0} | {'precision': 0.7954422137818774, 'recall': 0.724308300395257, 'f1-score': 0.7582104990949057, 'support': 2024.0} | {'precision': 0.8803978651140223, 'recall': 0.8900425114453892, 'f1-score': 0.885193918204732, 'support': 12232.0} | {'precision': 0.9188239054010866, 'recall': 0.874037292257803, 'f1-score': 0.8958712022851208, 'support': 9868.0} | 0.8322 | {'precision': 0.7454510053712774, 'recall': 0.7544870210299808, 'f1-score': 0.748871664761092, 'support': 29334.0} | {'precision': 0.8376519459918353, 'recall': 0.8321742687666189, 'f1-score': 0.8343275428320325, 'support': 29334.0} |
91
+ | 0.0774 | 16.0 | 1296 | 1.0037 | {'precision': 0.5662251655629139, 'recall': 0.602112676056338, 'f1-score': 0.5836177474402731, 'support': 284.0} | {'precision': 0.7094594594594594, 'recall': 0.7446808510638298, 'f1-score': 0.726643598615917, 'support': 141.0} | {'precision': 0.766042780748663, 'recall': 0.809322033898305, 'f1-score': 0.7870879120879121, 'support': 708.0} | {'precision': 0.5981858298602599, 'recall': 0.5984792739759627, 'f1-score': 0.5983325159391859, 'support': 4077.0} | {'precision': 0.7981220657276995, 'recall': 0.7559288537549407, 'f1-score': 0.7764526769855367, 'support': 2024.0} | {'precision': 0.8736565560066873, 'recall': 0.8971550032701112, 'f1-score': 0.885249868914613, 'support': 12232.0} | {'precision': 0.9181542958555173, 'recall': 0.8912646939602756, 'f1-score': 0.9045096930117758, 'support': 9868.0} | 0.8382 | {'precision': 0.7471208790316002, 'recall': 0.7569919122828231, 'f1-score': 0.751699144713602, 'support': 29334.0} | {'precision': 0.8387644471781172, 'recall': 0.8382082225403968, 'f1-score': 0.838292846606077, 'support': 29334.0} |
92
+ | 0.0774 | 17.0 | 1377 | 1.0845 | {'precision': 0.5382165605095541, 'recall': 0.5950704225352113, 'f1-score': 0.5652173913043479, 'support': 284.0} | {'precision': 0.7163120567375887, 'recall': 0.7163120567375887, 'f1-score': 0.7163120567375887, 'support': 141.0} | {'precision': 0.7509627727856226, 'recall': 0.826271186440678, 'f1-score': 0.7868190988567586, 'support': 708.0} | {'precision': 0.5689655172413793, 'recall': 0.5827814569536424, 'f1-score': 0.5757906215921483, 'support': 4077.0} | {'precision': 0.7852169255490091, 'recall': 0.724308300395257, 'f1-score': 0.7535337959393473, 'support': 2024.0} | {'precision': 0.8561790861698866, 'recall': 0.9130150425114454, 'f1-score': 0.8836841272353221, 'support': 12232.0} | {'precision': 0.9375346721402419, 'recall': 0.8563032022699635, 'f1-score': 0.8950797097611355, 'support': 9868.0} | 0.8289 | {'precision': 0.7361982273047546, 'recall': 0.7448659525491124, 'f1-score': 0.7394909716323783, 'support': 29334.0} | {'precision': 0.8324422630439487, 'recall': 0.8289016158723665, 'f1-score': 0.829519030769714, 'support': 29334.0} |
93
+ | 0.0774 | 18.0 | 1458 | 1.0618 | {'precision': 0.5774647887323944, 'recall': 0.5774647887323944, 'f1-score': 0.5774647887323944, 'support': 284.0} | {'precision': 0.7571428571428571, 'recall': 0.75177304964539, 'f1-score': 0.7544483985765125, 'support': 141.0} | {'precision': 0.754863813229572, 'recall': 0.8220338983050848, 'f1-score': 0.7870182555780934, 'support': 708.0} | {'precision': 0.59768299104792, 'recall': 0.5567819475104243, 'f1-score': 0.5765079365079365, 'support': 4077.0} | {'precision': 0.7977588046958378, 'recall': 0.7386363636363636, 'f1-score': 0.767060030785018, 'support': 2024.0} | {'precision': 0.8586523736600307, 'recall': 0.9167756703727927, 'f1-score': 0.8867626126838526, 'support': 12232.0} | {'precision': 0.9229297331774211, 'recall': 0.879813538710985, 'f1-score': 0.9008560311284047, 'support': 9868.0} | 0.8357 | {'precision': 0.7523564802408619, 'recall': 0.7490398938447764, 'f1-score': 0.7500168648560301, 'support': 29334.0} | {'precision': 0.8340875618543231, 'recall': 0.8356514624667621, 'f1-score': 0.8340855697185618, 'support': 29334.0} |
94
+ | 0.0228 | 19.0 | 1539 | 1.0645 | {'precision': 0.5694444444444444, 'recall': 0.5774647887323944, 'f1-score': 0.5734265734265734, 'support': 284.0} | {'precision': 0.7394366197183099, 'recall': 0.7446808510638298, 'f1-score': 0.7420494699646644, 'support': 141.0} | {'precision': 0.7552083333333334, 'recall': 0.8192090395480226, 'f1-score': 0.7859078590785908, 'support': 708.0} | {'precision': 0.5936120488184887, 'recall': 0.5607064017660044, 'f1-score': 0.5766902119071644, 'support': 4077.0} | {'precision': 0.7824947589098532, 'recall': 0.7376482213438735, 'f1-score': 0.7594099694811801, 'support': 2024.0} | {'precision': 0.8594939629316312, 'recall': 0.9136690647482014, 'f1-score': 0.8857539132157718, 'support': 12232.0} | {'precision': 0.9252186899935994, 'recall': 0.8789014997973247, 'f1-score': 0.9014655441222326, 'support': 9868.0} | 0.8344 | {'precision': 0.7464155511642371, 'recall': 0.7474685524285215, 'f1-score': 0.7463862201708825, 'support': 29334.0} | {'precision': 0.8334350647066741, 'recall': 0.8344242176314175, 'f1-score': 0.8332419893084726, 'support': 29334.0} |
95
+ | 0.0228 | 20.0 | 1620 | 1.0525 | {'precision': 0.5714285714285714, 'recall': 0.5915492957746479, 'f1-score': 0.5813148788927336, 'support': 284.0} | {'precision': 0.7328767123287672, 'recall': 0.7588652482269503, 'f1-score': 0.7456445993031359, 'support': 141.0} | {'precision': 0.7592592592592593, 'recall': 0.8107344632768362, 'f1-score': 0.7841530054644807, 'support': 708.0} | {'precision': 0.5995872033023736, 'recall': 0.5700269806230072, 'f1-score': 0.5844335470891487, 'support': 4077.0} | {'precision': 0.7741293532338308, 'recall': 0.7687747035573123, 'f1-score': 0.7714427367377293, 'support': 2024.0} | {'precision': 0.8661675245671502, 'recall': 0.907946370176586, 'f1-score': 0.8865650195577552, 'support': 12232.0} | {'precision': 0.9227995758218451, 'recall': 0.8818402918524524, 'f1-score': 0.9018551145196393, 'support': 9868.0} | 0.8365 | {'precision': 0.746606885705971, 'recall': 0.7556767647839704, 'f1-score': 0.7507727002235176, 'support': 29334.0} | {'precision': 0.8357427933389249, 'recall': 0.8364696256903252, 'f1-score': 0.8356690155425791, 'support': 29334.0} |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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1
+ ---
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+ license: apache-2.0
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+ base_model: allenai/longformer-base-4096
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - essays_su_g
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: longformer-full_labels
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+ results:
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+ - task:
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+ name: Token Classification
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+ type: token-classification
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+ dataset:
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+ name: essays_su_g
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+ type: essays_su_g
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+ config: full_labels
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+ split: train[0%:20%]
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+ args: full_labels
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.8364696256903252
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
29
+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # longformer-full_labels
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+
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+ 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.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0525
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+ - B-claim: {'precision': 0.5714285714285714, 'recall': 0.5915492957746479, 'f1-score': 0.5813148788927336, 'support': 284.0}
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+ - B-majorclaim: {'precision': 0.7328767123287672, 'recall': 0.7588652482269503, 'f1-score': 0.7456445993031359, 'support': 141.0}
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+ - B-premise: {'precision': 0.7592592592592593, 'recall': 0.8107344632768362, 'f1-score': 0.7841530054644807, 'support': 708.0}
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+ - I-claim: {'precision': 0.5995872033023736, 'recall': 0.5700269806230072, 'f1-score': 0.5844335470891487, 'support': 4077.0}
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+ - I-majorclaim: {'precision': 0.7741293532338308, 'recall': 0.7687747035573123, 'f1-score': 0.7714427367377293, 'support': 2024.0}
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+ - I-premise: {'precision': 0.8661675245671502, 'recall': 0.907946370176586, 'f1-score': 0.8865650195577552, 'support': 12232.0}
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+ - O: {'precision': 0.9227995758218451, 'recall': 0.8818402918524524, 'f1-score': 0.9018551145196393, 'support': 9868.0}
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+ - Accuracy: 0.8365
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+ - Macro avg: {'precision': 0.746606885705971, 'recall': 0.7556767647839704, 'f1-score': 0.7507727002235176, 'support': 29334.0}
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+ - Weighted avg: {'precision': 0.8357427933389249, 'recall': 0.8364696256903252, 'f1-score': 0.8356690155425791, 'support': 29334.0}
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
57
+ More information needed
58
+
59
+ ## Training procedure
60
+
61
+ ### Training hyperparameters
62
+
63
+ The following hyperparameters were used during training:
64
+ - learning_rate: 2e-05
65
+ - train_batch_size: 8
66
+ - eval_batch_size: 8
67
+ - seed: 42
68
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
69
+ - lr_scheduler_type: linear
70
+ - num_epochs: 20
71
+
72
+ ### Training results
73
+
74
+ | Training Loss | Epoch | Step | Validation Loss | B-claim | B-majorclaim | B-premise | I-claim | I-majorclaim | I-premise | O | Accuracy | Macro avg | Weighted avg |
75
+ |:-------------:|:-----:|:----:|:---------------:|:------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:--------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
76
+ | No log | 1.0 | 81 | 0.6443 | {'precision': 0.5, 'recall': 0.0035211267605633804, 'f1-score': 0.006993006993006993, 'support': 284.0} | {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 141.0} | {'precision': 0.5883777239709443, 'recall': 0.6864406779661016, 'f1-score': 0.6336375488917861, 'support': 708.0} | {'precision': 0.41618672324946954, 'recall': 0.3367672308069659, 'f1-score': 0.37228850325379614, 'support': 4077.0} | {'precision': 0.5611921369689283, 'recall': 0.43725296442687744, 'f1-score': 0.49153013051930017, 'support': 2024.0} | {'precision': 0.7746890504995582, 'recall': 0.9318181818181818, 'f1-score': 0.846019669697532, 'support': 12232.0} | {'precision': 0.9111808904340025, 'recall': 0.8233684637211187, 'f1-score': 0.8650519031141869, 'support': 9868.0} | 0.7591 | {'precision': 0.535946646446129, 'recall': 0.4598812350714013, 'f1-score': 0.4593601089242298, 'support': 29334.0} | {'precision': 0.7451676238152983, 'recall': 0.7591191109292971, 'f1-score': 0.7448054609057474, 'support': 29334.0} |
77
+ | No log | 2.0 | 162 | 0.5139 | {'precision': 0.4420731707317073, 'recall': 0.5105633802816901, 'f1-score': 0.47385620915032683, 'support': 284.0} | {'precision': 0.6274509803921569, 'recall': 0.45390070921985815, 'f1-score': 0.5267489711934156, 'support': 141.0} | {'precision': 0.7261306532663316, 'recall': 0.8163841807909604, 'f1-score': 0.7686170212765958, 'support': 708.0} | {'precision': 0.5221008840353614, 'recall': 0.49251900907530044, 'f1-score': 0.5068787075602675, 'support': 4077.0} | {'precision': 0.5741007194244604, 'recall': 0.7885375494071146, 'f1-score': 0.6644462947543713, 'support': 2024.0} | {'precision': 0.8642982877260361, 'recall': 0.8830935251798561, 'f1-score': 0.8735948241002829, 'support': 12232.0} | {'precision': 0.925979519145147, 'recall': 0.8430279691933522, 'f1-score': 0.8825588796944621, 'support': 9868.0} | 0.8015 | {'precision': 0.668876316388743, 'recall': 0.6840037604497332, 'f1-score': 0.6709572725328175, 'support': 29334.0} | {'precision': 0.8089032379475054, 'recall': 0.8015272380173177, 'f1-score': 0.8031401896750007, 'support': 29334.0} |
78
+ | No log | 3.0 | 243 | 0.5770 | {'precision': 0.4393939393939394, 'recall': 0.4084507042253521, 'f1-score': 0.4233576642335767, 'support': 284.0} | {'precision': 0.7181818181818181, 'recall': 0.5602836879432624, 'f1-score': 0.6294820717131473, 'support': 141.0} | {'precision': 0.6709816612729234, 'recall': 0.8785310734463276, 'f1-score': 0.7608562691131499, 'support': 708.0} | {'precision': 0.5186211141889813, 'recall': 0.41329408879077756, 'f1-score': 0.46000546000546, 'support': 4077.0} | {'precision': 0.7556615017878426, 'recall': 0.6264822134387352, 'f1-score': 0.6850351161534306, 'support': 2024.0} | {'precision': 0.7999862438957287, 'recall': 0.9508665794637018, 'f1-score': 0.8689253296477533, 'support': 12232.0} | {'precision': 0.9404692424419283, 'recall': 0.8164775030401297, 'f1-score': 0.8740981828044481, 'support': 9868.0} | 0.7997 | {'precision': 0.6918993601661659, 'recall': 0.6649122643354695, 'f1-score': 0.6716800133815666, 'support': 29334.0} | {'precision': 0.7980829724295806, 'recall': 0.7996863707643008, 'f1-score': 0.7930703491848509, 'support': 29334.0} |
79
+ | No log | 4.0 | 324 | 0.5089 | {'precision': 0.4666666666666667, 'recall': 0.6654929577464789, 'f1-score': 0.5486211901306242, 'support': 284.0} | {'precision': 0.6477987421383647, 'recall': 0.7304964539007093, 'f1-score': 0.6866666666666668, 'support': 141.0} | {'precision': 0.7981366459627329, 'recall': 0.7259887005649718, 'f1-score': 0.7603550295857988, 'support': 708.0} | {'precision': 0.5201636469900643, 'recall': 0.6548933038999264, 'f1-score': 0.5798045602605862, 'support': 4077.0} | {'precision': 0.7390321121664405, 'recall': 0.8073122529644269, 'f1-score': 0.7716646989374262, 'support': 2024.0} | {'precision': 0.899807994414383, 'recall': 0.842871157619359, 'f1-score': 0.8704094554664417, 'support': 12232.0} | {'precision': 0.9231016731016731, 'recall': 0.8722132144304824, 'f1-score': 0.8969362234264276, 'support': 9868.0} | 0.8191 | {'precision': 0.7135296402057607, 'recall': 0.7570382915894793, 'f1-score': 0.7306368320677102, 'support': 29334.0} | {'precision': 0.835926930625345, 'recall': 0.8190836571896093, 'f1-score': 0.825475128990697, 'support': 29334.0} |
80
+ | No log | 5.0 | 405 | 0.5750 | {'precision': 0.5029585798816568, 'recall': 0.5985915492957746, 'f1-score': 0.5466237942122186, 'support': 284.0} | {'precision': 0.728, 'recall': 0.6453900709219859, 'f1-score': 0.6842105263157895, 'support': 141.0} | {'precision': 0.7608695652173914, 'recall': 0.7909604519774012, 'f1-score': 0.775623268698061, 'support': 708.0} | {'precision': 0.5492530345471522, 'recall': 0.577140053961246, 'f1-score': 0.5628513335725392, 'support': 4077.0} | {'precision': 0.8153946510110893, 'recall': 0.6175889328063241, 'f1-score': 0.7028394714647174, 'support': 2024.0} | {'precision': 0.8660855784469097, 'recall': 0.8935578809679529, 'f1-score': 0.8796072750684049, 'support': 12232.0} | {'precision': 0.9043101670447515, 'recall': 0.8887312525334414, 'f1-score': 0.8964530307676581, 'support': 9868.0} | 0.8224 | {'precision': 0.7324102251641358, 'recall': 0.715994313209161, 'f1-score': 0.7211726714427698, 'support': 29334.0} | {'precision': 0.8246928072651426, 'recall': 0.8223904002181769, 'f1-score': 0.8223802682715222, 'support': 29334.0} |
81
+ | No log | 6.0 | 486 | 0.5503 | {'precision': 0.5160349854227405, 'recall': 0.6232394366197183, 'f1-score': 0.5645933014354066, 'support': 284.0} | {'precision': 0.6923076923076923, 'recall': 0.7659574468085106, 'f1-score': 0.7272727272727273, 'support': 141.0} | {'precision': 0.7780859916782247, 'recall': 0.7923728813559322, 'f1-score': 0.7851644506648006, 'support': 708.0} | {'precision': 0.5575316048853654, 'recall': 0.6382143733137111, 'f1-score': 0.5951509606587375, 'support': 4077.0} | {'precision': 0.7698019801980198, 'recall': 0.7682806324110671, 'f1-score': 0.7690405539070228, 'support': 2024.0} | {'precision': 0.8899397388684298, 'recall': 0.8692773054283846, 'f1-score': 0.8794871794871795, 'support': 12232.0} | {'precision': 0.9260470513767275, 'recall': 0.8895419537900284, 'f1-score': 0.907427508140797, 'support': 9868.0} | 0.8323 | {'precision': 0.7328212921053143, 'recall': 0.763840575675336, 'f1-score': 0.7468766687952387, 'support': 29334.0} | {'precision': 0.8403274341189826, 'recall': 0.8322765391695643, 'f1-score': 0.835690214793681, 'support': 29334.0} |
82
+ | 0.4181 | 7.0 | 567 | 0.6419 | {'precision': 0.5571428571428572, 'recall': 0.5492957746478874, 'f1-score': 0.5531914893617021, 'support': 284.0} | {'precision': 0.7152777777777778, 'recall': 0.7304964539007093, 'f1-score': 0.7228070175438596, 'support': 141.0} | {'precision': 0.7544529262086515, 'recall': 0.8375706214689266, 'f1-score': 0.7938420348058902, 'support': 708.0} | {'precision': 0.6019025655808591, 'recall': 0.5121412803532008, 'f1-score': 0.5534057778955738, 'support': 4077.0} | {'precision': 0.8124655267512411, 'recall': 0.7277667984189723, 'f1-score': 0.7677873338545738, 'support': 2024.0} | {'precision': 0.855129565085619, 'recall': 0.9226618705035972, 'f1-score': 0.8876130554463233, 'support': 12232.0} | {'precision': 0.9203649937785151, 'recall': 0.8994730441832185, 'f1-score': 0.9097990979909799, 'support': 9868.0} | 0.8378 | {'precision': 0.7452480303322171, 'recall': 0.7399151204966445, 'f1-score': 0.7412065438427005, 'support': 29334.0} | {'precision': 0.8329491032454597, 'recall': 0.8377650507943001, 'f1-score': 0.8340655773672634, 'support': 29334.0} |
83
+ | 0.4181 | 8.0 | 648 | 0.6668 | {'precision': 0.5745454545454546, 'recall': 0.5563380281690141, 'f1-score': 0.5652951699463328, 'support': 284.0} | {'precision': 0.7027027027027027, 'recall': 0.7375886524822695, 'f1-score': 0.7197231833910034, 'support': 141.0} | {'precision': 0.7538071065989848, 'recall': 0.8389830508474576, 'f1-score': 0.7941176470588234, 'support': 708.0} | {'precision': 0.6235260281852172, 'recall': 0.5317635516311013, 'f1-score': 0.5740005295207837, 'support': 4077.0} | {'precision': 0.8115154807170016, 'recall': 0.7381422924901185, 'f1-score': 0.773091849935317, 'support': 2024.0} | {'precision': 0.8614178024822965, 'recall': 0.9248691955526488, 'f1-score': 0.8920165582495565, 'support': 12232.0} | {'precision': 0.9189412737799835, 'recall': 0.9006890960680989, 'f1-score': 0.9097236438075741, 'support': 9868.0} | 0.8427 | {'precision': 0.7494936927159488, 'recall': 0.7469105524629585, 'f1-score': 0.7468526545584844, 'support': 29334.0} | {'precision': 0.8381245456177384, 'recall': 0.8426740301356788, 'f1-score': 0.8392138000943469, 'support': 29334.0} |
84
+ | 0.4181 | 9.0 | 729 | 0.7192 | {'precision': 0.5454545454545454, 'recall': 0.6338028169014085, 'f1-score': 0.5863192182410424, 'support': 284.0} | {'precision': 0.6928104575163399, 'recall': 0.75177304964539, 'f1-score': 0.7210884353741497, 'support': 141.0} | {'precision': 0.7757404795486601, 'recall': 0.7768361581920904, 'f1-score': 0.7762879322512349, 'support': 708.0} | {'precision': 0.5975181456333412, 'recall': 0.6259504537650233, 'f1-score': 0.6114039290848108, 'support': 4077.0} | {'precision': 0.7642474427666829, 'recall': 0.775197628458498, 'f1-score': 0.7696835908756438, 'support': 2024.0} | {'precision': 0.893157763146929, 'recall': 0.8761445389143231, 'f1-score': 0.8845693533077462, 'support': 12232.0} | {'precision': 0.9098686220592729, 'recall': 0.9053506282934739, 'f1-score': 0.9076040026413369, 'support': 9868.0} | 0.8389 | {'precision': 0.7398282080179673, 'recall': 0.7635793248814581, 'f1-score': 0.7509937802537092, 'support': 29334.0} | {'precision': 0.8416318009865815, 'recall': 0.8388900252266994, 'f1-score': 0.8401384747371046, 'support': 29334.0} |
85
+ | 0.4181 | 10.0 | 810 | 0.8728 | {'precision': 0.5584905660377358, 'recall': 0.5211267605633803, 'f1-score': 0.5391621129326047, 'support': 284.0} | {'precision': 0.6948051948051948, 'recall': 0.7588652482269503, 'f1-score': 0.7254237288135594, 'support': 141.0} | {'precision': 0.7503201024327785, 'recall': 0.827683615819209, 'f1-score': 0.7871054398925452, 'support': 708.0} | {'precision': 0.5859070464767616, 'recall': 0.4792739759627177, 'f1-score': 0.5272531030760929, 'support': 4077.0} | {'precision': 0.7485322896281801, 'recall': 0.7559288537549407, 'f1-score': 0.7522123893805309, 'support': 2024.0} | {'precision': 0.8385786052009456, 'recall': 0.92797580117724, 'f1-score': 0.8810152126668737, 'support': 12232.0} | {'precision': 0.9320967566981234, 'recall': 0.8707944872314552, 'f1-score': 0.9004034159375491, 'support': 9868.0} | 0.8273 | {'precision': 0.7298186516113886, 'recall': 0.7345212489622704, 'f1-score': 0.7303679146713938, 'support': 29334.0} | {'precision': 0.8231745470223255, 'recall': 0.8273334696938706, 'f1-score': 0.8231582874630071, 'support': 29334.0} |
86
+ | 0.4181 | 11.0 | 891 | 0.7904 | {'precision': 0.5487804878048781, 'recall': 0.6338028169014085, 'f1-score': 0.5882352941176471, 'support': 284.0} | {'precision': 0.6956521739130435, 'recall': 0.7943262411347518, 'f1-score': 0.7417218543046358, 'support': 141.0} | {'precision': 0.7777777777777778, 'recall': 0.7810734463276836, 'f1-score': 0.7794221282593374, 'support': 708.0} | {'precision': 0.600095785440613, 'recall': 0.6146676477802305, 'f1-score': 0.6072943172179812, 'support': 4077.0} | {'precision': 0.7808219178082192, 'recall': 0.7885375494071146, 'f1-score': 0.7846607669616519, 'support': 2024.0} | {'precision': 0.8951898734177215, 'recall': 0.8672334859385219, 'f1-score': 0.8809899510007474, 'support': 12232.0} | {'precision': 0.8980524642289348, 'recall': 0.9158897446291042, 'f1-score': 0.9068834035721453, 'support': 9868.0} | 0.8384 | {'precision': 0.742338640055884, 'recall': 0.7707901331598307, 'f1-score': 0.755601102204878, 'support': 29334.0} | {'precision': 0.8401010980182351, 'recall': 0.8383786732119725, 'f1-score': 0.8390590885154817, 'support': 29334.0} |
87
+ | 0.4181 | 12.0 | 972 | 0.9021 | {'precision': 0.5766423357664233, 'recall': 0.5563380281690141, 'f1-score': 0.5663082437275986, 'support': 284.0} | {'precision': 0.7272727272727273, 'recall': 0.7375886524822695, 'f1-score': 0.7323943661971831, 'support': 141.0} | {'precision': 0.7567221510883483, 'recall': 0.8347457627118644, 'f1-score': 0.793821356615178, 'support': 708.0} | {'precision': 0.6302699423718532, 'recall': 0.5096884964434634, 'f1-score': 0.5636018443178736, 'support': 4077.0} | {'precision': 0.7813152400835073, 'recall': 0.7396245059288538, 'f1-score': 0.7598984771573604, 'support': 2024.0} | {'precision': 0.8537686174213931, 'recall': 0.9278940483976456, 'f1-score': 0.889289352033221, 'support': 12232.0} | {'precision': 0.9143213210094506, 'recall': 0.892176732873936, 'f1-score': 0.9031132994819715, 'support': 9868.0} | 0.8380 | {'precision': 0.7486160478591003, 'recall': 0.7425794610010066, 'f1-score': 0.7440609913614838, 'support': 29334.0} | {'precision': 0.8324430451309904, 'recall': 0.838003681734506, 'f1-score': 0.8335608269497821, 'support': 29334.0} |
88
+ | 0.0774 | 13.0 | 1053 | 0.9174 | {'precision': 0.5379939209726444, 'recall': 0.6232394366197183, 'f1-score': 0.5774877650897227, 'support': 284.0} | {'precision': 0.7013888888888888, 'recall': 0.7163120567375887, 'f1-score': 0.7087719298245613, 'support': 141.0} | {'precision': 0.7626666666666667, 'recall': 0.807909604519774, 'f1-score': 0.784636488340192, 'support': 708.0} | {'precision': 0.5750291715285881, 'recall': 0.6043659553593328, 'f1-score': 0.5893326955273857, 'support': 4077.0} | {'precision': 0.7868589743589743, 'recall': 0.7277667984189723, 'f1-score': 0.7561601642710472, 'support': 2024.0} | {'precision': 0.8721798538290435, 'recall': 0.8975637671680837, 'f1-score': 0.8846897663174859, 'support': 12232.0} | {'precision': 0.9202434336963485, 'recall': 0.8734292663153628, 'f1-score': 0.8962254341270668, 'support': 9868.0} | 0.8313 | {'precision': 0.7366229871344505, 'recall': 0.7500838407341189, 'f1-score': 0.7424720347853516, 'support': 29334.0} | {'precision': 0.8344622887797986, 'recall': 0.8312879252744256, 'f1-score': 0.8324170375280131, 'support': 29334.0} |
89
+ | 0.0774 | 14.0 | 1134 | 0.9774 | {'precision': 0.5398773006134969, 'recall': 0.6197183098591549, 'f1-score': 0.5770491803278688, 'support': 284.0} | {'precision': 0.6871165644171779, 'recall': 0.7943262411347518, 'f1-score': 0.736842105263158, 'support': 141.0} | {'precision': 0.7735334242837654, 'recall': 0.8008474576271186, 'f1-score': 0.7869535045107564, 'support': 708.0} | {'precision': 0.5810174281676872, 'recall': 0.6051017905322541, 'f1-score': 0.5928150907124834, 'support': 4077.0} | {'precision': 0.7494387067804221, 'recall': 0.8246047430830039, 'f1-score': 0.7852270054104916, 'support': 2024.0} | {'precision': 0.8794297680412371, 'recall': 0.8926586003924133, 'f1-score': 0.8859948068808828, 'support': 12232.0} | {'precision': 0.9270302504608046, 'recall': 0.8664369679773004, 'f1-score': 0.8957100204284741, 'support': 9868.0} | 0.8338 | {'precision': 0.733920491823513, 'recall': 0.7719563015151424, 'f1-score': 0.751513101933445, 'support': 29334.0} | {'precision': 0.8382307794620859, 'recall': 0.8338446853480602, 'f1-score': 0.835464012013009, 'support': 29334.0} |
90
+ | 0.0774 | 15.0 | 1215 | 0.9720 | {'precision': 0.5487804878048781, 'recall': 0.6338028169014085, 'f1-score': 0.5882352941176471, 'support': 284.0} | {'precision': 0.7445255474452555, 'recall': 0.723404255319149, 'f1-score': 0.7338129496402878, 'support': 141.0} | {'precision': 0.7593582887700535, 'recall': 0.8022598870056498, 'f1-score': 0.7802197802197803, 'support': 708.0} | {'precision': 0.570828729281768, 'recall': 0.6335540838852097, 'f1-score': 0.6005580097651709, 'support': 4077.0} | {'precision': 0.7954422137818774, 'recall': 0.724308300395257, 'f1-score': 0.7582104990949057, 'support': 2024.0} | {'precision': 0.8803978651140223, 'recall': 0.8900425114453892, 'f1-score': 0.885193918204732, 'support': 12232.0} | {'precision': 0.9188239054010866, 'recall': 0.874037292257803, 'f1-score': 0.8958712022851208, 'support': 9868.0} | 0.8322 | {'precision': 0.7454510053712774, 'recall': 0.7544870210299808, 'f1-score': 0.748871664761092, 'support': 29334.0} | {'precision': 0.8376519459918353, 'recall': 0.8321742687666189, 'f1-score': 0.8343275428320325, 'support': 29334.0} |
91
+ | 0.0774 | 16.0 | 1296 | 1.0037 | {'precision': 0.5662251655629139, 'recall': 0.602112676056338, 'f1-score': 0.5836177474402731, 'support': 284.0} | {'precision': 0.7094594594594594, 'recall': 0.7446808510638298, 'f1-score': 0.726643598615917, 'support': 141.0} | {'precision': 0.766042780748663, 'recall': 0.809322033898305, 'f1-score': 0.7870879120879121, 'support': 708.0} | {'precision': 0.5981858298602599, 'recall': 0.5984792739759627, 'f1-score': 0.5983325159391859, 'support': 4077.0} | {'precision': 0.7981220657276995, 'recall': 0.7559288537549407, 'f1-score': 0.7764526769855367, 'support': 2024.0} | {'precision': 0.8736565560066873, 'recall': 0.8971550032701112, 'f1-score': 0.885249868914613, 'support': 12232.0} | {'precision': 0.9181542958555173, 'recall': 0.8912646939602756, 'f1-score': 0.9045096930117758, 'support': 9868.0} | 0.8382 | {'precision': 0.7471208790316002, 'recall': 0.7569919122828231, 'f1-score': 0.751699144713602, 'support': 29334.0} | {'precision': 0.8387644471781172, 'recall': 0.8382082225403968, 'f1-score': 0.838292846606077, 'support': 29334.0} |
92
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+ ### Framework versions
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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