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Theoreticallyhugo
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longformer-spans

Token Classification
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longformer
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trainer: training complete at 2024-03-02 12:20:23.213790.

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  1. README.md +27 -27
  2. meta_data/README_s42_e16.md +27 -27
  3. meta_data/meta_s42_e16_cvi2.json +1 -1
  4. 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: spans
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- split: train[20%:40%]
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  args: spans
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9337012922629474
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  ---
27
 
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,13 +32,13 @@ 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: 0.2971
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- - B: {'precision': 0.8351477449455676, 'recall': 0.9117147707979627, 'f1-score': 0.8717532467532468, 'support': 1178.0}
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- - I: {'precision': 0.9428615911567804, 'recall': 0.9613207047991957, 'f1-score': 0.9520016767973171, 'support': 18899.0}
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- - O: {'precision': 0.9285714285714286, 'recall': 0.8849705304518664, 'f1-score': 0.9062468564530731, 'support': 10180.0}
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- - Accuracy: 0.9337
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- - Macro avg: {'precision': 0.9021935882245922, 'recall': 0.9193353353496749, 'f1-score': 0.9100005933345456, 'support': 30257.0}
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- - Weighted avg: {'precision': 0.9338600124822359, 'recall': 0.9337012922629474, 'f1-score': 0.9334830952559773, 'support': 30257.0}
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  ## Model description
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@@ -67,24 +67,24 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | B | I | O | Accuracy | Macro avg | Weighted avg |
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- |:-------------:|:-----:|:----:|:---------------:|:------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:--------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
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- | No log | 1.0 | 41 | 0.2806 | {'precision': 0.7871116225546605, 'recall': 0.5806451612903226, 'f1-score': 0.668295065950171, 'support': 1178.0} | {'precision': 0.9208257120459891, 'recall': 0.9323244616117254, 'f1-score': 0.9265394121049587, 'support': 18899.0} | {'precision': 0.8648200526675119, 'recall': 0.8710216110019646, 'f1-score': 0.8679097538295895, 'support': 10180.0} | 0.8980 | {'precision': 0.8575857957560539, 'recall': 0.7946637446346708, 'f1-score': 0.820914743961573, 'support': 30257.0} | {'precision': 0.8967766387772022, 'recall': 0.8980070727434973, 'f1-score': 0.896759137754772, 'support': 30257.0} |
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- | No log | 2.0 | 82 | 0.1942 | {'precision': 0.8446771378708552, 'recall': 0.8217317487266553, 'f1-score': 0.8330464716006883, 'support': 1178.0} | {'precision': 0.950406156477127, 'recall': 0.9410021694269538, 'f1-score': 0.9456807848767648, 'support': 18899.0} | {'precision': 0.8897009327819982, 'recall': 0.9088408644400786, 'f1-score': 0.8991690558336167, 'support': 10180.0} | 0.9255 | {'precision': 0.8949280757099934, 'recall': 0.8905249275312292, 'f1-score': 0.89263210410369, 'support': 30257.0} | {'precision': 0.9258654564363231, 'recall': 0.9255378920580362, 'f1-score': 0.925646656486691, 'support': 30257.0} |
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- | No log | 3.0 | 123 | 0.1832 | {'precision': 0.8074866310160428, 'recall': 0.8972835314091681, 'f1-score': 0.8500201045436268, 'support': 1178.0} | {'precision': 0.942701581540057, 'recall': 0.9619556590295782, 'f1-score': 0.9522313010685104, 'support': 18899.0} | {'precision': 0.9321121804822519, 'recall': 0.8847740667976425, 'f1-score': 0.907826437534647, 'support': 10180.0} | 0.9335 | {'precision': 0.894100131012784, 'recall': 0.9146710857454629, 'f1-score': 0.9033592810489282, 'support': 30257.0} | {'precision': 0.9338744237092824, 'recall': 0.9334699408401361, 'f1-score': 0.9333118344895024, 'support': 30257.0} |
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- | No log | 4.0 | 164 | 0.1747 | {'precision': 0.8522167487684729, 'recall': 0.8811544991511036, 'f1-score': 0.8664440734557596, 'support': 1178.0} | {'precision': 0.9485603194619588, 'recall': 0.9552357267580295, 'f1-score': 0.9518863198966544, 'support': 18899.0} | {'precision': 0.9159588288198262, 'recall': 0.9003929273084479, 'f1-score': 0.9081091791747165, 'support': 10180.0} | 0.9339 | {'precision': 0.905578632350086, 'recall': 0.912261051072527, 'f1-score': 0.9088131908423769, 'support': 30257.0} | {'precision': 0.9338405554069026, 'recall': 0.9338995934825, 'f1-score': 0.9338309192007261, 'support': 30257.0} |
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- | No log | 5.0 | 205 | 0.1861 | {'precision': 0.8224085365853658, 'recall': 0.9159592529711376, 'f1-score': 0.8666666666666667, 'support': 1178.0} | {'precision': 0.9393582120155833, 'recall': 0.9696280226467009, 'f1-score': 0.9542531309396725, 'support': 18899.0} | {'precision': 0.9446858111688037, 'recall': 0.8757367387033399, 'f1-score': 0.9089055411123006, 'support': 10180.0} | 0.9359 | {'precision': 0.9021508532565843, 'recall': 0.9204413381070594, 'f1-score': 0.9099417795728799, 'support': 30257.0} | {'precision': 0.9365974704259672, 'recall': 0.9359487060845424, 'f1-score': 0.9355858698312928, 'support': 30257.0} |
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- | No log | 6.0 | 246 | 0.1963 | {'precision': 0.8229740361919748, 'recall': 0.8879456706281834, 'f1-score': 0.8542262147815436, 'support': 1178.0} | {'precision': 0.962094547029837, 'recall': 0.9401026509339119, 'f1-score': 0.9509714713911042, 'support': 18899.0} | {'precision': 0.897328643407168, 'recall': 0.9272102161100196, 'f1-score': 0.9120247354944683, 'support': 10180.0} | 0.9337 | {'precision': 0.8941324088763266, 'recall': 0.9184195125573716, 'f1-score': 0.9057408072223719, 'support': 30257.0} | {'precision': 0.9348875912627161, 'recall': 0.9337343424662061, 'f1-score': 0.9341012038922174, 'support': 30257.0} |
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- | No log | 7.0 | 287 | 0.2315 | {'precision': 0.8133535660091047, 'recall': 0.9100169779286927, 'f1-score': 0.8589743589743589, 'support': 1178.0} | {'precision': 0.9424149252175725, 'recall': 0.9568760251865178, 'f1-score': 0.9495904221802143, 'support': 18899.0} | {'precision': 0.9218461538461539, 'recall': 0.8829076620825147, 'f1-score': 0.9019568489713999, 'support': 10180.0} | 0.9302 | {'precision': 0.8925382150242771, 'recall': 0.9166002217325749, 'f1-score': 0.9035072100419911, 'support': 30257.0} | {'precision': 0.9304697762038363, 'recall': 0.9301649205142611, 'f1-score': 0.9300360877213377, 'support': 30257.0} |
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- | No log | 8.0 | 328 | 0.2543 | {'precision': 0.833076923076923, 'recall': 0.9193548387096774, 'f1-score': 0.87409200968523, 'support': 1178.0} | {'precision': 0.9300999293428889, 'recall': 0.9751309593100164, 'f1-score': 0.952083279518508, 'support': 18899.0} | {'precision': 0.9527507382697146, 'recall': 0.8556974459724951, 'f1-score': 0.9016198312891373, 'support': 10180.0} | 0.9328 | {'precision': 0.9053091968965088, 'recall': 0.9167277479973963, 'f1-score': 0.9092650401642918, 'support': 30257.0} | {'precision': 0.9339434079922521, 'recall': 0.9327758865717024, 'f1-score': 0.932068353424097, 'support': 30257.0} |
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- | No log | 9.0 | 369 | 0.2367 | {'precision': 0.8409976617303195, 'recall': 0.9159592529711376, 'f1-score': 0.8768793173506705, 'support': 1178.0} | {'precision': 0.9428438661710037, 'recall': 0.9662416000846605, 'f1-score': 0.9543993519220215, 'support': 18899.0} | {'precision': 0.9379554445138455, 'recall': 0.8850687622789783, 'f1-score': 0.9107449711917517, 'support': 10180.0} | 0.9370 | {'precision': 0.9072656574717229, 'recall': 0.9224232051115923, 'f1-score': 0.9140078801548146, 'support': 30257.0} | {'precision': 0.9372339589990767, 'recall': 0.9369732623855637, 'f1-score': 0.9366936905359226, 'support': 30257.0} |
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- | No log | 10.0 | 410 | 0.2730 | {'precision': 0.8094170403587444, 'recall': 0.9193548387096774, 'f1-score': 0.8608903020667728, 'support': 1178.0} | {'precision': 0.9393060590367686, 'recall': 0.9597333192232393, 'f1-score': 0.9494098249103614, 'support': 18899.0} | {'precision': 0.9288167343115828, 'recall': 0.8767190569744597, 'f1-score': 0.9020162716660771, 'support': 10180.0} | 0.9302 | {'precision': 0.8925132779023652, 'recall': 0.9186024049691256, 'f1-score': 0.9041054662144038, 'support': 30257.0} | {'precision': 0.9307199272423042, 'recall': 0.9302310209207787, 'f1-score': 0.9300178703234373, 'support': 30257.0} |
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- | No log | 11.0 | 451 | 0.2785 | {'precision': 0.8337218337218337, 'recall': 0.9108658743633277, 'f1-score': 0.8705882352941178, 'support': 1178.0} | {'precision': 0.9392393320964749, 'recall': 0.9643367373935129, 'f1-score': 0.9516225883090098, 'support': 18899.0} | {'precision': 0.9336190675308383, 'recall': 0.8773084479371316, 'f1-score': 0.9045882710422363, 'support': 10180.0} | 0.9330 | {'precision': 0.9021934111163823, 'recall': 0.9175036865646574, 'f1-score': 0.9089330315484546, 'support': 30257.0} | {'precision': 0.9332402605968713, 'recall': 0.932974187791255, 'f1-score': 0.9326429202114688, 'support': 30257.0} |
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- | No log | 12.0 | 492 | 0.2703 | {'precision': 0.8390894819466248, 'recall': 0.9074702886247877, 'f1-score': 0.871941272430669, 'support': 1178.0} | {'precision': 0.9483742604324834, 'recall': 0.9584104979099424, 'f1-score': 0.9533659666298226, 'support': 18899.0} | {'precision': 0.924524484014569, 'recall': 0.8976424361493124, 'f1-score': 0.9108851674641149, 'support': 10180.0} | 0.9360 | {'precision': 0.903996075464559, 'recall': 0.9211744075613475, 'f1-score': 0.9120641355082021, 'support': 30257.0} | {'precision': 0.9360951781377842, 'recall': 0.9359817562878012, 'f1-score': 0.9359031373581331, 'support': 30257.0} |
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- | 0.1317 | 13.0 | 533 | 0.2982 | {'precision': 0.8402832415420929, 'recall': 0.9066213921901528, 'f1-score': 0.8721927317272357, 'support': 1178.0} | {'precision': 0.9399876263147041, 'recall': 0.9647071273612361, 'f1-score': 0.952186969578274, 'support': 18899.0} | {'precision': 0.9331595411887382, 'recall': 0.8790766208251474, 'f1-score': 0.9053110773899848, 'support': 10180.0} | 0.9336 | {'precision': 0.9044768030151783, 'recall': 0.9168017134588454, 'f1-score': 0.9098969262318315, 'support': 30257.0} | {'precision': 0.9338085050586488, 'recall': 0.93363519185643, 'f1-score': 0.9333010987164798, 'support': 30257.0} |
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- | 0.1317 | 14.0 | 574 | 0.3190 | {'precision': 0.827559661277906, 'recall': 0.9125636672325976, 'f1-score': 0.8679854662898667, 'support': 1178.0} | {'precision': 0.938201668554949, 'recall': 0.9639663474257897, 'f1-score': 0.9509095179685257, 'support': 18899.0} | {'precision': 0.9335429769392034, 'recall': 0.8748526522593321, 'f1-score': 0.9032454361054767, 'support': 10180.0} | 0.9320 | {'precision': 0.8997681022573528, 'recall': 0.9171275556392398, 'f1-score': 0.9073801401212896, 'support': 30257.0} | {'precision': 0.9323266060827724, 'recall': 0.9319826816934924, 'f1-score': 0.9316443929976661, 'support': 30257.0} |
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- | 0.1317 | 15.0 | 615 | 0.3058 | {'precision': 0.8361934477379095, 'recall': 0.9100169779286927, 'f1-score': 0.8715447154471545, 'support': 1178.0} | {'precision': 0.9371953409615681, 'recall': 0.9664532514947881, 'f1-score': 0.9515994581640096, 'support': 18899.0} | {'precision': 0.9362218005481763, 'recall': 0.8723968565815324, 'f1-score': 0.9031831587511441, 'support': 10180.0} | 0.9326 | {'precision': 0.9032035297492179, 'recall': 0.9162890286683378, 'f1-score': 0.9087757774541028, 'support': 30257.0} | {'precision': 0.932935471456138, 'recall': 0.9326106355554087, 'f1-score': 0.9321929600001657, 'support': 30257.0} |
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- | 0.1317 | 16.0 | 656 | 0.2971 | {'precision': 0.8351477449455676, 'recall': 0.9117147707979627, 'f1-score': 0.8717532467532468, 'support': 1178.0} | {'precision': 0.9428615911567804, 'recall': 0.9613207047991957, 'f1-score': 0.9520016767973171, 'support': 18899.0} | {'precision': 0.9285714285714286, 'recall': 0.8849705304518664, 'f1-score': 0.9062468564530731, 'support': 10180.0} | 0.9337 | {'precision': 0.9021935882245922, 'recall': 0.9193353353496749, 'f1-score': 0.9100005933345456, 'support': 30257.0} | {'precision': 0.9338600124822359, 'recall': 0.9337012922629474, 'f1-score': 0.9334830952559773, 'support': 30257.0} |
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  ### Framework versions
 
17
  name: essays_su_g
18
  type: essays_su_g
19
  config: spans
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+ split: train[40%:60%]
21
  args: spans
22
  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9435675748131765
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.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3010
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+ - B: {'precision': 0.8761061946902655, 'recall': 0.9173745173745174, 'f1-score': 0.8962655601659751, 'support': 1295.0}
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+ - I: {'precision': 0.9587562509283557, 'recall': 0.9650635434836781, 'f1-score': 0.9618995578957825, 'support': 20065.0}
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+ - O: {'precision': 0.9175916988416989, 'recall': 0.8967102935974531, 'f1-score': 0.907030830699505, 'support': 8481.0}
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+ - Accuracy: 0.9436
40
+ - Macro avg: {'precision': 0.9174847148201067, 'recall': 0.9263827848185495, 'f1-score': 0.9217319829204209, 'support': 29841.0}
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+ - Weighted avg: {'precision': 0.943470289027774, 'recall': 0.9435675748131765, 'f1-score': 0.9434572234427906, 'support': 29841.0}
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43
  ## Model description
44
 
 
67
 
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | B | I | O | Accuracy | Macro avg | Weighted avg |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:--------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
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+ | No log | 1.0 | 41 | 0.3153 | {'precision': 0.8472222222222222, 'recall': 0.47104247104247104, 'f1-score': 0.6054590570719602, 'support': 1295.0} | {'precision': 0.8894522863277146, 'recall': 0.9703962123099925, 'f1-score': 0.9281628372580799, 'support': 20065.0} | {'precision': 0.8983402489626556, 'recall': 0.7658295012380616, 'f1-score': 0.826809241932404, 'support': 8481.0} | 0.8906 | {'precision': 0.8783382525041974, 'recall': 0.735756061530175, 'f1-score': 0.786810378754148, 'support': 29841.0} | {'precision': 0.8901456571293072, 'recall': 0.8905867765825543, 'f1-score': 0.8853532384745914, 'support': 29841.0} |
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+ | No log | 2.0 | 82 | 0.2253 | {'precision': 0.7966329966329966, 'recall': 0.9135135135135135, 'f1-score': 0.8510791366906474, 'support': 1295.0} | {'precision': 0.9247806497510078, 'recall': 0.9717916770495888, 'f1-score': 0.9477035236938031, 'support': 20065.0} | {'precision': 0.9339843212763032, 'recall': 0.8007310458672326, 'f1-score': 0.8622397155916709, 'support': 8481.0} | 0.9206 | {'precision': 0.8851326558867693, 'recall': 0.895345412143445, 'f1-score': 0.8870074586587071, 'support': 29841.0} | {'precision': 0.9218352098333846, 'recall': 0.9206460909486948, 'f1-score': 0.9192209950358067, 'support': 29841.0} |
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+ | No log | 3.0 | 123 | 0.1809 | {'precision': 0.8226027397260274, 'recall': 0.9274131274131274, 'f1-score': 0.8718693284936478, 'support': 1295.0} | {'precision': 0.9520828198175992, 'recall': 0.9625218041365562, 'f1-score': 0.95727385377943, 'support': 20065.0} | {'precision': 0.91600790513834, 'recall': 0.8744251857092324, 'f1-score': 0.8947336671291549, 'support': 8481.0} | 0.9360 | {'precision': 0.8968978215606556, 'recall': 0.9214533724196388, 'f1-score': 0.9079589498007442, 'support': 29841.0} | {'precision': 0.9362110978540797, 'recall': 0.9359605911330049, 'f1-score': 0.9357932672298482, 'support': 29841.0} |
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+ | No log | 4.0 | 164 | 0.1962 | {'precision': 0.8513513513513513, 'recall': 0.9243243243243243, 'f1-score': 0.8863383931877082, 'support': 1295.0} | {'precision': 0.942660770931462, 'recall': 0.9774732120608024, 'f1-score': 0.9597514129823103, 'support': 20065.0} | {'precision': 0.9454712282081531, 'recall': 0.8504893290885509, 'f1-score': 0.8954686530105526, 'support': 8481.0} | 0.9391 | {'precision': 0.9131611168303221, 'recall': 0.9174289551578925, 'f1-score': 0.913852819726857, 'support': 29841.0} | {'precision': 0.9394969959174669, 'recall': 0.9390771086759827, 'f1-score': 0.9382959675228925, 'support': 29841.0} |
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+ | No log | 5.0 | 205 | 0.1936 | {'precision': 0.8609467455621301, 'recall': 0.8988416988416988, 'f1-score': 0.8794862108046846, 'support': 1295.0} | {'precision': 0.9656717938270347, 'recall': 0.9449289808123599, 'f1-score': 0.955187788105494, 'support': 20065.0} | {'precision': 0.8764539808018069, 'recall': 0.9151043509020163, 'f1-score': 0.8953622519612366, 'support': 8481.0} | 0.9345 | {'precision': 0.9010241733969906, 'recall': 0.9196250101853582, 'f1-score': 0.9100120836238051, 'support': 29841.0} | {'precision': 0.9357708116290517, 'recall': 0.9344525987734995, 'f1-score': 0.9348997979361299, 'support': 29841.0} |
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+ | No log | 6.0 | 246 | 0.1947 | {'precision': 0.8310533515731874, 'recall': 0.9382239382239382, 'f1-score': 0.8813928182807399, 'support': 1295.0} | {'precision': 0.958739197762126, 'recall': 0.9565412409668577, 'f1-score': 0.9576389581878055, 'support': 20065.0} | {'precision': 0.9059808612440191, 'recall': 0.8930550642612899, 'f1-score': 0.8994715278190131, 'support': 8481.0} | 0.9377 | {'precision': 0.8985911368597775, 'recall': 0.9292734144840287, 'f1-score': 0.9128344347625195, 'support': 29841.0} | {'precision': 0.9382038060921168, 'recall': 0.9377031600817667, 'f1-score': 0.9377985799116962, 'support': 29841.0} |
78
+ | No log | 7.0 | 287 | 0.2014 | {'precision': 0.8799403430275914, 'recall': 0.9111969111969112, 'f1-score': 0.8952959028831563, 'support': 1295.0} | {'precision': 0.9675979919882359, 'recall': 0.9510092200348866, 'f1-score': 0.9592318906147891, 'support': 20065.0} | {'precision': 0.8888256065611118, 'recall': 0.9200565970993987, 'f1-score': 0.9041714947856316, 'support': 8481.0} | 0.9405 | {'precision': 0.9121213138589797, 'recall': 0.9274209094437321, 'f1-score': 0.919566429427859, 'support': 29841.0} | {'precision': 0.9414063343289258, 'recall': 0.940484568211521, 'f1-score': 0.9408087707079646, 'support': 29841.0} |
79
+ | No log | 8.0 | 328 | 0.2169 | {'precision': 0.8607322325915291, 'recall': 0.9258687258687258, 'f1-score': 0.8921130952380952, 'support': 1295.0} | {'precision': 0.9490554125588849, 'recall': 0.9739347121853975, 'f1-score': 0.9613341204250295, 'support': 20065.0} | {'precision': 0.9371261295659921, 'recall': 0.8681759226506308, 'f1-score': 0.9013343126453666, 'support': 8481.0} | 0.9418 | {'precision': 0.9156379249054686, 'recall': 0.9226597869015847, 'f1-score': 0.9182605094361639, 'support': 29841.0} | {'precision': 0.9418321034499257, 'recall': 0.9417914949230924, 'f1-score': 0.9412778355352336, 'support': 29841.0} |
80
+ | No log | 9.0 | 369 | 0.2356 | {'precision': 0.8841554559043349, 'recall': 0.9135135135135135, 'f1-score': 0.8985947588302315, 'support': 1295.0} | {'precision': 0.958962427602594, 'recall': 0.9654622476949912, 'f1-score': 0.9622013609496847, 'support': 20065.0} | {'precision': 0.9177306673090821, 'recall': 0.8983610423299139, 'f1-score': 0.9079425609247452, 'support': 8481.0} | 0.9441 | {'precision': 0.9202828502720036, 'recall': 0.9257789345128061, 'f1-score': 0.9229128935682205, 'support': 29841.0} | {'precision': 0.9439977284504704, 'recall': 0.9441372608156563, 'f1-score': 0.944020353853535, 'support': 29841.0} |
81
+ | No log | 10.0 | 410 | 0.2491 | {'precision': 0.846045197740113, 'recall': 0.9250965250965251, 'f1-score': 0.883806713389893, 'support': 1295.0} | {'precision': 0.9549009000147544, 'recall': 0.9676551208572141, 'f1-score': 0.9612357047378584, 'support': 20065.0} | {'precision': 0.9259762728620861, 'recall': 0.8835043037377668, 'f1-score': 0.904241839135944, 'support': 8481.0} | 0.9419 | {'precision': 0.9089741235389845, 'recall': 0.9254186498971686, 'f1-score': 0.9164280857545651, 'support': 29841.0} | {'precision': 0.941956364063297, 'recall': 0.9418920277470594, 'f1-score': 0.9416775291416837, 'support': 29841.0} |
82
+ | No log | 11.0 | 451 | 0.2823 | {'precision': 0.8699127906976745, 'recall': 0.9243243243243243, 'f1-score': 0.8962935230250841, 'support': 1295.0} | {'precision': 0.9454922579711543, 'recall': 0.9768751557438325, 'f1-score': 0.9609275419158742, 'support': 20065.0} | {'precision': 0.9427204551331781, 'recall': 0.8596863577408325, 'f1-score': 0.8992907801418439, 'support': 8481.0} | 0.9413 | {'precision': 0.9193751679340023, 'recall': 0.9202952792696631, 'f1-score': 0.9188372816942675, 'support': 29841.0} | {'precision': 0.9414245970352596, 'recall': 0.9412888308032573, 'f1-score': 0.9406050851929385, 'support': 29841.0} |
83
+ | No log | 12.0 | 492 | 0.2666 | {'precision': 0.8749080206033848, 'recall': 0.9181467181467181, 'f1-score': 0.896006028636021, 'support': 1295.0} | {'precision': 0.9618267212950934, 'recall': 0.9593820084724645, 'f1-score': 0.9606028094513335, 'support': 20065.0} | {'precision': 0.9059990552668871, 'recall': 0.9046103053885155, 'f1-score': 0.9053041477373296, 'support': 8481.0} | 0.9420 | {'precision': 0.9142445990551217, 'recall': 0.9273796773358992, 'f1-score': 0.9206376619415613, 'support': 29841.0} | {'precision': 0.9421881651816595, 'recall': 0.9420260715123487, 'f1-score': 0.9420832966618057, 'support': 29841.0} |
84
+ | 0.1288 | 13.0 | 533 | 0.2789 | {'precision': 0.8708971553610503, 'recall': 0.922007722007722, 'f1-score': 0.8957239309827456, 'support': 1295.0} | {'precision': 0.960913024019096, 'recall': 0.9630201844006977, 'f1-score': 0.961965450291233, 'support': 20065.0} | {'precision': 0.9144839134074871, 'recall': 0.9015446291710884, 'f1-score': 0.9079681748010924, 'support': 8481.0} | 0.9438 | {'precision': 0.9154313642625445, 'recall': 0.928857511859836, 'f1-score': 0.9218858520250238, 'support': 29841.0} | {'precision': 0.9438111897303917, 'recall': 0.9437686404611105, 'f1-score': 0.9437444234846122, 'support': 29841.0} |
85
+ | 0.1288 | 14.0 | 574 | 0.2878 | {'precision': 0.8693759071117562, 'recall': 0.9250965250965251, 'f1-score': 0.8963711185933408, 'support': 1295.0} | {'precision': 0.9577367433593365, 'recall': 0.9667580363817593, 'f1-score': 0.9622262456906173, 'support': 20065.0} | {'precision': 0.9222804239249605, 'recall': 0.8927013323900483, 'f1-score': 0.9072498502097065, 'support': 8481.0} | 0.9439 | {'precision': 0.9164643581320178, 'recall': 0.9281852979561108, 'f1-score': 0.9219490714978882, 'support': 29841.0} | {'precision': 0.9438252682725914, 'recall': 0.9439026842263999, 'f1-score': 0.943743714955569, 'support': 29841.0} |
86
+ | 0.1288 | 15.0 | 615 | 0.3028 | {'precision': 0.8794642857142857, 'recall': 0.9127413127413128, 'f1-score': 0.8957938613111027, 'support': 1295.0} | {'precision': 0.9580749193748449, 'recall': 0.9623722900573137, 'f1-score': 0.9602187966185977, 'support': 20065.0} | {'precision': 0.9105730040757612, 'recall': 0.8956490979837284, 'f1-score': 0.9030493966593355, 'support': 8481.0} | 0.9413 | {'precision': 0.916037403054964, 'recall': 0.9235875669274516, 'f1-score': 0.9196873515296785, 'support': 29841.0} | {'precision': 0.9411631364506148, 'recall': 0.9412553198619349, 'f1-score': 0.941175065769172, 'support': 29841.0} |
87
+ | 0.1288 | 16.0 | 656 | 0.3010 | {'precision': 0.8761061946902655, 'recall': 0.9173745173745174, 'f1-score': 0.8962655601659751, 'support': 1295.0} | {'precision': 0.9587562509283557, 'recall': 0.9650635434836781, 'f1-score': 0.9618995578957825, 'support': 20065.0} | {'precision': 0.9175916988416989, 'recall': 0.8967102935974531, 'f1-score': 0.907030830699505, 'support': 8481.0} | 0.9436 | {'precision': 0.9174847148201067, 'recall': 0.9263827848185495, 'f1-score': 0.9217319829204209, 'support': 29841.0} | {'precision': 0.943470289027774, 'recall': 0.9435675748131765, 'f1-score': 0.9434572234427906, 'support': 29841.0} |
88
 
89
 
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  ### Framework versions
meta_data/README_s42_e16.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: spans
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- split: train[20%:40%]
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  args: spans
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9337012922629474
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  ---
27
 
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,13 +32,13 @@ should probably proofread and complete it, then remove this comment. -->
32
 
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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:
35
- - Loss: 0.2971
36
- - B: {'precision': 0.8351477449455676, 'recall': 0.9117147707979627, 'f1-score': 0.8717532467532468, 'support': 1178.0}
37
- - I: {'precision': 0.9428615911567804, 'recall': 0.9613207047991957, 'f1-score': 0.9520016767973171, 'support': 18899.0}
38
- - O: {'precision': 0.9285714285714286, 'recall': 0.8849705304518664, 'f1-score': 0.9062468564530731, 'support': 10180.0}
39
- - Accuracy: 0.9337
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- - Macro avg: {'precision': 0.9021935882245922, 'recall': 0.9193353353496749, 'f1-score': 0.9100005933345456, 'support': 30257.0}
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- - Weighted avg: {'precision': 0.9338600124822359, 'recall': 0.9337012922629474, 'f1-score': 0.9334830952559773, 'support': 30257.0}
42
 
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  ## Model description
44
 
@@ -67,24 +67,24 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | B | I | O | Accuracy | Macro avg | Weighted avg |
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- |:-------------:|:-----:|:----:|:---------------:|:------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:--------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
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- | No log | 1.0 | 41 | 0.2806 | {'precision': 0.7871116225546605, 'recall': 0.5806451612903226, 'f1-score': 0.668295065950171, 'support': 1178.0} | {'precision': 0.9208257120459891, 'recall': 0.9323244616117254, 'f1-score': 0.9265394121049587, 'support': 18899.0} | {'precision': 0.8648200526675119, 'recall': 0.8710216110019646, 'f1-score': 0.8679097538295895, 'support': 10180.0} | 0.8980 | {'precision': 0.8575857957560539, 'recall': 0.7946637446346708, 'f1-score': 0.820914743961573, 'support': 30257.0} | {'precision': 0.8967766387772022, 'recall': 0.8980070727434973, 'f1-score': 0.896759137754772, 'support': 30257.0} |
73
- | No log | 2.0 | 82 | 0.1942 | {'precision': 0.8446771378708552, 'recall': 0.8217317487266553, 'f1-score': 0.8330464716006883, 'support': 1178.0} | {'precision': 0.950406156477127, 'recall': 0.9410021694269538, 'f1-score': 0.9456807848767648, 'support': 18899.0} | {'precision': 0.8897009327819982, 'recall': 0.9088408644400786, 'f1-score': 0.8991690558336167, 'support': 10180.0} | 0.9255 | {'precision': 0.8949280757099934, 'recall': 0.8905249275312292, 'f1-score': 0.89263210410369, 'support': 30257.0} | {'precision': 0.9258654564363231, 'recall': 0.9255378920580362, 'f1-score': 0.925646656486691, 'support': 30257.0} |
74
- | No log | 3.0 | 123 | 0.1832 | {'precision': 0.8074866310160428, 'recall': 0.8972835314091681, 'f1-score': 0.8500201045436268, 'support': 1178.0} | {'precision': 0.942701581540057, 'recall': 0.9619556590295782, 'f1-score': 0.9522313010685104, 'support': 18899.0} | {'precision': 0.9321121804822519, 'recall': 0.8847740667976425, 'f1-score': 0.907826437534647, 'support': 10180.0} | 0.9335 | {'precision': 0.894100131012784, 'recall': 0.9146710857454629, 'f1-score': 0.9033592810489282, 'support': 30257.0} | {'precision': 0.9338744237092824, 'recall': 0.9334699408401361, 'f1-score': 0.9333118344895024, 'support': 30257.0} |
75
- | No log | 4.0 | 164 | 0.1747 | {'precision': 0.8522167487684729, 'recall': 0.8811544991511036, 'f1-score': 0.8664440734557596, 'support': 1178.0} | {'precision': 0.9485603194619588, 'recall': 0.9552357267580295, 'f1-score': 0.9518863198966544, 'support': 18899.0} | {'precision': 0.9159588288198262, 'recall': 0.9003929273084479, 'f1-score': 0.9081091791747165, 'support': 10180.0} | 0.9339 | {'precision': 0.905578632350086, 'recall': 0.912261051072527, 'f1-score': 0.9088131908423769, 'support': 30257.0} | {'precision': 0.9338405554069026, 'recall': 0.9338995934825, 'f1-score': 0.9338309192007261, 'support': 30257.0} |
76
- | No log | 5.0 | 205 | 0.1861 | {'precision': 0.8224085365853658, 'recall': 0.9159592529711376, 'f1-score': 0.8666666666666667, 'support': 1178.0} | {'precision': 0.9393582120155833, 'recall': 0.9696280226467009, 'f1-score': 0.9542531309396725, 'support': 18899.0} | {'precision': 0.9446858111688037, 'recall': 0.8757367387033399, 'f1-score': 0.9089055411123006, 'support': 10180.0} | 0.9359 | {'precision': 0.9021508532565843, 'recall': 0.9204413381070594, 'f1-score': 0.9099417795728799, 'support': 30257.0} | {'precision': 0.9365974704259672, 'recall': 0.9359487060845424, 'f1-score': 0.9355858698312928, 'support': 30257.0} |
77
- | No log | 6.0 | 246 | 0.1963 | {'precision': 0.8229740361919748, 'recall': 0.8879456706281834, 'f1-score': 0.8542262147815436, 'support': 1178.0} | {'precision': 0.962094547029837, 'recall': 0.9401026509339119, 'f1-score': 0.9509714713911042, 'support': 18899.0} | {'precision': 0.897328643407168, 'recall': 0.9272102161100196, 'f1-score': 0.9120247354944683, 'support': 10180.0} | 0.9337 | {'precision': 0.8941324088763266, 'recall': 0.9184195125573716, 'f1-score': 0.9057408072223719, 'support': 30257.0} | {'precision': 0.9348875912627161, 'recall': 0.9337343424662061, 'f1-score': 0.9341012038922174, 'support': 30257.0} |
78
- | No log | 7.0 | 287 | 0.2315 | {'precision': 0.8133535660091047, 'recall': 0.9100169779286927, 'f1-score': 0.8589743589743589, 'support': 1178.0} | {'precision': 0.9424149252175725, 'recall': 0.9568760251865178, 'f1-score': 0.9495904221802143, 'support': 18899.0} | {'precision': 0.9218461538461539, 'recall': 0.8829076620825147, 'f1-score': 0.9019568489713999, 'support': 10180.0} | 0.9302 | {'precision': 0.8925382150242771, 'recall': 0.9166002217325749, 'f1-score': 0.9035072100419911, 'support': 30257.0} | {'precision': 0.9304697762038363, 'recall': 0.9301649205142611, 'f1-score': 0.9300360877213377, 'support': 30257.0} |
79
- | No log | 8.0 | 328 | 0.2543 | {'precision': 0.833076923076923, 'recall': 0.9193548387096774, 'f1-score': 0.87409200968523, 'support': 1178.0} | {'precision': 0.9300999293428889, 'recall': 0.9751309593100164, 'f1-score': 0.952083279518508, 'support': 18899.0} | {'precision': 0.9527507382697146, 'recall': 0.8556974459724951, 'f1-score': 0.9016198312891373, 'support': 10180.0} | 0.9328 | {'precision': 0.9053091968965088, 'recall': 0.9167277479973963, 'f1-score': 0.9092650401642918, 'support': 30257.0} | {'precision': 0.9339434079922521, 'recall': 0.9327758865717024, 'f1-score': 0.932068353424097, 'support': 30257.0} |
80
- | No log | 9.0 | 369 | 0.2367 | {'precision': 0.8409976617303195, 'recall': 0.9159592529711376, 'f1-score': 0.8768793173506705, 'support': 1178.0} | {'precision': 0.9428438661710037, 'recall': 0.9662416000846605, 'f1-score': 0.9543993519220215, 'support': 18899.0} | {'precision': 0.9379554445138455, 'recall': 0.8850687622789783, 'f1-score': 0.9107449711917517, 'support': 10180.0} | 0.9370 | {'precision': 0.9072656574717229, 'recall': 0.9224232051115923, 'f1-score': 0.9140078801548146, 'support': 30257.0} | {'precision': 0.9372339589990767, 'recall': 0.9369732623855637, 'f1-score': 0.9366936905359226, 'support': 30257.0} |
81
- | No log | 10.0 | 410 | 0.2730 | {'precision': 0.8094170403587444, 'recall': 0.9193548387096774, 'f1-score': 0.8608903020667728, 'support': 1178.0} | {'precision': 0.9393060590367686, 'recall': 0.9597333192232393, 'f1-score': 0.9494098249103614, 'support': 18899.0} | {'precision': 0.9288167343115828, 'recall': 0.8767190569744597, 'f1-score': 0.9020162716660771, 'support': 10180.0} | 0.9302 | {'precision': 0.8925132779023652, 'recall': 0.9186024049691256, 'f1-score': 0.9041054662144038, 'support': 30257.0} | {'precision': 0.9307199272423042, 'recall': 0.9302310209207787, 'f1-score': 0.9300178703234373, 'support': 30257.0} |
82
- | No log | 11.0 | 451 | 0.2785 | {'precision': 0.8337218337218337, 'recall': 0.9108658743633277, 'f1-score': 0.8705882352941178, 'support': 1178.0} | {'precision': 0.9392393320964749, 'recall': 0.9643367373935129, 'f1-score': 0.9516225883090098, 'support': 18899.0} | {'precision': 0.9336190675308383, 'recall': 0.8773084479371316, 'f1-score': 0.9045882710422363, 'support': 10180.0} | 0.9330 | {'precision': 0.9021934111163823, 'recall': 0.9175036865646574, 'f1-score': 0.9089330315484546, 'support': 30257.0} | {'precision': 0.9332402605968713, 'recall': 0.932974187791255, 'f1-score': 0.9326429202114688, 'support': 30257.0} |
83
- | No log | 12.0 | 492 | 0.2703 | {'precision': 0.8390894819466248, 'recall': 0.9074702886247877, 'f1-score': 0.871941272430669, 'support': 1178.0} | {'precision': 0.9483742604324834, 'recall': 0.9584104979099424, 'f1-score': 0.9533659666298226, 'support': 18899.0} | {'precision': 0.924524484014569, 'recall': 0.8976424361493124, 'f1-score': 0.9108851674641149, 'support': 10180.0} | 0.9360 | {'precision': 0.903996075464559, 'recall': 0.9211744075613475, 'f1-score': 0.9120641355082021, 'support': 30257.0} | {'precision': 0.9360951781377842, 'recall': 0.9359817562878012, 'f1-score': 0.9359031373581331, 'support': 30257.0} |
84
- | 0.1317 | 13.0 | 533 | 0.2982 | {'precision': 0.8402832415420929, 'recall': 0.9066213921901528, 'f1-score': 0.8721927317272357, 'support': 1178.0} | {'precision': 0.9399876263147041, 'recall': 0.9647071273612361, 'f1-score': 0.952186969578274, 'support': 18899.0} | {'precision': 0.9331595411887382, 'recall': 0.8790766208251474, 'f1-score': 0.9053110773899848, 'support': 10180.0} | 0.9336 | {'precision': 0.9044768030151783, 'recall': 0.9168017134588454, 'f1-score': 0.9098969262318315, 'support': 30257.0} | {'precision': 0.9338085050586488, 'recall': 0.93363519185643, 'f1-score': 0.9333010987164798, 'support': 30257.0} |
85
- | 0.1317 | 14.0 | 574 | 0.3190 | {'precision': 0.827559661277906, 'recall': 0.9125636672325976, 'f1-score': 0.8679854662898667, 'support': 1178.0} | {'precision': 0.938201668554949, 'recall': 0.9639663474257897, 'f1-score': 0.9509095179685257, 'support': 18899.0} | {'precision': 0.9335429769392034, 'recall': 0.8748526522593321, 'f1-score': 0.9032454361054767, 'support': 10180.0} | 0.9320 | {'precision': 0.8997681022573528, 'recall': 0.9171275556392398, 'f1-score': 0.9073801401212896, 'support': 30257.0} | {'precision': 0.9323266060827724, 'recall': 0.9319826816934924, 'f1-score': 0.9316443929976661, 'support': 30257.0} |
86
- | 0.1317 | 15.0 | 615 | 0.3058 | {'precision': 0.8361934477379095, 'recall': 0.9100169779286927, 'f1-score': 0.8715447154471545, 'support': 1178.0} | {'precision': 0.9371953409615681, 'recall': 0.9664532514947881, 'f1-score': 0.9515994581640096, 'support': 18899.0} | {'precision': 0.9362218005481763, 'recall': 0.8723968565815324, 'f1-score': 0.9031831587511441, 'support': 10180.0} | 0.9326 | {'precision': 0.9032035297492179, 'recall': 0.9162890286683378, 'f1-score': 0.9087757774541028, 'support': 30257.0} | {'precision': 0.932935471456138, 'recall': 0.9326106355554087, 'f1-score': 0.9321929600001657, 'support': 30257.0} |
87
- | 0.1317 | 16.0 | 656 | 0.2971 | {'precision': 0.8351477449455676, 'recall': 0.9117147707979627, 'f1-score': 0.8717532467532468, 'support': 1178.0} | {'precision': 0.9428615911567804, 'recall': 0.9613207047991957, 'f1-score': 0.9520016767973171, 'support': 18899.0} | {'precision': 0.9285714285714286, 'recall': 0.8849705304518664, 'f1-score': 0.9062468564530731, 'support': 10180.0} | 0.9337 | {'precision': 0.9021935882245922, 'recall': 0.9193353353496749, 'f1-score': 0.9100005933345456, 'support': 30257.0} | {'precision': 0.9338600124822359, 'recall': 0.9337012922629474, 'f1-score': 0.9334830952559773, 'support': 30257.0} |
88
 
89
 
90
  ### Framework versions
 
17
  name: essays_su_g
18
  type: essays_su_g
19
  config: spans
20
+ split: train[40%:60%]
21
  args: spans
22
  metrics:
23
  - name: Accuracy
24
  type: accuracy
25
+ value: 0.9435675748131765
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: 0.3010
36
+ - B: {'precision': 0.8761061946902655, 'recall': 0.9173745173745174, 'f1-score': 0.8962655601659751, 'support': 1295.0}
37
+ - I: {'precision': 0.9587562509283557, 'recall': 0.9650635434836781, 'f1-score': 0.9618995578957825, 'support': 20065.0}
38
+ - O: {'precision': 0.9175916988416989, 'recall': 0.8967102935974531, 'f1-score': 0.907030830699505, 'support': 8481.0}
39
+ - Accuracy: 0.9436
40
+ - Macro avg: {'precision': 0.9174847148201067, 'recall': 0.9263827848185495, 'f1-score': 0.9217319829204209, 'support': 29841.0}
41
+ - Weighted avg: {'precision': 0.943470289027774, 'recall': 0.9435675748131765, 'f1-score': 0.9434572234427906, 'support': 29841.0}
42
 
43
  ## Model description
44
 
 
67
 
68
  ### Training results
69
 
70
+ | Training Loss | Epoch | Step | Validation Loss | B | I | O | Accuracy | Macro avg | Weighted avg |
71
+ |:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:--------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
72
+ | No log | 1.0 | 41 | 0.3153 | {'precision': 0.8472222222222222, 'recall': 0.47104247104247104, 'f1-score': 0.6054590570719602, 'support': 1295.0} | {'precision': 0.8894522863277146, 'recall': 0.9703962123099925, 'f1-score': 0.9281628372580799, 'support': 20065.0} | {'precision': 0.8983402489626556, 'recall': 0.7658295012380616, 'f1-score': 0.826809241932404, 'support': 8481.0} | 0.8906 | {'precision': 0.8783382525041974, 'recall': 0.735756061530175, 'f1-score': 0.786810378754148, 'support': 29841.0} | {'precision': 0.8901456571293072, 'recall': 0.8905867765825543, 'f1-score': 0.8853532384745914, 'support': 29841.0} |
73
+ | No log | 2.0 | 82 | 0.2253 | {'precision': 0.7966329966329966, 'recall': 0.9135135135135135, 'f1-score': 0.8510791366906474, 'support': 1295.0} | {'precision': 0.9247806497510078, 'recall': 0.9717916770495888, 'f1-score': 0.9477035236938031, 'support': 20065.0} | {'precision': 0.9339843212763032, 'recall': 0.8007310458672326, 'f1-score': 0.8622397155916709, 'support': 8481.0} | 0.9206 | {'precision': 0.8851326558867693, 'recall': 0.895345412143445, 'f1-score': 0.8870074586587071, 'support': 29841.0} | {'precision': 0.9218352098333846, 'recall': 0.9206460909486948, 'f1-score': 0.9192209950358067, 'support': 29841.0} |
74
+ | No log | 3.0 | 123 | 0.1809 | {'precision': 0.8226027397260274, 'recall': 0.9274131274131274, 'f1-score': 0.8718693284936478, 'support': 1295.0} | {'precision': 0.9520828198175992, 'recall': 0.9625218041365562, 'f1-score': 0.95727385377943, 'support': 20065.0} | {'precision': 0.91600790513834, 'recall': 0.8744251857092324, 'f1-score': 0.8947336671291549, 'support': 8481.0} | 0.9360 | {'precision': 0.8968978215606556, 'recall': 0.9214533724196388, 'f1-score': 0.9079589498007442, 'support': 29841.0} | {'precision': 0.9362110978540797, 'recall': 0.9359605911330049, 'f1-score': 0.9357932672298482, 'support': 29841.0} |
75
+ | No log | 4.0 | 164 | 0.1962 | {'precision': 0.8513513513513513, 'recall': 0.9243243243243243, 'f1-score': 0.8863383931877082, 'support': 1295.0} | {'precision': 0.942660770931462, 'recall': 0.9774732120608024, 'f1-score': 0.9597514129823103, 'support': 20065.0} | {'precision': 0.9454712282081531, 'recall': 0.8504893290885509, 'f1-score': 0.8954686530105526, 'support': 8481.0} | 0.9391 | {'precision': 0.9131611168303221, 'recall': 0.9174289551578925, 'f1-score': 0.913852819726857, 'support': 29841.0} | {'precision': 0.9394969959174669, 'recall': 0.9390771086759827, 'f1-score': 0.9382959675228925, 'support': 29841.0} |
76
+ | No log | 5.0 | 205 | 0.1936 | {'precision': 0.8609467455621301, 'recall': 0.8988416988416988, 'f1-score': 0.8794862108046846, 'support': 1295.0} | {'precision': 0.9656717938270347, 'recall': 0.9449289808123599, 'f1-score': 0.955187788105494, 'support': 20065.0} | {'precision': 0.8764539808018069, 'recall': 0.9151043509020163, 'f1-score': 0.8953622519612366, 'support': 8481.0} | 0.9345 | {'precision': 0.9010241733969906, 'recall': 0.9196250101853582, 'f1-score': 0.9100120836238051, 'support': 29841.0} | {'precision': 0.9357708116290517, 'recall': 0.9344525987734995, 'f1-score': 0.9348997979361299, 'support': 29841.0} |
77
+ | No log | 6.0 | 246 | 0.1947 | {'precision': 0.8310533515731874, 'recall': 0.9382239382239382, 'f1-score': 0.8813928182807399, 'support': 1295.0} | {'precision': 0.958739197762126, 'recall': 0.9565412409668577, 'f1-score': 0.9576389581878055, 'support': 20065.0} | {'precision': 0.9059808612440191, 'recall': 0.8930550642612899, 'f1-score': 0.8994715278190131, 'support': 8481.0} | 0.9377 | {'precision': 0.8985911368597775, 'recall': 0.9292734144840287, 'f1-score': 0.9128344347625195, 'support': 29841.0} | {'precision': 0.9382038060921168, 'recall': 0.9377031600817667, 'f1-score': 0.9377985799116962, 'support': 29841.0} |
78
+ | No log | 7.0 | 287 | 0.2014 | {'precision': 0.8799403430275914, 'recall': 0.9111969111969112, 'f1-score': 0.8952959028831563, 'support': 1295.0} | {'precision': 0.9675979919882359, 'recall': 0.9510092200348866, 'f1-score': 0.9592318906147891, 'support': 20065.0} | {'precision': 0.8888256065611118, 'recall': 0.9200565970993987, 'f1-score': 0.9041714947856316, 'support': 8481.0} | 0.9405 | {'precision': 0.9121213138589797, 'recall': 0.9274209094437321, 'f1-score': 0.919566429427859, 'support': 29841.0} | {'precision': 0.9414063343289258, 'recall': 0.940484568211521, 'f1-score': 0.9408087707079646, 'support': 29841.0} |
79
+ | No log | 8.0 | 328 | 0.2169 | {'precision': 0.8607322325915291, 'recall': 0.9258687258687258, 'f1-score': 0.8921130952380952, 'support': 1295.0} | {'precision': 0.9490554125588849, 'recall': 0.9739347121853975, 'f1-score': 0.9613341204250295, 'support': 20065.0} | {'precision': 0.9371261295659921, 'recall': 0.8681759226506308, 'f1-score': 0.9013343126453666, 'support': 8481.0} | 0.9418 | {'precision': 0.9156379249054686, 'recall': 0.9226597869015847, 'f1-score': 0.9182605094361639, 'support': 29841.0} | {'precision': 0.9418321034499257, 'recall': 0.9417914949230924, 'f1-score': 0.9412778355352336, 'support': 29841.0} |
80
+ | No log | 9.0 | 369 | 0.2356 | {'precision': 0.8841554559043349, 'recall': 0.9135135135135135, 'f1-score': 0.8985947588302315, 'support': 1295.0} | {'precision': 0.958962427602594, 'recall': 0.9654622476949912, 'f1-score': 0.9622013609496847, 'support': 20065.0} | {'precision': 0.9177306673090821, 'recall': 0.8983610423299139, 'f1-score': 0.9079425609247452, 'support': 8481.0} | 0.9441 | {'precision': 0.9202828502720036, 'recall': 0.9257789345128061, 'f1-score': 0.9229128935682205, 'support': 29841.0} | {'precision': 0.9439977284504704, 'recall': 0.9441372608156563, 'f1-score': 0.944020353853535, 'support': 29841.0} |
81
+ | No log | 10.0 | 410 | 0.2491 | {'precision': 0.846045197740113, 'recall': 0.9250965250965251, 'f1-score': 0.883806713389893, 'support': 1295.0} | {'precision': 0.9549009000147544, 'recall': 0.9676551208572141, 'f1-score': 0.9612357047378584, 'support': 20065.0} | {'precision': 0.9259762728620861, 'recall': 0.8835043037377668, 'f1-score': 0.904241839135944, 'support': 8481.0} | 0.9419 | {'precision': 0.9089741235389845, 'recall': 0.9254186498971686, 'f1-score': 0.9164280857545651, 'support': 29841.0} | {'precision': 0.941956364063297, 'recall': 0.9418920277470594, 'f1-score': 0.9416775291416837, 'support': 29841.0} |
82
+ | No log | 11.0 | 451 | 0.2823 | {'precision': 0.8699127906976745, 'recall': 0.9243243243243243, 'f1-score': 0.8962935230250841, 'support': 1295.0} | {'precision': 0.9454922579711543, 'recall': 0.9768751557438325, 'f1-score': 0.9609275419158742, 'support': 20065.0} | {'precision': 0.9427204551331781, 'recall': 0.8596863577408325, 'f1-score': 0.8992907801418439, 'support': 8481.0} | 0.9413 | {'precision': 0.9193751679340023, 'recall': 0.9202952792696631, 'f1-score': 0.9188372816942675, 'support': 29841.0} | {'precision': 0.9414245970352596, 'recall': 0.9412888308032573, 'f1-score': 0.9406050851929385, 'support': 29841.0} |
83
+ | No log | 12.0 | 492 | 0.2666 | {'precision': 0.8749080206033848, 'recall': 0.9181467181467181, 'f1-score': 0.896006028636021, 'support': 1295.0} | {'precision': 0.9618267212950934, 'recall': 0.9593820084724645, 'f1-score': 0.9606028094513335, 'support': 20065.0} | {'precision': 0.9059990552668871, 'recall': 0.9046103053885155, 'f1-score': 0.9053041477373296, 'support': 8481.0} | 0.9420 | {'precision': 0.9142445990551217, 'recall': 0.9273796773358992, 'f1-score': 0.9206376619415613, 'support': 29841.0} | {'precision': 0.9421881651816595, 'recall': 0.9420260715123487, 'f1-score': 0.9420832966618057, 'support': 29841.0} |
84
+ | 0.1288 | 13.0 | 533 | 0.2789 | {'precision': 0.8708971553610503, 'recall': 0.922007722007722, 'f1-score': 0.8957239309827456, 'support': 1295.0} | {'precision': 0.960913024019096, 'recall': 0.9630201844006977, 'f1-score': 0.961965450291233, 'support': 20065.0} | {'precision': 0.9144839134074871, 'recall': 0.9015446291710884, 'f1-score': 0.9079681748010924, 'support': 8481.0} | 0.9438 | {'precision': 0.9154313642625445, 'recall': 0.928857511859836, 'f1-score': 0.9218858520250238, 'support': 29841.0} | {'precision': 0.9438111897303917, 'recall': 0.9437686404611105, 'f1-score': 0.9437444234846122, 'support': 29841.0} |
85
+ | 0.1288 | 14.0 | 574 | 0.2878 | {'precision': 0.8693759071117562, 'recall': 0.9250965250965251, 'f1-score': 0.8963711185933408, 'support': 1295.0} | {'precision': 0.9577367433593365, 'recall': 0.9667580363817593, 'f1-score': 0.9622262456906173, 'support': 20065.0} | {'precision': 0.9222804239249605, 'recall': 0.8927013323900483, 'f1-score': 0.9072498502097065, 'support': 8481.0} | 0.9439 | {'precision': 0.9164643581320178, 'recall': 0.9281852979561108, 'f1-score': 0.9219490714978882, 'support': 29841.0} | {'precision': 0.9438252682725914, 'recall': 0.9439026842263999, 'f1-score': 0.943743714955569, 'support': 29841.0} |
86
+ | 0.1288 | 15.0 | 615 | 0.3028 | {'precision': 0.8794642857142857, 'recall': 0.9127413127413128, 'f1-score': 0.8957938613111027, 'support': 1295.0} | {'precision': 0.9580749193748449, 'recall': 0.9623722900573137, 'f1-score': 0.9602187966185977, 'support': 20065.0} | {'precision': 0.9105730040757612, 'recall': 0.8956490979837284, 'f1-score': 0.9030493966593355, 'support': 8481.0} | 0.9413 | {'precision': 0.916037403054964, 'recall': 0.9235875669274516, 'f1-score': 0.9196873515296785, 'support': 29841.0} | {'precision': 0.9411631364506148, 'recall': 0.9412553198619349, 'f1-score': 0.941175065769172, 'support': 29841.0} |
87
+ | 0.1288 | 16.0 | 656 | 0.3010 | {'precision': 0.8761061946902655, 'recall': 0.9173745173745174, 'f1-score': 0.8962655601659751, 'support': 1295.0} | {'precision': 0.9587562509283557, 'recall': 0.9650635434836781, 'f1-score': 0.9618995578957825, 'support': 20065.0} | {'precision': 0.9175916988416989, 'recall': 0.8967102935974531, 'f1-score': 0.907030830699505, 'support': 8481.0} | 0.9436 | {'precision': 0.9174847148201067, 'recall': 0.9263827848185495, 'f1-score': 0.9217319829204209, 'support': 29841.0} | {'precision': 0.943470289027774, 'recall': 0.9435675748131765, 'f1-score': 0.9434572234427906, 'support': 29841.0} |
88
 
89
 
90
  ### Framework versions
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