trainer: training complete at 2024-04-23 12:40:09.588057.

README.md

@@ -17,12 +17,12 @@ model-index:
       name: essays_su_g
       type: essays_su_g
       config: sep_tok
-      split: train[80%:100%]
+      split: train[0%:20%]
       args: sep_tok
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9138865510856758
+      value: 0.9097784810126582
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,14 +32,14 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the essays_su_g dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7436
-- Claim: {'precision': 0.700735294117647, 'recall': 0.6859404990403071, 'f1-score': 0.6932589718719689, 'support': 4168.0}
-- Majorclaim: {'precision': 0.9293954776188279, 'recall': 0.9358736059479554, 'f1-score': 0.932623292428803, 'support': 2152.0}
-- O: {'precision': 0.9999116061168567, 'recall': 1.0, 'f1-score': 0.9999558011049724, 'support': 11312.0}
-- Premise: {'precision': 0.9025936599423631, 'recall': 0.9079764764350203, 'f1-score': 0.9052770666446445, 'support': 12073.0}
-- Accuracy: 0.9139
-- Macro avg: {'precision': 0.8831590094489237, 'recall': 0.8824476453558208, 'f1-score': 0.8827787830125972, 'support': 29705.0}
-- Weighted avg: {'precision': 0.9132717427569804, 'recall': 0.9138865510856758, 'f1-score': 0.9135640049745629, 'support': 29705.0}
+- Loss: 0.6673
+- Claim: {'precision': 0.6793010091065715, 'recall': 0.6475832942280619, 'f1-score': 0.663063063063063, 'support': 4262.0}
+- Majorclaim: {'precision': 0.9517884914463453, 'recall': 0.8480369515011548, 'f1-score': 0.8969223253541768, 'support': 2165.0}
+- O: {'precision': 0.9979434024350116, 'recall': 0.9997527608373167, 'f1-score': 0.9988472622478387, 'support': 12134.0}
+- Premise: {'precision': 0.8936961046684508, 'recall': 0.922003221105913, 'f1-score': 0.9076290060775357, 'support': 13039.0}
+- Accuracy: 0.9098
+- Macro avg: {'precision': 0.8806822519140949, 'recall': 0.8543440569181115, 'f1-score': 0.8666154141856536, 'support': 31600.0}
+- Weighted avg: {'precision': 0.908789611984554, 'recall': 0.9097784810126582, 'f1-score': 0.9089366740356591, 'support': 31600.0}
 
 ## Model description
 
@@ -64,62 +64,32 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 50
+- num_epochs: 20
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Claim                                                                                                              | Majorclaim                                                                                                         | O                                                                                                                   | Premise                                                                                                             | Accuracy | Macro avg                                                                                                           | Weighted avg                                                                                                        |
 |:-------------:|:-----:|:----:|:---------------:|:------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:--------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
-| No log        | 1.0   | 81   | 0.2830          | {'precision': 0.5768789443488239, 'recall': 0.4824856046065259, 'f1-score': 0.5254768748366867, 'support': 4168.0} | {'precision': 0.7495921696574225, 'recall': 0.854089219330855, 'f1-score': 0.7984361424847959, 'support': 2152.0}  | {'precision': 0.9988511841640155, 'recall': 0.9992043847241867, 'f1-score': 0.9990277532260916, 'support': 11312.0} | {'precision': 0.8719781543651113, 'recall': 0.8992793837488611, 'f1-score': 0.8854183656825966, 'support': 12073.0} | 0.8756   | {'precision': 0.7993251131338432, 'recall': 0.8087646481026072, 'f1-score': 0.8020897840575427, 'support': 29705.0} | {'precision': 0.8700202202343714, 'recall': 0.8755765022723447, 'f1-score': 0.8718761173649596, 'support': 29705.0} |
-| No log        | 2.0   | 162  | 0.2736          | {'precision': 0.6124497991967871, 'recall': 0.5122360844529751, 'f1-score': 0.5578782336033447, 'support': 4168.0} | {'precision': 0.9571619812583668, 'recall': 0.6644981412639405, 'f1-score': 0.784421283598464, 'support': 2152.0}  | {'precision': 0.9997348652231551, 'recall': 1.0, 'f1-score': 0.9998674150351351, 'support': 11312.0}                | {'precision': 0.8530201342281879, 'recall': 0.9474861260664292, 'f1-score': 0.8977749872463995, 'support': 12073.0} | 0.8859   | {'precision': 0.8555916949766242, 'recall': 0.7810550879458362, 'f1-score': 0.8099854798708358, 'support': 29705.0} | {'precision': 0.8826802296805741, 'recall': 0.8859114627167144, 'f1-score': 0.8807489883812781, 'support': 29705.0} |
-| No log        | 3.0   | 243  | 0.2259          | {'precision': 0.6627322953289804, 'recall': 0.6331573896353166, 'f1-score': 0.64760736196319, 'support': 4168.0}   | {'precision': 0.8881875563570785, 'recall': 0.9154275092936803, 'f1-score': 0.9016018306636155, 'support': 2152.0} | {'precision': 1.0, 'recall': 0.9993811881188119, 'f1-score': 0.9996904982977407, 'support': 11312.0}                | {'precision': 0.8936065573770492, 'recall': 0.9030067091857865, 'f1-score': 0.8982820417748115, 'support': 12073.0} | 0.9027   | {'precision': 0.861131602265777, 'recall': 0.8627431990583988, 'f1-score': 0.8617954331748394, 'support': 29705.0}  | {'precision': 0.9013351218793044, 'recall': 0.9027436458508669, 'f1-score': 0.9019670975035187, 'support': 29705.0} |
-| No log        | 4.0   | 324  | 0.3234          | {'precision': 0.5561865427637239, 'recall': 0.7754318618042226, 'f1-score': 0.6477602966229081, 'support': 4168.0} | {'precision': 0.8627031650983746, 'recall': 0.9372676579925651, 'f1-score': 0.8984409799554566, 'support': 2152.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | {'precision': 0.9384029675907849, 'recall': 0.7962395427814131, 'f1-score': 0.861495720750997, 'support': 12073.0}  | 0.8811   | {'precision': 0.8393231688632209, 'recall': 0.8772347656445502, 'f1-score': 0.8519242493323405, 'support': 29705.0} | {'precision': 0.9027457246003854, 'recall': 0.8811311227066151, 'f1-score': 0.8869263673393438, 'support': 29705.0} |
-| No log        | 5.0   | 405  | 0.3072          | {'precision': 0.6833864888373442, 'recall': 0.5654990403071017, 'f1-score': 0.6188788236838649, 'support': 4168.0} | {'precision': 0.9230033476805356, 'recall': 0.8968401486988847, 'f1-score': 0.909733679000707, 'support': 2152.0}  | {'precision': 0.9999116061168567, 'recall': 1.0, 'f1-score': 0.9999558011049724, 'support': 11312.0}                | {'precision': 0.8706816059757236, 'recall': 0.9268615919821088, 'f1-score': 0.8978936810431294, 'support': 12073.0} | 0.9018   | {'precision': 0.8692457621526151, 'recall': 0.8473001952470238, 'f1-score': 0.8566154962081685, 'support': 29705.0} | {'precision': 0.8974043833368577, 'recall': 0.9018347079616226, 'f1-score': 0.8984684143294738, 'support': 29705.0} |
-| No log        | 6.0   | 486  | 0.3635          | {'precision': 0.6545212765957447, 'recall': 0.5904510556621881, 'f1-score': 0.620837537840565, 'support': 4168.0}  | {'precision': 0.8547509418166597, 'recall': 0.9488847583643123, 'f1-score': 0.8993613741466637, 'support': 2152.0} | {'precision': 0.9999116061168567, 'recall': 1.0, 'f1-score': 0.9999558011049724, 'support': 11312.0}                | {'precision': 0.8869558114841134, 'recall': 0.8994450426571688, 'f1-score': 0.8931567692054615, 'support': 12073.0} | 0.8980   | {'precision': 0.8490349090033436, 'recall': 0.8596952141709173, 'f1-score': 0.8533278705744156, 'support': 29705.0} | {'precision': 0.8950239457358053, 'recall': 0.8979633058407676, 'f1-score': 0.8960665959131486, 'support': 29705.0} |
-| 0.214         | 7.0   | 567  | 0.3469          | {'precision': 0.6769303647560397, 'recall': 0.685700575815739, 'f1-score': 0.6812872467222885, 'support': 4168.0}  | {'precision': 0.9319887429643527, 'recall': 0.9233271375464684, 'f1-score': 0.9276377217553688, 'support': 2152.0} | {'precision': 0.9999115983026874, 'recall': 0.9999115983026874, 'f1-score': 0.9999115983026874, 'support': 11312.0} | {'precision': 0.9029819752471135, 'recall': 0.9004389961070156, 'f1-score': 0.9017086927670869, 'support': 12073.0} | 0.9098   | {'precision': 0.8779531703175483, 'recall': 0.8773445769429775, 'f1-score': 0.8776363148868579, 'support': 29705.0} | {'precision': 0.910277290769933, 'recall': 0.9098468271334792, 'f1-score': 0.9100559053806798, 'support': 29705.0}  |
-| 0.214         | 8.0   | 648  | 0.4017          | {'precision': 0.6105725260654838, 'recall': 0.8008637236084453, 'f1-score': 0.6928905033731187, 'support': 4168.0} | {'precision': 0.9278779472954231, 'recall': 0.9326208178438662, 'f1-score': 0.9302433371958285, 'support': 2152.0} | {'precision': 1.0, 'recall': 0.9998231966053748, 'f1-score': 0.9999115904871364, 'support': 11312.0}                | {'precision': 0.9356247097073851, 'recall': 0.8342582622380519, 'f1-score': 0.8820387074174622, 'support': 12073.0} | 0.8997   | {'precision': 0.868518795767073, 'recall': 0.8918915000739345, 'f1-score': 0.8762710346183864, 'support': 29705.0}  | {'precision': 0.9139692560686062, 'recall': 0.8997475172529877, 'f1-score': 0.9038782866839282, 'support': 29705.0} |
-| 0.214         | 9.0   | 729  | 0.4713          | {'precision': 0.7130531589201224, 'recall': 0.6146833013435701, 'f1-score': 0.6602241979126401, 'support': 4168.0} | {'precision': 0.8839681133746679, 'recall': 0.9275092936802974, 'f1-score': 0.9052154195011338, 'support': 2152.0} | {'precision': 0.9999116061168567, 'recall': 1.0, 'f1-score': 0.9999558011049724, 'support': 11312.0}                | {'precision': 0.8903596204449405, 'recall': 0.9248736850824153, 'f1-score': 0.9072885349800925, 'support': 12073.0} | 0.9101   | {'precision': 0.8718231247141469, 'recall': 0.8667665700265708, 'f1-score': 0.8681709883747097, 'support': 29705.0} | {'precision': 0.9067368029754924, 'recall': 0.910149806429894, 'f1-score': 0.9077607320175198, 'support': 29705.0}  |
-| 0.214         | 10.0  | 810  | 0.4968          | {'precision': 0.6562300319488817, 'recall': 0.7392034548944337, 'f1-score': 0.6952499153785399, 'support': 4168.0} | {'precision': 0.9344422700587084, 'recall': 0.887546468401487, 'f1-score': 0.9103908484270734, 'support': 2152.0}  | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | {'precision': 0.9174532349407929, 'recall': 0.8856125238134681, 'f1-score': 0.9012517385257303, 'support': 12073.0} | 0.9088   | {'precision': 0.8770313842370958, 'recall': 0.8780906117773473, 'f1-score': 0.8767231255828358, 'support': 29705.0} | {'precision': 0.9134657277821738, 'recall': 0.9087695674128935, 'f1-score': 0.9106135328171674, 'support': 29705.0} |
-| 0.214         | 11.0  | 891  | 0.5865          | {'precision': 0.6913151364764268, 'recall': 0.668426103646833, 'f1-score': 0.6796779702366431, 'support': 4168.0}  | {'precision': 0.9079646017699115, 'recall': 0.9535315985130112, 'f1-score': 0.9301903898458749, 'support': 2152.0} | {'precision': 0.9999116061168567, 'recall': 1.0, 'f1-score': 0.9999558011049724, 'support': 11312.0}                | {'precision': 0.9008428358948934, 'recall': 0.9030067091857865, 'f1-score': 0.901923474663909, 'support': 12073.0}  | 0.9107   | {'precision': 0.8750085450645222, 'recall': 0.8812411028364077, 'f1-score': 0.8779369089628499, 'support': 29705.0} | {'precision': 0.9096858090555641, 'recall': 0.9106884362901868, 'f1-score': 0.9101191594213591, 'support': 29705.0} |
-| 0.214         | 12.0  | 972  | 0.5556          | {'precision': 0.6425824731835661, 'recall': 0.7617562380038387, 'f1-score': 0.697112745636184, 'support': 4168.0}  | {'precision': 0.920556552962298, 'recall': 0.9530669144981413, 'f1-score': 0.9365296803652968, 'support': 2152.0}  | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | {'precision': 0.9260513186029936, 'recall': 0.8609293464756067, 'f1-score': 0.8923037300940034, 'support': 12073.0} | 0.9066   | {'precision': 0.8722975861872144, 'recall': 0.8939381247443967, 'f1-score': 0.8814865390238711, 'support': 29705.0} | {'precision': 0.9140393543072853, 'recall': 0.9066487123379903, 'f1-score': 0.9091318205481447, 'support': 29705.0} |
-| 0.0252        | 13.0  | 1053 | 0.5548          | {'precision': 0.7212470526591565, 'recall': 0.6605086372360844, 'f1-score': 0.6895428929242329, 'support': 4168.0} | {'precision': 0.9069870939029817, 'recall': 0.9470260223048327, 'f1-score': 0.9265742214139577, 'support': 2152.0} | {'precision': 0.9999116061168567, 'recall': 1.0, 'f1-score': 0.9999558011049724, 'support': 11312.0}                | {'precision': 0.8989292667099286, 'recall': 0.917916010933488, 'f1-score': 0.9083234293676489, 'support': 12073.0}  | 0.9152   | {'precision': 0.8817687548472308, 'recall': 0.8813626676186013, 'f1-score': 0.8810990862027029, 'support': 29705.0} | {'precision': 0.9130371003853032, 'recall': 0.9151657970038714, 'f1-score': 0.9138424940934561, 'support': 29705.0} |
-| 0.0252        | 14.0  | 1134 | 0.5989          | {'precision': 0.6706368497812348, 'recall': 0.6619481765834933, 'f1-score': 0.6662641873943491, 'support': 4168.0} | {'precision': 0.9337434926644581, 'recall': 0.91682156133829, 'f1-score': 0.9252051582649472, 'support': 2152.0}   | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | {'precision': 0.8933914187078744, 'recall': 0.9002733371987078, 'f1-score': 0.8968191757085687, 'support': 12073.0} | 0.9060   | {'precision': 0.8744429402883919, 'recall': 0.8697607687801228, 'f1-score': 0.8720721303419663, 'support': 29705.0} | {'precision': 0.9056571278963901, 'recall': 0.9060090893788925, 'f1-score': 0.9058181633386757, 'support': 29705.0} |
-| 0.0252        | 15.0  | 1215 | 0.5878          | {'precision': 0.7189061267420458, 'recall': 0.6559500959692899, 'f1-score': 0.6859867017940033, 'support': 4168.0} | {'precision': 0.9410912602607436, 'recall': 0.9056691449814126, 'f1-score': 0.9230404925408477, 'support': 2152.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | {'precision': 0.89272306094736, 'recall': 0.9257019796239543, 'f1-score': 0.9089134677944047, 'support': 12073.0}   | 0.9147   | {'precision': 0.8881801119875374, 'recall': 0.8718303051436642, 'f1-score': 0.8794851655323139, 'support': 29705.0} | {'precision': 0.9126906124611831, 'recall': 0.9146944958761152, 'f1-score': 0.9133441511431463, 'support': 29705.0} |
-| 0.0252        | 16.0  | 1296 | 0.5438          | {'precision': 0.6844300278035218, 'recall': 0.7087332053742802, 'f1-score': 0.6963696369636965, 'support': 4168.0} | {'precision': 0.9468033186920449, 'recall': 0.9014869888475836, 'f1-score': 0.9235896215186861, 'support': 2152.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | {'precision': 0.9065513801130695, 'recall': 0.9031723680940943, 'f1-score': 0.9048587195552051, 'support': 12073.0} | 0.9126   | {'precision': 0.884446181652159, 'recall': 0.8783481405789896, 'f1-score': 0.881204494509397, 'support': 29705.0}   | {'precision': 0.9138872213369954, 'recall': 0.9126409695337485, 'f1-score': 0.913192823886985, 'support': 29705.0}  |
-| 0.0252        | 17.0  | 1377 | 0.6229          | {'precision': 0.7666776207689779, 'recall': 0.5597408829174664, 'f1-score': 0.647066981001248, 'support': 4168.0}  | {'precision': 0.8876889848812095, 'recall': 0.9549256505576208, 'f1-score': 0.9200805910006717, 'support': 2152.0} | {'precision': 0.9999116061168567, 'recall': 1.0, 'f1-score': 0.9999558011049724, 'support': 11312.0}                | {'precision': 0.8760165720423507, 'recall': 0.9457467075291974, 'f1-score': 0.9095471382482972, 'support': 12073.0} | 0.9129   | {'precision': 0.8825736959523487, 'recall': 0.8651033102510712, 'f1-score': 0.8691626278387974, 'support': 29705.0} | {'precision': 0.9087011338660376, 'recall': 0.912910284463895, 'f1-score': 0.9079094842894391, 'support': 29705.0}  |
-| 0.0252        | 18.0  | 1458 | 0.5978          | {'precision': 0.6511780104712042, 'recall': 0.7161708253358925, 'f1-score': 0.6821297989031078, 'support': 4168.0} | {'precision': 0.9169724770642201, 'recall': 0.9289033457249071, 'f1-score': 0.922899353647276, 'support': 2152.0}  | {'precision': 0.9999116061168567, 'recall': 1.0, 'f1-score': 0.9999558011049724, 'support': 11312.0}                | {'precision': 0.9112487100103199, 'recall': 0.8776608962146939, 'f1-score': 0.8941394877853255, 'support': 12073.0} | 0.9053   | {'precision': 0.8698277009156502, 'recall': 0.8806837668188734, 'f1-score': 0.8747811103601705, 'support': 29705.0} | {'precision': 0.9089358856298488, 'recall': 0.9053021376872581, 'f1-score': 0.9067713337488226, 'support': 29705.0} |
-| 0.0101        | 19.0  | 1539 | 0.6089          | {'precision': 0.711257519335434, 'recall': 0.5957293666026872, 'f1-score': 0.6483875179527353, 'support': 4168.0}  | {'precision': 0.9259431765253843, 'recall': 0.9237918215613383, 'f1-score': 0.9248662479646429, 'support': 2152.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | {'precision': 0.8779302234417875, 'recall': 0.92752422761534, 'f1-score': 0.9020460770098276, 'support': 12073.0}   | 0.9083   | {'precision': 0.8787827298256514, 'recall': 0.8617613539448413, 'f1-score': 0.8688249607318015, 'support': 29705.0} | {'precision': 0.9045077476547858, 'recall': 0.9082982662851372, 'f1-score': 0.9054096491562553, 'support': 29705.0} |
-| 0.0101        | 20.0  | 1620 | 0.6036          | {'precision': 0.66363819907127, 'recall': 0.7886276391554703, 'f1-score': 0.7207543032562219, 'support': 4168.0}   | {'precision': 0.9459078080903104, 'recall': 0.9344795539033457, 'f1-score': 0.9401589527816735, 'support': 2152.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | {'precision': 0.9299982322785929, 'recall': 0.8715315166073055, 'f1-score': 0.8998161371702227, 'support': 12073.0} | 0.9134   | {'precision': 0.8848860598600434, 'recall': 0.8986596774165303, 'f1-score': 0.8901823483020296, 'support': 29705.0} | {'precision': 0.9204344815700675, 'recall': 0.9133815855916513, 'f1-score': 0.9157652323317351, 'support': 29705.0} |
-| 0.0101        | 21.0  | 1701 | 0.6373          | {'precision': 0.7248196633716271, 'recall': 0.650911708253359, 'f1-score': 0.6858804196688157, 'support': 4168.0}  | {'precision': 0.9418113561708118, 'recall': 0.9326208178438662, 'f1-score': 0.9371935559187485, 'support': 2152.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | {'precision': 0.8915248821790878, 'recall': 0.9244595378116458, 'f1-score': 0.907693558880937, 'support': 12073.0}  | 0.9154   | {'precision': 0.8895389754303817, 'recall': 0.8769980159772177, 'f1-score': 0.8826918836171254, 'support': 29705.0} | {'precision': 0.9130855511853444, 'recall': 0.9154351119340178, 'f1-score': 0.913858759733591, 'support': 29705.0}  |
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-| 0.0015        | 42.0  | 3402 | 0.7536          | {'precision': 0.6951059931954986, 'recall': 0.6372360844529751, 'f1-score': 0.6649142571035175, 'support': 4168.0} | {'precision': 0.9253592953175707, 'recall': 0.9275092936802974, 'f1-score': 0.9264330471106985, 'support': 2152.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 11312.0}                                              | {'precision': 0.8890052356020942, 'recall': 0.9141886854965626, 'f1-score': 0.9014211042143091, 'support': 12073.0} | 0.9090   | {'precision': 0.8773676310287909, 'recall': 0.8697335159074588, 'f1-score': 0.8731921021071313, 'support': 29705.0} | {'precision': 0.9067003936235091, 'recall': 0.9089715536105033, 'f1-score': 0.9075880670651082, 'support': 29705.0} |
-| 0.0015        | 43.0  | 3483 | 0.7570          | {'precision': 0.6914354644149577, 'recall': 0.6876199616122841, 'f1-score': 0.6895224347407675, 'support': 4168.0} | {'precision': 0.9220369535826949, 'recall': 0.9507434944237918, 'f1-score': 0.9361702127659575, 'support': 2152.0} | {'precision': 0.9999116061168567, 'recall': 1.0, 'f1-score': 0.9999558011049724, 'support': 11312.0}                | {'precision': 0.9040571998669771, 'recall': 0.9006874844694773, 'f1-score': 0.9023691962989088, 'support': 12073.0} | 0.9122   | {'precision': 0.8793603059953716, 'recall': 0.8847627351263884, 'f1-score': 0.8820044112276516, 'support': 29705.0} | {'precision': 0.9120285878532032, 'recall': 0.9122369971385289, 'f1-score': 0.9121148336942613, 'support': 29705.0} |
-| 0.0013        | 44.0  | 3564 | 0.7517          | {'precision': 0.6876495931067497, 'recall': 0.689299424184261, 'f1-score': 0.6884735202492213, 'support': 4168.0}  | {'precision': 0.9240969364426155, 'recall': 0.9391263940520446, 'f1-score': 0.9315510486287162, 'support': 2152.0} | {'precision': 0.9999116061168567, 'recall': 1.0, 'f1-score': 0.9999558011049724, 'support': 11312.0}                | {'precision': 0.9038829300740001, 'recall': 0.9004389961070156, 'f1-score': 0.9021576763485477, 'support': 12073.0} | 0.9115   | {'precision': 0.8788852664350555, 'recall': 0.8822162035858303, 'f1-score': 0.8805345115828644, 'support': 29705.0} | {'precision': 0.9115757890749278, 'recall': 0.9115300454468944, 'f1-score': 0.9115470505875514, 'support': 29705.0} |
-| 0.0013        | 45.0  | 3645 | 0.7445          | {'precision': 0.713818479149632, 'recall': 0.628358925143954, 'f1-score': 0.6683679979584024, 'support': 4168.0}   | {'precision': 0.9268518518518518, 'recall': 0.9302973977695167, 'f1-score': 0.9285714285714285, 'support': 2152.0} | {'precision': 0.9999116061168567, 'recall': 1.0, 'f1-score': 0.9999558011049724, 'support': 11312.0}                | {'precision': 0.8871288704927167, 'recall': 0.9231342665451835, 'f1-score': 0.9047735021919143, 'support': 12073.0} | 0.9116   | {'precision': 0.8819277019027643, 'recall': 0.8704476473646635, 'f1-score': 0.8754171824566794, 'support': 29705.0} | {'precision': 0.9086378572002458, 'recall': 0.9115637098131628, 'f1-score': 0.9095732719689872, 'support': 29705.0} |
-| 0.0013        | 46.0  | 3726 | 0.7457          | {'precision': 0.7061894108873975, 'recall': 0.6816218809980806, 'f1-score': 0.693688194359663, 'support': 4168.0}  | {'precision': 0.9259936043855642, 'recall': 0.9419144981412639, 'f1-score': 0.9338862013360976, 'support': 2152.0} | {'precision': 0.9999116061168567, 'recall': 1.0, 'f1-score': 0.9999558011049724, 'support': 11312.0}                | {'precision': 0.9022167487684729, 'recall': 0.9102128716971755, 'f1-score': 0.9061971714839401, 'support': 12073.0} | 0.9146   | {'precision': 0.8835778425395728, 'recall': 0.88343731270913, 'f1-score': 0.8834318420711683, 'support': 29705.0}   | {'precision': 0.9136373875607494, 'recall': 0.9146271671435785, 'f1-score': 0.9140896809557788, 'support': 29705.0} |
-| 0.0013        | 47.0  | 3807 | 0.7466          | {'precision': 0.717948717948718, 'recall': 0.6583493282149712, 'f1-score': 0.6868585732165207, 'support': 4168.0}  | {'precision': 0.9279816513761467, 'recall': 0.9400557620817844, 'f1-score': 0.9339796860572483, 'support': 2152.0} | {'precision': 0.9999116061168567, 'recall': 1.0, 'f1-score': 0.9999558011049724, 'support': 11312.0}                | {'precision': 0.8955609362389023, 'recall': 0.9190756232916425, 'f1-score': 0.9071659240485632, 'support': 12073.0} | 0.9148   | {'precision': 0.885350727920156, 'recall': 0.8793701783970995, 'f1-score': 0.8819899961068263, 'support': 29705.0}  | {'precision': 0.9127262764442979, 'recall': 0.9148291533411883, 'f1-score': 0.913531898357159, 'support': 29705.0}  |
-| 0.0013        | 48.0  | 3888 | 0.7467          | {'precision': 0.7121250315099571, 'recall': 0.6777831094049904, 'f1-score': 0.6945298094652735, 'support': 4168.0} | {'precision': 0.9271978021978022, 'recall': 0.9409851301115242, 'f1-score': 0.9340405904059041, 'support': 2152.0} | {'precision': 0.9999116061168567, 'recall': 1.0, 'f1-score': 0.9999558011049724, 'support': 11312.0}                | {'precision': 0.9010701740053917, 'recall': 0.9136088793174852, 'f1-score': 0.9072962079460393, 'support': 12073.0} | 0.9154   | {'precision': 0.8850761534575019, 'recall': 0.8830942797085, 'f1-score': 0.8839556022305474, 'support': 29705.0}    | {'precision': 0.914091469477332, 'recall': 0.9154014475677495, 'f1-score': 0.9146656366617318, 'support': 29705.0}  |
-| 0.0013        | 49.0  | 3969 | 0.7450          | {'precision': 0.695160125210691, 'recall': 0.692658349328215, 'f1-score': 0.6939069823338541, 'support': 4168.0}   | {'precision': 0.9298569450853715, 'recall': 0.9363382899628253, 'f1-score': 0.9330863625839315, 'support': 2152.0} | {'precision': 0.9999116061168567, 'recall': 1.0, 'f1-score': 0.9999558011049724, 'support': 11312.0}                | {'precision': 0.9042412193505633, 'recall': 0.904166321543941, 'f1-score': 0.9042037688962519, 'support': 12073.0}  | 0.9133   | {'precision': 0.8822924739408706, 'recall': 0.8832907402087453, 'f1-score': 0.8827882287297525, 'support': 29705.0} | {'precision': 0.9131925223805796, 'recall': 0.9133142568591146, 'f1-score': 0.9132522564764188, 'support': 29705.0} |
-| 0.0007        | 50.0  | 4050 | 0.7436          | {'precision': 0.700735294117647, 'recall': 0.6859404990403071, 'f1-score': 0.6932589718719689, 'support': 4168.0}  | {'precision': 0.9293954776188279, 'recall': 0.9358736059479554, 'f1-score': 0.932623292428803, 'support': 2152.0}  | {'precision': 0.9999116061168567, 'recall': 1.0, 'f1-score': 0.9999558011049724, 'support': 11312.0}                | {'precision': 0.9025936599423631, 'recall': 0.9079764764350203, 'f1-score': 0.9052770666446445, 'support': 12073.0} | 0.9139   | {'precision': 0.8831590094489237, 'recall': 0.8824476453558208, 'f1-score': 0.8827787830125972, 'support': 29705.0} | {'precision': 0.9132717427569804, 'recall': 0.9138865510856758, 'f1-score': 0.9135640049745629, 'support': 29705.0} |
+| No log        | 1.0   | 81   | 0.3209          | {'precision': 0.5136306192453511, 'recall': 0.6675269826372595, 'f1-score': 0.580553004795429, 'support': 4262.0}  | {'precision': 0.7583745194947831, 'recall': 0.6378752886836028, 'f1-score': 0.6929252383341696, 'support': 2165.0} | {'precision': 0.9967861557478368, 'recall': 0.996868303939344, 'f1-score': 0.9968272281511393, 'support': 12134.0}  | {'precision': 0.9107806691449815, 'recall': 0.8455403021704119, 'f1-score': 0.8769487750556793, 'support': 13039.0} | 0.8654   | {'precision': 0.7948929909082382, 'recall': 0.7869527193576545, 'f1-score': 0.7868135615841043, 'support': 31600.0} | {'precision': 0.8797989523023909, 'recall': 0.8654113924050633, 'f1-score': 0.8703967313850799, 'support': 31600.0} |
+| No log        | 2.0   | 162  | 0.2567          | {'precision': 0.6369094231271208, 'recall': 0.5725011731581418, 'f1-score': 0.6029902384776968, 'support': 4262.0} | {'precision': 0.8129562043795621, 'recall': 0.8230946882217091, 'f1-score': 0.8179940325912326, 'support': 2165.0} | {'precision': 0.9972866304884065, 'recall': 0.9995879347288611, 'f1-score': 0.9984359565360553, 'support': 12134.0} | {'precision': 0.8891539321654864, 'recall': 0.9147940793005599, 'f1-score': 0.9017917895214335, 'support': 13039.0} | 0.8949   | {'precision': 0.8340765475401439, 'recall': 0.8274944688523179, 'f1-score': 0.8303030042816045, 'support': 31600.0} | {'precision': 0.8914339316361279, 'recall': 0.8949050632911393, 'f1-score': 0.8928603328205832, 'support': 31600.0} |
+| No log        | 3.0   | 243  | 0.2675          | {'precision': 0.6579241071428571, 'recall': 0.5532613796339747, 'f1-score': 0.6010706092276319, 'support': 4262.0} | {'precision': 0.8917869034406215, 'recall': 0.7422632794457275, 'f1-score': 0.8101840181497353, 'support': 2165.0} | {'precision': 0.9967118783394986, 'recall': 0.9992582825119499, 'f1-score': 0.997983456109305, 'support': 12134.0}  | {'precision': 0.8758630507509432, 'recall': 0.9437073395199018, 'f1-score': 0.9085203780271707, 'support': 13039.0} | 0.8986   | {'precision': 0.8555714849184801, 'recall': 0.8096225702778885, 'f1-score': 0.8294396153784607, 'support': 31600.0} | {'precision': 0.8939642861109123, 'recall': 0.8985759493670886, 'f1-score': 0.894668981055346, 'support': 31600.0}  |
+| No log        | 4.0   | 324  | 0.2528          | {'precision': 0.6399294843543412, 'recall': 0.681370248709526, 'f1-score': 0.66, 'support': 4262.0}                | {'precision': 0.8895348837209303, 'recall': 0.8480369515011548, 'f1-score': 0.8682903759754079, 'support': 2165.0} | {'precision': 0.9971224204554797, 'recall': 0.9995055216746332, 'f1-score': 0.9983125488743466, 'support': 12134.0} | {'precision': 0.9082976236852357, 'recall': 0.8940869698596519, 'f1-score': 0.9011362757980985, 'support': 13039.0} | 0.9027   | {'precision': 0.8587211030539967, 'recall': 0.8557499229362415, 'f1-score': 0.8569348001619632, 'support': 31600.0} | {'precision': 0.9049240079307782, 'recall': 0.9027215189873418, 'f1-score': 0.9036775010177053, 'support': 31600.0} |
+| No log        | 5.0   | 405  | 0.2990          | {'precision': 0.6126, 'recall': 0.7186766776161426, 'f1-score': 0.6614122219822932, 'support': 4262.0}             | {'precision': 0.947565543071161, 'recall': 0.7011547344110854, 'f1-score': 0.805946376426865, 'support': 2165.0}   | {'precision': 0.9975324888962, 'recall': 0.9995055216746332, 'f1-score': 0.998518030627367, 'support': 12134.0}     | {'precision': 0.9121495327102803, 'recall': 0.8982283917478334, 'f1-score': 0.9051354379999227, 'support': 13039.0} | 0.8994   | {'precision': 0.8674618911694103, 'recall': 0.8293913313624237, 'f1-score': 0.842753016759112, 'support': 31600.0}  | {'precision': 0.9069606828488892, 'recall': 0.8993987341772152, 'f1-score': 0.9013256821128531, 'support': 31600.0} |
+| No log        | 6.0   | 486  | 0.3114          | {'precision': 0.6412139011257953, 'recall': 0.6147348662599719, 'f1-score': 0.6276952563488261, 'support': 4262.0} | {'precision': 0.8991759573436743, 'recall': 0.8568129330254042, 'f1-score': 0.8774834437086093, 'support': 2165.0} | {'precision': 0.99860036225918, 'recall': 0.9995879347288611, 'f1-score': 0.9990939044481055, 'support': 12134.0}   | {'precision': 0.8901916572717024, 'recall': 0.9083518674744996, 'f1-score': 0.8991800789553598, 'support': 13039.0} | 0.9003   | {'precision': 0.8572954695000881, 'recall': 0.8448719003721842, 'f1-score': 0.8508631708652252, 'support': 31600.0} | {'precision': 0.8988542850970194, 'recall': 0.900253164556962, 'f1-score': 0.8994431431727875, 'support': 31600.0}  |
+| 0.2362        | 7.0   | 567  | 0.3888          | {'precision': 0.6953872932985204, 'recall': 0.5624120131393712, 'f1-score': 0.6218705409261902, 'support': 4262.0} | {'precision': 0.9364837398373984, 'recall': 0.851270207852194, 'f1-score': 0.8918461166223083, 'support': 2165.0}  | {'precision': 0.9982714626718249, 'recall': 0.9995055216746332, 'f1-score': 0.9988881110241733, 'support': 12134.0} | {'precision': 0.8734682245654033, 'recall': 0.9402561546130839, 'f1-score': 0.9056325023084026, 'support': 13039.0} | 0.9059   | {'precision': 0.8759026800932868, 'recall': 0.8383609743198206, 'f1-score': 0.8545593177202686, 'support': 31600.0} | {'precision': 0.9016900648403317, 'recall': 0.9059493670886076, 'f1-score': 0.9022249881228259, 'support': 31600.0} |
+| 0.2362        | 8.0   | 648  | 0.4088          | {'precision': 0.6334106728538283, 'recall': 0.7045987799155327, 'f1-score': 0.6671109630123293, 'support': 4262.0} | {'precision': 0.9212598425196851, 'recall': 0.8646651270207852, 'f1-score': 0.8920657612580415, 'support': 2165.0} | {'precision': 0.9982713203819559, 'recall': 0.9994231086204055, 'f1-score': 0.998846882464377, 'support': 12134.0}  | {'precision': 0.9115860872308542, 'recall': 0.8864176700667229, 'f1-score': 0.8988257251730306, 'support': 13039.0} | 0.9038   | {'precision': 0.8661319807465809, 'recall': 0.8637761714058616, 'f1-score': 0.8642123329769446, 'support': 31600.0} | {'precision': 0.9080164253061992, 'recall': 0.9037974683544304, 'f1-score': 0.9055172784758262, 'support': 31600.0} |
+| 0.2362        | 9.0   | 729  | 0.4774          | {'precision': 0.6054054054054054, 'recall': 0.7095260441107462, 'f1-score': 0.6533434157934537, 'support': 4262.0} | {'precision': 0.882988298829883, 'recall': 0.9062355658198614, 'f1-score': 0.8944609072258947, 'support': 2165.0}  | {'precision': 0.9976968001974171, 'recall': 0.9995879347288611, 'f1-score': 0.9986414721501792, 'support': 12134.0} | {'precision': 0.9177163422214952, 'recall': 0.8604954367666232, 'f1-score': 0.8881852364931724, 'support': 13039.0} | 0.8967   | {'precision': 0.8509517116635501, 'recall': 0.868961245356523, 'f1-score': 0.8586577579156749, 'support': 31600.0}  | {'precision': 0.903926071665382, 'recall': 0.8966772151898734, 'f1-score': 0.899355076707611, 'support': 31600.0}   |
+| 0.2362        | 10.0  | 810  | 0.5144          | {'precision': 0.6497005988023952, 'recall': 0.6109807602064758, 'f1-score': 0.6297460701330109, 'support': 4262.0} | {'precision': 0.9827904118008605, 'recall': 0.7385681293302541, 'f1-score': 0.8433544303797468, 'support': 2165.0} | {'precision': 0.9987648221343873, 'recall': 0.9995879347288611, 'f1-score': 0.9991762089134196, 'support': 12134.0} | {'precision': 0.8794587945879458, 'recall': 0.9322033898305084, 'f1-score': 0.9050632911392404, 'support': 13039.0} | 0.9015   | {'precision': 0.8776786568313971, 'recall': 0.8203350535240248, 'f1-score': 0.8443350001413544, 'support': 31600.0} | {'precision': 0.901362049622011, 'recall': 0.901487341772152, 'f1-score': 0.8998406476202226, 'support': 31600.0}   |
+| 0.2362        | 11.0  | 891  | 0.5589          | {'precision': 0.6431628745212886, 'recall': 0.6698732989206945, 'f1-score': 0.6562464084587979, 'support': 4262.0} | {'precision': 0.9496362618914381, 'recall': 0.7838337182448037, 'f1-score': 0.8588056680161943, 'support': 2165.0} | {'precision': 0.9974508675273415, 'recall': 0.9996703477830888, 'f1-score': 0.9985593743568636, 'support': 12134.0} | {'precision': 0.8977522137289033, 'recall': 0.9097323414372268, 'f1-score': 0.9037025750419017, 'support': 13039.0} | 0.9033   | {'precision': 0.8720005544172429, 'recall': 0.8407774265964535, 'f1-score': 0.8543285064684394, 'support': 31600.0} | {'precision': 0.9052526145440706, 'recall': 0.9032911392405063, 'f1-score': 0.9036751198899997, 'support': 31600.0} |
+| 0.2362        | 12.0  | 972  | 0.6348          | {'precision': 0.668590065228299, 'recall': 0.6252932895354294, 'f1-score': 0.6462172647914647, 'support': 4262.0}  | {'precision': 0.9247202441505595, 'recall': 0.8397228637413395, 'f1-score': 0.8801742919389979, 'support': 2165.0} | {'precision': 0.99777924000658, 'recall': 0.9997527608373167, 'f1-score': 0.9987650255228059, 'support': 12134.0}   | {'precision': 0.8901408450704226, 'recall': 0.920929519134903, 'f1-score': 0.9052734743111314, 'support': 13039.0}  | 0.9058   | {'precision': 0.8703075986139653, 'recall': 0.8464246083122471, 'f1-score': 0.8576075141410999, 'support': 31600.0} | {'precision': 0.9039604418893055, 'recall': 0.905759493670886, 'f1-score': 0.9045136384754975, 'support': 31600.0}  |
+| 0.0312        | 13.0  | 1053 | 0.5935          | {'precision': 0.6740142052412442, 'recall': 0.6457062412013139, 'f1-score': 0.6595566207309765, 'support': 4262.0} | {'precision': 0.9273797841020608, 'recall': 0.8729792147806005, 'f1-score': 0.8993576017130621, 'support': 2165.0} | {'precision': 0.998025666337611, 'recall': 0.9998351738915444, 'f1-score': 0.9989296006587073, 'support': 12134.0}  | {'precision': 0.8968700743075884, 'recall': 0.9164046322570749, 'f1-score': 0.9065321295804567, 'support': 13039.0} | 0.9090   | {'precision': 0.8740724324971261, 'recall': 0.8587313155326335, 'f1-score': 0.8660939881708007, 'support': 31600.0} | {'precision': 0.9077455097960874, 'recall': 0.9089556962025317, 'f1-score': 0.9082096119384979, 'support': 31600.0} |
+| 0.0312        | 14.0  | 1134 | 0.6126          | {'precision': 0.6902082834570266, 'recall': 0.6764429845143125, 'f1-score': 0.6832563099893353, 'support': 4262.0} | {'precision': 0.9273270283723245, 'recall': 0.8605080831408776, 'f1-score': 0.892668902731193, 'support': 2165.0}  | {'precision': 0.9987641097470544, 'recall': 0.9990110433492665, 'f1-score': 0.9988875612871329, 'support': 12134.0} | {'precision': 0.9023875875574301, 'recall': 0.9188588081908122, 'f1-score': 0.9105487156102752, 'support': 13039.0} | 0.9129   | {'precision': 0.879671752283459, 'recall': 0.8637052297988173, 'f1-score': 0.8713403724044841, 'support': 31600.0}  | {'precision': 0.9124862715934182, 'recall': 0.9129430379746836, 'f1-score': 0.9125890170597477, 'support': 31600.0} |
+| 0.0312        | 15.0  | 1215 | 0.6346          | {'precision': 0.6470333477695972, 'recall': 0.7010793054903801, 'f1-score': 0.672972972972973, 'support': 4262.0}  | {'precision': 0.9200581395348837, 'recall': 0.877136258660508, 'f1-score': 0.8980846535824072, 'support': 2165.0}  | {'precision': 0.9985185185185185, 'recall': 0.9998351738915444, 'f1-score': 0.9991764124526437, 'support': 12134.0} | {'precision': 0.9112625313283208, 'recall': 0.8923230309072782, 'f1-score': 0.9016933390165459, 'support': 13039.0} | 0.9068   | {'precision': 0.86921813428783, 'recall': 0.8675934422374277, 'f1-score': 0.8679818445061424, 'support': 31600.0}   | {'precision': 0.9097328433538203, 'recall': 0.9067721518987342, 'f1-score': 0.9080300671504381, 'support': 31600.0} |
+| 0.0312        | 16.0  | 1296 | 0.6317          | {'precision': 0.6643092880716643, 'recall': 0.661191928671985, 'f1-score': 0.6627469426152399, 'support': 4262.0}  | {'precision': 0.9574241617881852, 'recall': 0.8309468822170901, 'f1-score': 0.8897131552917903, 'support': 2165.0} | {'precision': 0.9984362139917695, 'recall': 0.9997527608373167, 'f1-score': 0.999094053697908, 'support': 12134.0}  | {'precision': 0.8954160102033161, 'recall': 0.9153309302860649, 'f1-score': 0.9052639563106797, 'support': 13039.0} | 0.9077   | {'precision': 0.8788964185137338, 'recall': 0.8518056255031142, 'f1-score': 0.8642045269789045, 'support': 31600.0} | {'precision': 0.9080526542294312, 'recall': 0.9076898734177216, 'f1-score': 0.9075190007765268, 'support': 31600.0} |
+| 0.0312        | 17.0  | 1377 | 0.6472          | {'precision': 0.6666666666666666, 'recall': 0.684185828249648, 'f1-score': 0.6753126447429365, 'support': 4262.0}  | {'precision': 0.9678100263852243, 'recall': 0.8471131639722864, 'f1-score': 0.903448275862069, 'support': 2165.0}  | {'precision': 0.998025341451374, 'recall': 0.9996703477830888, 'f1-score': 0.9988471673254282, 'support': 12134.0}  | {'precision': 0.9003566820975943, 'recall': 0.9098857274330854, 'f1-score': 0.9050961245041197, 'support': 13039.0} | 0.9096   | {'precision': 0.8832146791502148, 'recall': 0.8602137668595271, 'f1-score': 0.8706760531086384, 'support': 31600.0} | {'precision': 0.9109630478322421, 'recall': 0.909620253164557, 'f1-score': 0.9099907564832829, 'support': 31600.0}  |
+| 0.0312        | 18.0  | 1458 | 0.6553          | {'precision': 0.672607421875, 'recall': 0.6464101360863445, 'f1-score': 0.6592486240727448, 'support': 4262.0}     | {'precision': 0.9460732984293194, 'recall': 0.8346420323325635, 'f1-score': 0.8868711656441718, 'support': 2165.0} | {'precision': 0.9978613144690301, 'recall': 0.9997527608373167, 'f1-score': 0.9988061421925816, 'support': 12134.0} | {'precision': 0.8936518568132767, 'recall': 0.920929519134903, 'f1-score': 0.9070856624867805, 'support': 13039.0}  | 0.9083   | {'precision': 0.8775484728966565, 'recall': 0.850433612097782, 'f1-score': 0.8630028985990696, 'support': 31600.0}  | {'precision': 0.9074454833508309, 'recall': 0.9082594936708861, 'f1-score': 0.9074935883527716, 'support': 31600.0} |
+| 0.0058        | 19.0  | 1539 | 0.6835          | {'precision': 0.687516356974614, 'recall': 0.6163772876583763, 'f1-score': 0.6500061858220958, 'support': 4262.0}  | {'precision': 0.9501039501039501, 'recall': 0.8443418013856813, 'f1-score': 0.8941061384201515, 'support': 2165.0} | {'precision': 0.9978613144690301, 'recall': 0.9997527608373167, 'f1-score': 0.9988061421925816, 'support': 12134.0} | {'precision': 0.8858227478464009, 'recall': 0.9305928368739934, 'f1-score': 0.9076560571492688, 'support': 13039.0} | 0.9089   | {'precision': 0.8803260923484988, 'recall': 0.8477661716888419, 'f1-score': 0.8626436308960244, 'support': 31600.0} | {'precision': 0.9065019545676358, 'recall': 0.9088607594936708, 'f1-score': 0.9069780763350475, 'support': 31600.0} |
+| 0.0058        | 20.0  | 1620 | 0.6673          | {'precision': 0.6793010091065715, 'recall': 0.6475832942280619, 'f1-score': 0.663063063063063, 'support': 4262.0}  | {'precision': 0.9517884914463453, 'recall': 0.8480369515011548, 'f1-score': 0.8969223253541768, 'support': 2165.0} | {'precision': 0.9979434024350116, 'recall': 0.9997527608373167, 'f1-score': 0.9988472622478387, 'support': 12134.0} | {'precision': 0.8936961046684508, 'recall': 0.922003221105913, 'f1-score': 0.9076290060775357, 'support': 13039.0}  | 0.9098   | {'precision': 0.8806822519140949, 'recall': 0.8543440569181115, 'f1-score': 0.8666154141856536, 'support': 31600.0} | {'precision': 0.908789611984554, 'recall': 0.9097784810126582, 'f1-score': 0.9089366740356591, 'support': 31600.0}  |
 
 
 ### Framework versions

meta_data/README_s42_e20.md

@@ -0,0 +1,100 @@
+---
+license: apache-2.0
+base_model: allenai/longformer-base-4096
+tags:
+- generated_from_trainer
+datasets:
+- essays_su_g
+metrics:
+- accuracy
+model-index:
+- name: longformer-sep_tok
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: essays_su_g
+      type: essays_su_g
+      config: sep_tok
+      split: train[0%:20%]
+      args: sep_tok
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9097784810126582
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# longformer-sep_tok
+
+This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the essays_su_g dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6673
+- Claim: {'precision': 0.6793010091065715, 'recall': 0.6475832942280619, 'f1-score': 0.663063063063063, 'support': 4262.0}
+- Majorclaim: {'precision': 0.9517884914463453, 'recall': 0.8480369515011548, 'f1-score': 0.8969223253541768, 'support': 2165.0}
+- O: {'precision': 0.9979434024350116, 'recall': 0.9997527608373167, 'f1-score': 0.9988472622478387, 'support': 12134.0}
+- Premise: {'precision': 0.8936961046684508, 'recall': 0.922003221105913, 'f1-score': 0.9076290060775357, 'support': 13039.0}
+- Accuracy: 0.9098
+- Macro avg: {'precision': 0.8806822519140949, 'recall': 0.8543440569181115, 'f1-score': 0.8666154141856536, 'support': 31600.0}
+- Weighted avg: {'precision': 0.908789611984554, 'recall': 0.9097784810126582, 'f1-score': 0.9089366740356591, 'support': 31600.0}
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Claim                                                                                                              | Majorclaim                                                                                                         | O                                                                                                                   | Premise                                                                                                             | Accuracy | Macro avg                                                                                                           | Weighted avg                                                                                                        |
+|:-------------:|:-----:|:----:|:---------------:|:------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:--------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
+| No log        | 1.0   | 81   | 0.3209          | {'precision': 0.5136306192453511, 'recall': 0.6675269826372595, 'f1-score': 0.580553004795429, 'support': 4262.0}  | {'precision': 0.7583745194947831, 'recall': 0.6378752886836028, 'f1-score': 0.6929252383341696, 'support': 2165.0} | {'precision': 0.9967861557478368, 'recall': 0.996868303939344, 'f1-score': 0.9968272281511393, 'support': 12134.0}  | {'precision': 0.9107806691449815, 'recall': 0.8455403021704119, 'f1-score': 0.8769487750556793, 'support': 13039.0} | 0.8654   | {'precision': 0.7948929909082382, 'recall': 0.7869527193576545, 'f1-score': 0.7868135615841043, 'support': 31600.0} | {'precision': 0.8797989523023909, 'recall': 0.8654113924050633, 'f1-score': 0.8703967313850799, 'support': 31600.0} |
+| No log        | 2.0   | 162  | 0.2567          | {'precision': 0.6369094231271208, 'recall': 0.5725011731581418, 'f1-score': 0.6029902384776968, 'support': 4262.0} | {'precision': 0.8129562043795621, 'recall': 0.8230946882217091, 'f1-score': 0.8179940325912326, 'support': 2165.0} | {'precision': 0.9972866304884065, 'recall': 0.9995879347288611, 'f1-score': 0.9984359565360553, 'support': 12134.0} | {'precision': 0.8891539321654864, 'recall': 0.9147940793005599, 'f1-score': 0.9017917895214335, 'support': 13039.0} | 0.8949   | {'precision': 0.8340765475401439, 'recall': 0.8274944688523179, 'f1-score': 0.8303030042816045, 'support': 31600.0} | {'precision': 0.8914339316361279, 'recall': 0.8949050632911393, 'f1-score': 0.8928603328205832, 'support': 31600.0} |
+| No log        | 3.0   | 243  | 0.2675          | {'precision': 0.6579241071428571, 'recall': 0.5532613796339747, 'f1-score': 0.6010706092276319, 'support': 4262.0} | {'precision': 0.8917869034406215, 'recall': 0.7422632794457275, 'f1-score': 0.8101840181497353, 'support': 2165.0} | {'precision': 0.9967118783394986, 'recall': 0.9992582825119499, 'f1-score': 0.997983456109305, 'support': 12134.0}  | {'precision': 0.8758630507509432, 'recall': 0.9437073395199018, 'f1-score': 0.9085203780271707, 'support': 13039.0} | 0.8986   | {'precision': 0.8555714849184801, 'recall': 0.8096225702778885, 'f1-score': 0.8294396153784607, 'support': 31600.0} | {'precision': 0.8939642861109123, 'recall': 0.8985759493670886, 'f1-score': 0.894668981055346, 'support': 31600.0}  |
+| No log        | 4.0   | 324  | 0.2528          | {'precision': 0.6399294843543412, 'recall': 0.681370248709526, 'f1-score': 0.66, 'support': 4262.0}                | {'precision': 0.8895348837209303, 'recall': 0.8480369515011548, 'f1-score': 0.8682903759754079, 'support': 2165.0} | {'precision': 0.9971224204554797, 'recall': 0.9995055216746332, 'f1-score': 0.9983125488743466, 'support': 12134.0} | {'precision': 0.9082976236852357, 'recall': 0.8940869698596519, 'f1-score': 0.9011362757980985, 'support': 13039.0} | 0.9027   | {'precision': 0.8587211030539967, 'recall': 0.8557499229362415, 'f1-score': 0.8569348001619632, 'support': 31600.0} | {'precision': 0.9049240079307782, 'recall': 0.9027215189873418, 'f1-score': 0.9036775010177053, 'support': 31600.0} |
+| No log        | 5.0   | 405  | 0.2990          | {'precision': 0.6126, 'recall': 0.7186766776161426, 'f1-score': 0.6614122219822932, 'support': 4262.0}             | {'precision': 0.947565543071161, 'recall': 0.7011547344110854, 'f1-score': 0.805946376426865, 'support': 2165.0}   | {'precision': 0.9975324888962, 'recall': 0.9995055216746332, 'f1-score': 0.998518030627367, 'support': 12134.0}     | {'precision': 0.9121495327102803, 'recall': 0.8982283917478334, 'f1-score': 0.9051354379999227, 'support': 13039.0} | 0.8994   | {'precision': 0.8674618911694103, 'recall': 0.8293913313624237, 'f1-score': 0.842753016759112, 'support': 31600.0}  | {'precision': 0.9069606828488892, 'recall': 0.8993987341772152, 'f1-score': 0.9013256821128531, 'support': 31600.0} |
+| No log        | 6.0   | 486  | 0.3114          | {'precision': 0.6412139011257953, 'recall': 0.6147348662599719, 'f1-score': 0.6276952563488261, 'support': 4262.0} | {'precision': 0.8991759573436743, 'recall': 0.8568129330254042, 'f1-score': 0.8774834437086093, 'support': 2165.0} | {'precision': 0.99860036225918, 'recall': 0.9995879347288611, 'f1-score': 0.9990939044481055, 'support': 12134.0}   | {'precision': 0.8901916572717024, 'recall': 0.9083518674744996, 'f1-score': 0.8991800789553598, 'support': 13039.0} | 0.9003   | {'precision': 0.8572954695000881, 'recall': 0.8448719003721842, 'f1-score': 0.8508631708652252, 'support': 31600.0} | {'precision': 0.8988542850970194, 'recall': 0.900253164556962, 'f1-score': 0.8994431431727875, 'support': 31600.0}  |
+| 0.2362        | 7.0   | 567  | 0.3888          | {'precision': 0.6953872932985204, 'recall': 0.5624120131393712, 'f1-score': 0.6218705409261902, 'support': 4262.0} | {'precision': 0.9364837398373984, 'recall': 0.851270207852194, 'f1-score': 0.8918461166223083, 'support': 2165.0}  | {'precision': 0.9982714626718249, 'recall': 0.9995055216746332, 'f1-score': 0.9988881110241733, 'support': 12134.0} | {'precision': 0.8734682245654033, 'recall': 0.9402561546130839, 'f1-score': 0.9056325023084026, 'support': 13039.0} | 0.9059   | {'precision': 0.8759026800932868, 'recall': 0.8383609743198206, 'f1-score': 0.8545593177202686, 'support': 31600.0} | {'precision': 0.9016900648403317, 'recall': 0.9059493670886076, 'f1-score': 0.9022249881228259, 'support': 31600.0} |
+| 0.2362        | 8.0   | 648  | 0.4088          | {'precision': 0.6334106728538283, 'recall': 0.7045987799155327, 'f1-score': 0.6671109630123293, 'support': 4262.0} | {'precision': 0.9212598425196851, 'recall': 0.8646651270207852, 'f1-score': 0.8920657612580415, 'support': 2165.0} | {'precision': 0.9982713203819559, 'recall': 0.9994231086204055, 'f1-score': 0.998846882464377, 'support': 12134.0}  | {'precision': 0.9115860872308542, 'recall': 0.8864176700667229, 'f1-score': 0.8988257251730306, 'support': 13039.0} | 0.9038   | {'precision': 0.8661319807465809, 'recall': 0.8637761714058616, 'f1-score': 0.8642123329769446, 'support': 31600.0} | {'precision': 0.9080164253061992, 'recall': 0.9037974683544304, 'f1-score': 0.9055172784758262, 'support': 31600.0} |
+| 0.2362        | 9.0   | 729  | 0.4774          | {'precision': 0.6054054054054054, 'recall': 0.7095260441107462, 'f1-score': 0.6533434157934537, 'support': 4262.0} | {'precision': 0.882988298829883, 'recall': 0.9062355658198614, 'f1-score': 0.8944609072258947, 'support': 2165.0}  | {'precision': 0.9976968001974171, 'recall': 0.9995879347288611, 'f1-score': 0.9986414721501792, 'support': 12134.0} | {'precision': 0.9177163422214952, 'recall': 0.8604954367666232, 'f1-score': 0.8881852364931724, 'support': 13039.0} | 0.8967   | {'precision': 0.8509517116635501, 'recall': 0.868961245356523, 'f1-score': 0.8586577579156749, 'support': 31600.0}  | {'precision': 0.903926071665382, 'recall': 0.8966772151898734, 'f1-score': 0.899355076707611, 'support': 31600.0}   |
+| 0.2362        | 10.0  | 810  | 0.5144          | {'precision': 0.6497005988023952, 'recall': 0.6109807602064758, 'f1-score': 0.6297460701330109, 'support': 4262.0} | {'precision': 0.9827904118008605, 'recall': 0.7385681293302541, 'f1-score': 0.8433544303797468, 'support': 2165.0} | {'precision': 0.9987648221343873, 'recall': 0.9995879347288611, 'f1-score': 0.9991762089134196, 'support': 12134.0} | {'precision': 0.8794587945879458, 'recall': 0.9322033898305084, 'f1-score': 0.9050632911392404, 'support': 13039.0} | 0.9015   | {'precision': 0.8776786568313971, 'recall': 0.8203350535240248, 'f1-score': 0.8443350001413544, 'support': 31600.0} | {'precision': 0.901362049622011, 'recall': 0.901487341772152, 'f1-score': 0.8998406476202226, 'support': 31600.0}   |
+| 0.2362        | 11.0  | 891  | 0.5589          | {'precision': 0.6431628745212886, 'recall': 0.6698732989206945, 'f1-score': 0.6562464084587979, 'support': 4262.0} | {'precision': 0.9496362618914381, 'recall': 0.7838337182448037, 'f1-score': 0.8588056680161943, 'support': 2165.0} | {'precision': 0.9974508675273415, 'recall': 0.9996703477830888, 'f1-score': 0.9985593743568636, 'support': 12134.0} | {'precision': 0.8977522137289033, 'recall': 0.9097323414372268, 'f1-score': 0.9037025750419017, 'support': 13039.0} | 0.9033   | {'precision': 0.8720005544172429, 'recall': 0.8407774265964535, 'f1-score': 0.8543285064684394, 'support': 31600.0} | {'precision': 0.9052526145440706, 'recall': 0.9032911392405063, 'f1-score': 0.9036751198899997, 'support': 31600.0} |
+| 0.2362        | 12.0  | 972  | 0.6348          | {'precision': 0.668590065228299, 'recall': 0.6252932895354294, 'f1-score': 0.6462172647914647, 'support': 4262.0}  | {'precision': 0.9247202441505595, 'recall': 0.8397228637413395, 'f1-score': 0.8801742919389979, 'support': 2165.0} | {'precision': 0.99777924000658, 'recall': 0.9997527608373167, 'f1-score': 0.9987650255228059, 'support': 12134.0}   | {'precision': 0.8901408450704226, 'recall': 0.920929519134903, 'f1-score': 0.9052734743111314, 'support': 13039.0}  | 0.9058   | {'precision': 0.8703075986139653, 'recall': 0.8464246083122471, 'f1-score': 0.8576075141410999, 'support': 31600.0} | {'precision': 0.9039604418893055, 'recall': 0.905759493670886, 'f1-score': 0.9045136384754975, 'support': 31600.0}  |
+| 0.0312        | 13.0  | 1053 | 0.5935          | {'precision': 0.6740142052412442, 'recall': 0.6457062412013139, 'f1-score': 0.6595566207309765, 'support': 4262.0} | {'precision': 0.9273797841020608, 'recall': 0.8729792147806005, 'f1-score': 0.8993576017130621, 'support': 2165.0} | {'precision': 0.998025666337611, 'recall': 0.9998351738915444, 'f1-score': 0.9989296006587073, 'support': 12134.0}  | {'precision': 0.8968700743075884, 'recall': 0.9164046322570749, 'f1-score': 0.9065321295804567, 'support': 13039.0} | 0.9090   | {'precision': 0.8740724324971261, 'recall': 0.8587313155326335, 'f1-score': 0.8660939881708007, 'support': 31600.0} | {'precision': 0.9077455097960874, 'recall': 0.9089556962025317, 'f1-score': 0.9082096119384979, 'support': 31600.0} |
+| 0.0312        | 14.0  | 1134 | 0.6126          | {'precision': 0.6902082834570266, 'recall': 0.6764429845143125, 'f1-score': 0.6832563099893353, 'support': 4262.0} | {'precision': 0.9273270283723245, 'recall': 0.8605080831408776, 'f1-score': 0.892668902731193, 'support': 2165.0}  | {'precision': 0.9987641097470544, 'recall': 0.9990110433492665, 'f1-score': 0.9988875612871329, 'support': 12134.0} | {'precision': 0.9023875875574301, 'recall': 0.9188588081908122, 'f1-score': 0.9105487156102752, 'support': 13039.0} | 0.9129   | {'precision': 0.879671752283459, 'recall': 0.8637052297988173, 'f1-score': 0.8713403724044841, 'support': 31600.0}  | {'precision': 0.9124862715934182, 'recall': 0.9129430379746836, 'f1-score': 0.9125890170597477, 'support': 31600.0} |
+| 0.0312        | 15.0  | 1215 | 0.6346          | {'precision': 0.6470333477695972, 'recall': 0.7010793054903801, 'f1-score': 0.672972972972973, 'support': 4262.0}  | {'precision': 0.9200581395348837, 'recall': 0.877136258660508, 'f1-score': 0.8980846535824072, 'support': 2165.0}  | {'precision': 0.9985185185185185, 'recall': 0.9998351738915444, 'f1-score': 0.9991764124526437, 'support': 12134.0} | {'precision': 0.9112625313283208, 'recall': 0.8923230309072782, 'f1-score': 0.9016933390165459, 'support': 13039.0} | 0.9068   | {'precision': 0.86921813428783, 'recall': 0.8675934422374277, 'f1-score': 0.8679818445061424, 'support': 31600.0}   | {'precision': 0.9097328433538203, 'recall': 0.9067721518987342, 'f1-score': 0.9080300671504381, 'support': 31600.0} |
+| 0.0312        | 16.0  | 1296 | 0.6317          | {'precision': 0.6643092880716643, 'recall': 0.661191928671985, 'f1-score': 0.6627469426152399, 'support': 4262.0}  | {'precision': 0.9574241617881852, 'recall': 0.8309468822170901, 'f1-score': 0.8897131552917903, 'support': 2165.0} | {'precision': 0.9984362139917695, 'recall': 0.9997527608373167, 'f1-score': 0.999094053697908, 'support': 12134.0}  | {'precision': 0.8954160102033161, 'recall': 0.9153309302860649, 'f1-score': 0.9052639563106797, 'support': 13039.0} | 0.9077   | {'precision': 0.8788964185137338, 'recall': 0.8518056255031142, 'f1-score': 0.8642045269789045, 'support': 31600.0} | {'precision': 0.9080526542294312, 'recall': 0.9076898734177216, 'f1-score': 0.9075190007765268, 'support': 31600.0} |
+| 0.0312        | 17.0  | 1377 | 0.6472          | {'precision': 0.6666666666666666, 'recall': 0.684185828249648, 'f1-score': 0.6753126447429365, 'support': 4262.0}  | {'precision': 0.9678100263852243, 'recall': 0.8471131639722864, 'f1-score': 0.903448275862069, 'support': 2165.0}  | {'precision': 0.998025341451374, 'recall': 0.9996703477830888, 'f1-score': 0.9988471673254282, 'support': 12134.0}  | {'precision': 0.9003566820975943, 'recall': 0.9098857274330854, 'f1-score': 0.9050961245041197, 'support': 13039.0} | 0.9096   | {'precision': 0.8832146791502148, 'recall': 0.8602137668595271, 'f1-score': 0.8706760531086384, 'support': 31600.0} | {'precision': 0.9109630478322421, 'recall': 0.909620253164557, 'f1-score': 0.9099907564832829, 'support': 31600.0}  |
+| 0.0312        | 18.0  | 1458 | 0.6553          | {'precision': 0.672607421875, 'recall': 0.6464101360863445, 'f1-score': 0.6592486240727448, 'support': 4262.0}     | {'precision': 0.9460732984293194, 'recall': 0.8346420323325635, 'f1-score': 0.8868711656441718, 'support': 2165.0} | {'precision': 0.9978613144690301, 'recall': 0.9997527608373167, 'f1-score': 0.9988061421925816, 'support': 12134.0} | {'precision': 0.8936518568132767, 'recall': 0.920929519134903, 'f1-score': 0.9070856624867805, 'support': 13039.0}  | 0.9083   | {'precision': 0.8775484728966565, 'recall': 0.850433612097782, 'f1-score': 0.8630028985990696, 'support': 31600.0}  | {'precision': 0.9074454833508309, 'recall': 0.9082594936708861, 'f1-score': 0.9074935883527716, 'support': 31600.0} |
+| 0.0058        | 19.0  | 1539 | 0.6835          | {'precision': 0.687516356974614, 'recall': 0.6163772876583763, 'f1-score': 0.6500061858220958, 'support': 4262.0}  | {'precision': 0.9501039501039501, 'recall': 0.8443418013856813, 'f1-score': 0.8941061384201515, 'support': 2165.0} | {'precision': 0.9978613144690301, 'recall': 0.9997527608373167, 'f1-score': 0.9988061421925816, 'support': 12134.0} | {'precision': 0.8858227478464009, 'recall': 0.9305928368739934, 'f1-score': 0.9076560571492688, 'support': 13039.0} | 0.9089   | {'precision': 0.8803260923484988, 'recall': 0.8477661716888419, 'f1-score': 0.8626436308960244, 'support': 31600.0} | {'precision': 0.9065019545676358, 'recall': 0.9088607594936708, 'f1-score': 0.9069780763350475, 'support': 31600.0} |
+| 0.0058        | 20.0  | 1620 | 0.6673          | {'precision': 0.6793010091065715, 'recall': 0.6475832942280619, 'f1-score': 0.663063063063063, 'support': 4262.0}  | {'precision': 0.9517884914463453, 'recall': 0.8480369515011548, 'f1-score': 0.8969223253541768, 'support': 2165.0} | {'precision': 0.9979434024350116, 'recall': 0.9997527608373167, 'f1-score': 0.9988472622478387, 'support': 12134.0} | {'precision': 0.8936961046684508, 'recall': 0.922003221105913, 'f1-score': 0.9076290060775357, 'support': 13039.0}  | 0.9098   | {'precision': 0.8806822519140949, 'recall': 0.8543440569181115, 'f1-score': 0.8666154141856536, 'support': 31600.0} | {'precision': 0.908789611984554, 'recall': 0.9097784810126582, 'f1-score': 0.9089366740356591, 'support': 31600.0}  |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

model.safetensors

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