longformer-simple / meta_data /README_s42_e50.md
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---
license: apache-2.0
base_model: allenai/longformer-base-4096
tags:
- generated_from_trainer
datasets:
- essays_su_g
metrics:
- accuracy
model-index:
- name: longformer-simple
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: essays_su_g
type: essays_su_g
config: simple
split: train[0%:20%]
args: simple
metrics:
- name: Accuracy
type: accuracy
value: 0.8424353991954728
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# longformer-simple
This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the essays_su_g dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2704
- Claim: {'precision': 0.5972354623450906, 'recall': 0.5879868606288128, 'f1-score': 0.5925750768503193, 'support': 4262.0}
- Majorclaim: {'precision': 0.8091328886608518, 'recall': 0.7284064665127021, 'f1-score': 0.7666504618376278, 'support': 2165.0}
- O: {'precision': 0.9211161229413616, 'recall': 0.8898459667612485, 'f1-score': 0.9052110715942477, 'support': 9868.0}
- Premise: {'precision': 0.8676039835969537, 'recall': 0.9086586394662167, 'f1-score': 0.8876568645813823, 'support': 13039.0}
- Accuracy: 0.8424
- Macro avg: {'precision': 0.7987721143860643, 'recall': 0.7787244833422451, 'f1-score': 0.7880233687158943, 'support': 29334.0}
- Weighted avg: {'precision': 0.8420076528182845, 'recall': 0.8424353991954728, 'f1-score': 0.8417581625139158, 'support': 29334.0}
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Claim | Majorclaim | O | Premise | Accuracy | Macro avg | Weighted avg |
|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:--------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
| No log | 1.0 | 81 | 0.5471 | {'precision': 0.45446915652538816, 'recall': 0.5082121069920226, 'f1-score': 0.4798404962339389, 'support': 4262.0} | {'precision': 0.5914396887159533, 'recall': 0.6318706697459584, 'f1-score': 0.6109870477891916, 'support': 2165.0} | {'precision': 0.9164132026585559, 'recall': 0.8243818402918525, 'f1-score': 0.8679647906108295, 'support': 9868.0} | {'precision': 0.852593810734041, 'recall': 0.8747603343814709, 'f1-score': 0.8635348449861832, 'support': 13039.0} | 0.7866 | {'precision': 0.7037289646584846, 'recall': 0.709806237852826, 'f1-score': 0.7055817949050358, 'support': 29334.0} | {'precision': 0.7969438417255414, 'recall': 0.7866298493216063, 'f1-score': 0.7906379815550267, 'support': 29334.0} |
| No log | 2.0 | 162 | 0.5196 | {'precision': 0.5064490124949617, 'recall': 0.5896292820272173, 'f1-score': 0.5448829141370338, 'support': 4262.0} | {'precision': 0.5564053537284895, 'recall': 0.8064665127020785, 'f1-score': 0.6584951914010938, 'support': 2165.0} | {'precision': 0.9374127501163332, 'recall': 0.8165788406972031, 'f1-score': 0.8728336221837087, 'support': 9868.0} | {'precision': 0.8852666561164741, 'recall': 0.858041260832886, 'f1-score': 0.8714413677610314, 'support': 13039.0} | 0.8013 | {'precision': 0.7213834431140647, 'recall': 0.7676789740648462, 'f1-score': 0.7369132738707169, 'support': 29334.0} | {'precision': 0.8234977919590369, 'recall': 0.8012886070771119, 'f1-score': 0.8087468210056704, 'support': 29334.0} |
| No log | 3.0 | 243 | 0.5239 | {'precision': 0.5717288491854966, 'recall': 0.5105584232754575, 'f1-score': 0.5394149727317799, 'support': 4262.0} | {'precision': 0.7751024590163934, 'recall': 0.6988452655889146, 'f1-score': 0.7350012144765606, 'support': 2165.0} | {'precision': 0.9378775789353699, 'recall': 0.8338062423996757, 'f1-score': 0.8827852583015933, 'support': 9868.0} | {'precision': 0.8284131594946971, 'recall': 0.9404862336068717, 'f1-score': 0.8808993606781121, 'support': 13039.0} | 0.8243 | {'precision': 0.7782805116579892, 'recall': 0.7459240412177299, 'f1-score': 0.7595252015470114, 'support': 29334.0} | {'precision': 0.8240083287170064, 'recall': 0.8242994477398241, 'f1-score': 0.8211507443896716, 'support': 29334.0} |
| No log | 4.0 | 324 | 0.4756 | {'precision': 0.5839096357768557, 'recall': 0.5943219145940872, 'f1-score': 0.5890697674418606, 'support': 4262.0} | {'precision': 0.7539079946404645, 'recall': 0.7796766743648961, 'f1-score': 0.7665758401453224, 'support': 2165.0} | {'precision': 0.9029426948890036, 'recall': 0.8861978111066072, 'f1-score': 0.8944918938270342, 'support': 9868.0} | {'precision': 0.8858629130966952, 'recall': 0.8881049160211673, 'f1-score': 0.8869824977978629, 'support': 13039.0} | 0.8368 | {'precision': 0.7816558096007548, 'recall': 0.7870753290216894, 'f1-score': 0.7842799998030201, 'support': 29334.0} | {'precision': 0.8379981834427648, 'recall': 0.8367764368991614, 'f1-score': 0.8373376573199475, 'support': 29334.0} |
| No log | 5.0 | 405 | 0.5507 | {'precision': 0.5626541134274826, 'recall': 0.5889253871421868, 'f1-score': 0.575490083686805, 'support': 4262.0} | {'precision': 0.7744245524296676, 'recall': 0.6993071593533488, 'f1-score': 0.7349514563106796, 'support': 2165.0} | {'precision': 0.9094442693560247, 'recall': 0.8772800972841508, 'f1-score': 0.893072677567442, 'support': 9868.0} | {'precision': 0.8688708112545712, 'recall': 0.8928598818927832, 'f1-score': 0.8807020198199561, 'support': 13039.0} | 0.8292 | {'precision': 0.7788484366169366, 'recall': 0.7645931314181174, 'f1-score': 0.7710540593462206, 'support': 29334.0} | {'precision': 0.8310582786320232, 'recall': 0.8291743369468876, 'f1-score': 0.8297614869521274, 'support': 29334.0} |
| No log | 6.0 | 486 | 0.6030 | {'precision': 0.5614867536575722, 'recall': 0.666353824495542, 'f1-score': 0.6094420600858369, 'support': 4262.0} | {'precision': 0.7341541267669859, 'recall': 0.74364896073903, 'f1-score': 0.7388710417622762, 'support': 2165.0} | {'precision': 0.918757975329647, 'recall': 0.8755573571139035, 'f1-score': 0.896637608966376, 'support': 9868.0} | {'precision': 0.8982569603281015, 'recall': 0.873456553416673, 'f1-score': 0.8856831790963526, 'support': 13039.0} | 0.8345 | {'precision': 0.7781639540205766, 'recall': 0.7897541739412871, 'f1-score': 0.7826584724777105, 'support': 29334.0} | {'precision': 0.8441118304632907, 'recall': 0.8344923979000477, 'f1-score': 0.8383971078959127, 'support': 29334.0} |
| 0.3501 | 7.0 | 567 | 0.7000 | {'precision': 0.5986996098829649, 'recall': 0.5401220084467386, 'f1-score': 0.5679042802516344, 'support': 4262.0} | {'precision': 0.8235613463626493, 'recall': 0.7006928406466513, 'f1-score': 0.7571749438482656, 'support': 2165.0} | {'precision': 0.9108108108108108, 'recall': 0.8879205512768544, 'f1-score': 0.8992200328407225, 'support': 9868.0} | {'precision': 0.8537819918728167, 'recall': 0.9184753432011658, 'f1-score': 0.8849479051208157, 'support': 13039.0} | 0.8372 | {'precision': 0.7967134397323103, 'recall': 0.7618026858928525, 'f1-score': 0.7773117905153596, 'support': 29334.0} | {'precision': 0.833674661665885, 'recall': 0.8371514283766278, 'f1-score': 0.834254817440735, 'support': 29334.0} |
| 0.3501 | 8.0 | 648 | 0.7253 | {'precision': 0.5610444601270289, 'recall': 0.5595964335992492, 'f1-score': 0.5603195113356043, 'support': 4262.0} | {'precision': 0.8215042372881356, 'recall': 0.7163972286374134, 'f1-score': 0.765358993338268, 'support': 2165.0} | {'precision': 0.9208110992529349, 'recall': 0.8743413052290231, 'f1-score': 0.8969747374987005, 'support': 9868.0} | {'precision': 0.8566365280289331, 'recall': 0.9082751744765702, 'f1-score': 0.8817004169148303, 'support': 13039.0} | 0.8320 | {'precision': 0.7899990811742581, 'recall': 0.764652535485564, 'f1-score': 0.7760884147718508, 'support': 29334.0} | {'precision': 0.8326847950905921, 'recall': 0.8320379082293584, 'f1-score': 0.8315580017617559, 'support': 29334.0} |
| 0.3501 | 9.0 | 729 | 0.7606 | {'precision': 0.575776926351639, 'recall': 0.6346785546691694, 'f1-score': 0.6037946428571428, 'support': 4262.0} | {'precision': 0.7266247379454926, 'recall': 0.8004618937644342, 'f1-score': 0.7617582417582419, 'support': 2165.0} | {'precision': 0.9148418491484185, 'recall': 0.8763680583704905, 'f1-score': 0.8951917602608561, 'support': 9868.0} | {'precision': 0.8901390842319112, 'recall': 0.873686632410461, 'f1-score': 0.8818361264852731, 'support': 13039.0} | 0.8345 | {'precision': 0.7768456494193653, 'recall': 0.7962987848036388, 'f1-score': 0.7856451928403785, 'support': 29334.0} | {'precision': 0.8407065761389229, 'recall': 0.8344583077657326, 'f1-score': 0.8370693701765644, 'support': 29334.0} |
| 0.3501 | 10.0 | 810 | 0.8529 | {'precision': 0.5611362700699877, 'recall': 0.639605818864383, 'f1-score': 0.5978070175438598, 'support': 4262.0} | {'precision': 0.8085327783558793, 'recall': 0.7177829099307159, 'f1-score': 0.760459995106435, 'support': 2165.0} | {'precision': 0.9375900676199977, 'recall': 0.8571139035265505, 'f1-score': 0.8955476732489809, 'support': 9868.0} | {'precision': 0.8664006502623217, 'recall': 0.8992254007209142, 'f1-score': 0.8825079030558481, 'support': 13039.0} | 0.8339 | {'precision': 0.7934149415770466, 'recall': 0.7784320082606409, 'f1-score': 0.7840806472387809, 'support': 29334.0} | {'precision': 0.8417254078619799, 'recall': 0.8339469557510056, 'f1-score': 0.8365219331064127, 'support': 29334.0} |
| 0.3501 | 11.0 | 891 | 0.8182 | {'precision': 0.5611759619541721, 'recall': 0.6091037071797278, 'f1-score': 0.5841584158415842, 'support': 4262.0} | {'precision': 0.745115856428896, 'recall': 0.7575057736720554, 'f1-score': 0.7512597343105818, 'support': 2165.0} | {'precision': 0.9214115609439273, 'recall': 0.8625861370085124, 'f1-score': 0.8910289961268711, 'support': 9868.0} | {'precision': 0.8729369206420982, 'recall': 0.8883349950149552, 'f1-score': 0.8805686483199028, 'support': 13039.0} | 0.8294 | {'precision': 0.7751600749922735, 'recall': 0.7793826532188127, 'f1-score': 0.776753948649735, 'support': 29334.0} | {'precision': 0.8345135873274777, 'recall': 0.8294470580214086, 'f1-score': 0.8314777811523291, 'support': 29334.0} |
| 0.3501 | 12.0 | 972 | 0.8319 | {'precision': 0.5907553551296505, 'recall': 0.6147348662599719, 'f1-score': 0.6025066114752213, 'support': 4262.0} | {'precision': 0.7414772727272727, 'recall': 0.7233256351039261, 'f1-score': 0.7322889876081365, 'support': 2165.0} | {'precision': 0.9154129405576013, 'recall': 0.881738954195379, 'f1-score': 0.8982604655964487, 'support': 9868.0} | {'precision': 0.8792350549616021, 'recall': 0.8956208298182375, 'f1-score': 0.8873523042437597, 'support': 13039.0} | 0.8374 | {'precision': 0.7817201558440317, 'recall': 0.7788550713443787, 'f1-score': 0.7801020922308914, 'support': 29334.0} | {'precision': 0.8393242789283376, 'recall': 0.8374241494511488, 'f1-score': 0.838191511754931, 'support': 29334.0} |
| 0.0592 | 13.0 | 1053 | 0.8901 | {'precision': 0.5857348703170029, 'recall': 0.5722665415297982, 'f1-score': 0.5789223830999287, 'support': 4262.0} | {'precision': 0.765908035299582, 'recall': 0.7616628175519631, 'f1-score': 0.7637795275590551, 'support': 2165.0} | {'precision': 0.9286720867208672, 'recall': 0.8681597081475476, 'f1-score': 0.8973969517624261, 'support': 9868.0} | {'precision': 0.8617314385150812, 'recall': 0.9114962803896004, 'f1-score': 0.8859155454511572, 'support': 13039.0} | 0.8366 | {'precision': 0.7855116077131332, 'recall': 0.7783963369047273, 'f1-score': 0.7815036019681417, 'support': 29334.0} | {'precision': 0.8370779741008496, 'recall': 0.8365718960932707, 'f1-score': 0.8361599437876358, 'support': 29334.0} |
| 0.0592 | 14.0 | 1134 | 1.0014 | {'precision': 0.5823915900131406, 'recall': 0.5199436884091976, 'f1-score': 0.5493987851741663, 'support': 4262.0} | {'precision': 0.7580798479087453, 'recall': 0.7367205542725174, 'f1-score': 0.7472475989693137, 'support': 2165.0} | {'precision': 0.9203320396722725, 'recall': 0.8651195784353466, 'f1-score': 0.8918721270371919, 'support': 9868.0} | {'precision': 0.8481164746625203, 'recall': 0.9203159751514687, 'f1-score': 0.8827423863469177, 'support': 13039.0} | 0.8300 | {'precision': 0.7772299880641695, 'recall': 0.7605249490671326, 'f1-score': 0.7678152243818974, 'support': 29334.0} | {'precision': 0.8271569887491997, 'recall': 0.8300265903047658, 'f1-score': 0.8273812231322469, 'support': 29334.0} |
| 0.0592 | 15.0 | 1215 | 0.9525 | {'precision': 0.5900047370914259, 'recall': 0.5844673862036602, 'f1-score': 0.5872230080150872, 'support': 4262.0} | {'precision': 0.787819253438114, 'recall': 0.7408775981524249, 'f1-score': 0.7636277076886455, 'support': 2165.0} | {'precision': 0.9236014917421417, 'recall': 0.8783948115119579, 'f1-score': 0.9004311016464966, 'support': 9868.0} | {'precision': 0.8681615659922577, 'recall': 0.9115729733875297, 'f1-score': 0.889337822671156, 'support': 13039.0} | 0.8403 | {'precision': 0.7923967620659849, 'recall': 0.7788281923138932, 'f1-score': 0.7851549100053463, 'support': 29334.0} | {'precision': 0.8404679570689874, 'recall': 0.8402877207336197, 'f1-score': 0.8398966533088925, 'support': 29334.0} |
| 0.0592 | 16.0 | 1296 | 0.9606 | {'precision': 0.5905569007263922, 'recall': 0.5722665415297982, 'f1-score': 0.5812678741658723, 'support': 4262.0} | {'precision': 0.6997189883580891, 'recall': 0.805080831408776, 'f1-score': 0.7487113402061856, 'support': 2165.0} | {'precision': 0.9022900763358779, 'recall': 0.8983583299554114, 'f1-score': 0.900319910628142, 'support': 9868.0} | {'precision': 0.8913718187461204, 'recall': 0.8810491602116727, 'f1-score': 0.8861804296679139, 'support': 13039.0} | 0.8364 | {'precision': 0.77098444604162, 'recall': 0.7891887157764146, 'f1-score': 0.7791198886670285, 'support': 29334.0} | {'precision': 0.8371937253222967, 'recall': 0.8364014454216949, 'f1-score': 0.8364896444998899, 'support': 29334.0} |
| 0.0592 | 17.0 | 1377 | 1.0477 | {'precision': 0.5815651380333106, 'recall': 0.5980760206475833, 'f1-score': 0.589705031810295, 'support': 4262.0} | {'precision': 0.7966360856269113, 'recall': 0.7219399538106236, 'f1-score': 0.7574509328810274, 'support': 2165.0} | {'precision': 0.917960088691796, 'recall': 0.8810295905958654, 'f1-score': 0.8991157764103624, 'support': 9868.0} | {'precision': 0.8738718745376535, 'recall': 0.9059743845386916, 'f1-score': 0.889633618255074, 'support': 13039.0} | 0.8393 | {'precision': 0.7925082967224177, 'recall': 0.7767549873981909, 'f1-score': 0.7839763398391897, 'support': 29334.0} | {'precision': 0.8405329403077433, 'recall': 0.8392650167041659, 'f1-score': 0.8394903983537285, 'support': 29334.0} |
| 0.0592 | 18.0 | 1458 | 1.0223 | {'precision': 0.5735161870503597, 'recall': 0.5985452839042703, 'f1-score': 0.5857634902411022, 'support': 4262.0} | {'precision': 0.7626000942063118, 'recall': 0.7478060046189376, 'f1-score': 0.7551305970149254, 'support': 2165.0} | {'precision': 0.9284857734656056, 'recall': 0.8630928252938792, 'f1-score': 0.8945958720655428, 'support': 9868.0} | {'precision': 0.8720382634289919, 'recall': 0.9088887184600046, 'f1-score': 0.8900822411656465, 'support': 13039.0} | 0.8365 | {'precision': 0.7841600795378172, 'recall': 0.7795832080692728, 'f1-score': 0.7813930501218043, 'support': 29334.0} | {'precision': 0.8395772728770206, 'recall': 0.8365037158246403, 'f1-score': 0.83742538167473, 'support': 29334.0} |
| 0.0221 | 19.0 | 1539 | 1.0659 | {'precision': 0.5930577757478876, 'recall': 0.6093383388080713, 'f1-score': 0.6010878370558963, 'support': 4262.0} | {'precision': 0.6994195688225538, 'recall': 0.7792147806004619, 'f1-score': 0.7371640812759448, 'support': 2165.0} | {'precision': 0.922713610991842, 'recall': 0.8710985002026753, 'f1-score': 0.896163469557965, 'support': 9868.0} | {'precision': 0.8897709231118167, 'recall': 0.9025998926298029, 'f1-score': 0.8961394959262925, 'support': 13039.0} | 0.8403 | {'precision': 0.776240469668525, 'recall': 0.7905628780602528, 'f1-score': 0.7826387209540246, 'support': 29334.0} | {'precision': 0.8436938905863776, 'recall': 0.8402877207336197, 'f1-score': 0.8415456672283212, 'support': 29334.0} |
| 0.0221 | 20.0 | 1620 | 1.1141 | {'precision': 0.5949911459650898, 'recall': 0.5518535898639136, 'f1-score': 0.5726110772976263, 'support': 4262.0} | {'precision': 0.8097686375321337, 'recall': 0.7274826789838337, 'f1-score': 0.7664233576642335, 'support': 2165.0} | {'precision': 0.9140376879102265, 'recall': 0.8749493311714633, 'f1-score': 0.8940664802733769, 'support': 9868.0} | {'precision': 0.8566118656182988, 'recall': 0.9190888871846, 'f1-score': 0.8867512671574975, 'support': 13039.0} | 0.8367 | {'precision': 0.7938523342564372, 'recall': 0.7683436218009527, 'f1-score': 0.7799630455981834, 'support': 29334.0} | {'precision': 0.8344612867135542, 'recall': 0.8367423467648463, 'f1-score': 0.8346891927657273, 'support': 29334.0} |
| 0.0221 | 21.0 | 1701 | 1.0835 | {'precision': 0.5811926605504587, 'recall': 0.5945565462224308, 'f1-score': 0.5877986546045001, 'support': 4262.0} | {'precision': 0.8357461024498887, 'recall': 0.6933025404157044, 'f1-score': 0.7578894218631658, 'support': 2165.0} | {'precision': 0.9177489177489178, 'recall': 0.8808269152817186, 'f1-score': 0.8989089404829618, 'support': 9868.0} | {'precision': 0.8672211278908587, 'recall': 0.911649666385459, 'f1-score': 0.8888805802736859, 'support': 13039.0} | 0.8391 | {'precision': 0.8004772021600309, 'recall': 0.7700839170763282, 'f1-score': 0.7833693993060784, 'support': 29334.0} | {'precision': 0.8403380390667924, 'recall': 0.8390945660325901, 'f1-score': 0.8388414732096745, 'support': 29334.0} |
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| 0.0221 | 23.0 | 1863 | 1.1053 | {'precision': 0.6242860690340204, 'recall': 0.5898639136555608, 'f1-score': 0.6065870430691278, 'support': 4262.0} | {'precision': 0.7682088868529546, 'recall': 0.77459584295612, 'f1-score': 0.7713891444342226, 'support': 2165.0} | {'precision': 0.916354556803995, 'recall': 0.8925820835022295, 'f1-score': 0.9043121149897331, 'support': 9868.0} | {'precision': 0.8755180580224985, 'recall': 0.9072781655034895, 'f1-score': 0.8911152122330608, 'support': 13039.0} | 0.8464 | {'precision': 0.7960918926783671, 'recall': 0.79108000140435, 'f1-score': 0.793350878681536, 'support': 29334.0} | {'precision': 0.8448335103073846, 'recall': 0.8464239449103429, 'f1-score': 0.8453785599743056, 'support': 29334.0} |
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| 0.0121 | 30.0 | 2430 | 1.1079 | {'precision': 0.5908226343319068, 'recall': 0.5830595964335993, 'f1-score': 0.5869154463863959, 'support': 4262.0} | {'precision': 0.7353747714808044, 'recall': 0.7431870669745958, 'f1-score': 0.7392602802664829, 'support': 2165.0} | {'precision': 0.9172500261205726, 'recall': 0.8896432914471017, 'f1-score': 0.903235763156541, 'support': 9868.0} | {'precision': 0.8796469444236666, 'recall': 0.9019096556484393, 'f1-score': 0.8906392002423507, 'support': 13039.0} | 0.8397 | {'precision': 0.7807735940892376, 'recall': 0.779449902625934, 'f1-score': 0.7800126725129426, 'support': 29334.0} | {'precision': 0.8396847417289331, 'recall': 0.8397422785845776, 'f1-score': 0.8395754817639772, 'support': 29334.0} |
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| 0.0062 | 34.0 | 2754 | 1.1772 | {'precision': 0.5838150289017341, 'recall': 0.6161426560300328, 'f1-score': 0.5995433789954339, 'support': 4262.0} | {'precision': 0.7706552706552706, 'recall': 0.7496535796766743, 'f1-score': 0.7600093654881762, 'support': 2165.0} | {'precision': 0.9282564268043455, 'recall': 0.8745439805431698, 'f1-score': 0.9006000521784504, 'support': 9868.0} | {'precision': 0.873967095957716, 'recall': 0.9003757956898535, 'f1-score': 0.8869749168933212, 'support': 13039.0} | 0.8393 | {'precision': 0.7891734555797665, 'recall': 0.7851790029849326, 'f1-score': 0.7867819283888454, 'support': 29334.0} | {'precision': 0.8424483431528531, 'recall': 0.8392650167041659, 'f1-score': 0.8404261748765735, 'support': 29334.0} |
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| 0.0043 | 42.0 | 3402 | 1.2454 | {'precision': 0.607732085693179, 'recall': 0.5790708587517598, 'f1-score': 0.5930553886819657, 'support': 4262.0} | {'precision': 0.8161802355350742, 'recall': 0.7362586605080832, 'f1-score': 0.7741622146673143, 'support': 2165.0} | {'precision': 0.9137449581135588, 'recall': 0.8953182002432104, 'f1-score': 0.9044377335312486, 'support': 9868.0} | {'precision': 0.869606622225478, 'recall': 0.9104225784185904, 'f1-score': 0.8895466466841514, 'support': 13039.0} | 0.8443 | {'precision': 0.8018159753918225, 'recall': 0.780267574480411, 'f1-score': 0.79030049589117, 'support': 29334.0} | {'precision': 0.8424633651401231, 'recall': 0.8443444467171201, 'f1-score': 0.8429622125151117, 'support': 29334.0} |
| 0.0043 | 43.0 | 3483 | 1.2396 | {'precision': 0.5977417078334509, 'recall': 0.5961989676208352, 'f1-score': 0.5969693410078702, 'support': 4262.0} | {'precision': 0.8070805541303232, 'recall': 0.7265588914549653, 'f1-score': 0.764705882352941, 'support': 2165.0} | {'precision': 0.9202486304256215, 'recall': 0.8851844345358735, 'f1-score': 0.9023760330578511, 'support': 9868.0} | {'precision': 0.8693739920832723, 'recall': 0.9095789554413682, 'f1-score': 0.8890221505940558, 'support': 13039.0} | 0.8423 | {'precision': 0.798611221118167, 'recall': 0.7793803122632605, 'f1-score': 0.7882683517531794, 'support': 29334.0} | {'precision': 0.8424246787445332, 'recall': 0.8423331287925274, 'f1-score': 0.8419062549424022, 'support': 29334.0} |
| 0.0034 | 44.0 | 3564 | 1.2523 | {'precision': 0.6167139540882125, 'recall': 0.5610042233693102, 'f1-score': 0.5875414670106893, 'support': 4262.0} | {'precision': 0.8153061224489796, 'recall': 0.7381062355658199, 'f1-score': 0.7747878787878788, 'support': 2165.0} | {'precision': 0.9169854233433268, 'recall': 0.8988650182407782, 'f1-score': 0.9078348088634154, 'support': 9868.0} | {'precision': 0.8653067129629629, 'recall': 0.9174016412301557, 'f1-score': 0.8905930089714477, 'support': 13039.0} | 0.8462 | {'precision': 0.8035780532108705, 'recall': 0.7788442796015159, 'f1-score': 0.7901892909083578, 'support': 29334.0} | {'precision': 0.8428826281892011, 'recall': 0.8461512238358219, 'f1-score': 0.8438151506040159, 'support': 29334.0} |
| 0.0034 | 45.0 | 3645 | 1.2569 | {'precision': 0.5956501403180543, 'recall': 0.5976067573908963, 'f1-score': 0.5966268446943078, 'support': 4262.0} | {'precision': 0.8109375, 'recall': 0.7191685912240184, 'f1-score': 0.7623011015911872, 'support': 2165.0} | {'precision': 0.9264893617021277, 'recall': 0.882549655451966, 'f1-score': 0.9039858833298734, 'support': 9868.0} | {'precision': 0.8643907410103363, 'recall': 0.9107293504103076, 'f1-score': 0.8869552227658065, 'support': 13039.0} | 0.8416 | {'precision': 0.7993669357576295, 'recall': 0.777513588619297, 'f1-score': 0.7874672630952938, 'support': 29334.0} | {'precision': 0.8422897824656003, 'recall': 0.8416172359719097, 'f1-score': 0.8413018116647781, 'support': 29334.0} |
| 0.0034 | 46.0 | 3726 | 1.2538 | {'precision': 0.5921505623135185, 'recall': 0.6053496011262318, 'f1-score': 0.5986773407587886, 'support': 4262.0} | {'precision': 0.8124022928608651, 'recall': 0.7200923787528868, 'f1-score': 0.7634671890303624, 'support': 2165.0} | {'precision': 0.9249020230907743, 'recall': 0.8848804215646534, 'f1-score': 0.9044487026775078, 'support': 9868.0} | {'precision': 0.8677388558419622, 'recall': 0.9062044635324795, 'f1-score': 0.8865546218487395, 'support': 13039.0} | 0.8416 | {'precision': 0.79929843352678, 'recall': 0.779131716244063, 'f1-score': 0.7882869635788495, 'support': 29334.0} | {'precision': 0.8428436887504975, 'recall': 0.8415831458375946, 'f1-score': 0.8416634213837886, 'support': 29334.0} |
| 0.0034 | 47.0 | 3807 | 1.2729 | {'precision': 0.5972959922742637, 'recall': 0.5804786485218207, 'f1-score': 0.5887672536887196, 'support': 4262.0} | {'precision': 0.8081907724209435, 'recall': 0.7200923787528868, 'f1-score': 0.7616023448949681, 'support': 2165.0} | {'precision': 0.9219409282700421, 'recall': 0.8856911228212404, 'f1-score': 0.9034525532354765, 'support': 9868.0} | {'precision': 0.8636000870637742, 'recall': 0.9128767543523276, 'f1-score': 0.8875549921706063, 'support': 13039.0} | 0.8412 | {'precision': 0.7977569450072559, 'recall': 0.7747847261120688, 'f1-score': 0.7853442859974425, 'support': 29334.0} | {'precision': 0.8404446429657594, 'recall': 0.8412081543601282, 'f1-score': 0.8401954881761488, 'support': 29334.0} |
| 0.0034 | 48.0 | 3888 | 1.2605 | {'precision': 0.5967088003815884, 'recall': 0.5870483341154388, 'f1-score': 0.5918391484328799, 'support': 4262.0} | {'precision': 0.8079877112135176, 'recall': 0.7288683602771363, 'f1-score': 0.7663914521612433, 'support': 2165.0} | {'precision': 0.9202300052273915, 'recall': 0.8919740575597892, 'f1-score': 0.9058817475428395, 'support': 9868.0} | {'precision': 0.8690449974308155, 'recall': 0.9079684024848531, 'f1-score': 0.8880804140724626, 'support': 13039.0} | 0.8427 | {'precision': 0.7984928785633282, 'recall': 0.7789647886093043, 'f1-score': 0.7880481905523563, 'support': 29334.0} | {'precision': 0.8421890541722198, 'recall': 0.842742210404309, 'f1-score': 0.8420460062860028, 'support': 29334.0} |
| 0.0034 | 49.0 | 3969 | 1.2654 | {'precision': 0.5976983936705826, 'recall': 0.5849366494603473, 'f1-score': 0.5912486659551762, 'support': 4262.0} | {'precision': 0.8090117767537123, 'recall': 0.7297921478060047, 'f1-score': 0.7673627974745022, 'support': 2165.0} | {'precision': 0.9196736743018513, 'recall': 0.8910620186461289, 'f1-score': 0.9051417983426837, 'support': 9868.0} | {'precision': 0.8682687376364568, 'recall': 0.9088887184600046, 'f1-score': 0.8881145083932854, 'support': 13039.0} | 0.8426 | {'precision': 0.7986631455906508, 'recall': 0.7786698835931214, 'f1-score': 0.787966942541412, 'support': 29334.0} | {'precision': 0.841876216627403, 'recall': 0.8426058498670485, 'f1-score': 0.8417981390815746, 'support': 29334.0} |
| 0.0031 | 50.0 | 4050 | 1.2704 | {'precision': 0.5972354623450906, 'recall': 0.5879868606288128, 'f1-score': 0.5925750768503193, 'support': 4262.0} | {'precision': 0.8091328886608518, 'recall': 0.7284064665127021, 'f1-score': 0.7666504618376278, 'support': 2165.0} | {'precision': 0.9211161229413616, 'recall': 0.8898459667612485, 'f1-score': 0.9052110715942477, 'support': 9868.0} | {'precision': 0.8676039835969537, 'recall': 0.9086586394662167, 'f1-score': 0.8876568645813823, 'support': 13039.0} | 0.8424 | {'precision': 0.7987721143860643, 'recall': 0.7787244833422451, 'f1-score': 0.7880233687158943, 'support': 29334.0} | {'precision': 0.8420076528182845, 'recall': 0.8424353991954728, 'f1-score': 0.8417581625139158, 'support': 29334.0} |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2