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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: bart-base-paraphrasing |
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results: [] |
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language: |
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- en |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bart-base-paraphrasing |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.309600 |
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- Rouge1: 37.346600 |
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- Rouge2: 31.232000 |
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- Rougel: 35.649300 |
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- Rougelsum: 36.620700 |
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- Gen Len: 20.0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 4e-05 |
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- train_batch_size: 27 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| 1.272100| 15| 1| 0.728453| 35.610300| 28.460200| 33.443200| 34.660100| 19.957500 | |
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| 0.828400| 30| 1| 0.672391| 35.944600| 29.183200| 33.994800| 35.159600| 19.961500 | |
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| 0.750400| 45| 1| 0.621431| 36.373600| 29.659600| 34.441700| 35.605300| 19.977000 | |
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| 0.728900| 60| 1| 0.597063| 36.034900| 29.380400| 34.177700| 35.257100| 19.970500 | |
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| 0.699800| 75| 1| 0.585529| 35.308700| 28.488400| 33.353300| 34.456300| 19.971500 | |
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| 0.698900| 90| 1| 0.560137| 35.956300| 29.453500| 34.155300| 35.154300| 19.970500 | |
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| 0.669100| 105| 1| 0.555273| 36.017400| 29.399500| 34.099400| 35.162900| 19.972500 | |
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| 0.637600| 120| 1| 0.551375| 36.357600| 29.783200| 34.549300| 35.561400| 19.976000 | |
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| 0.653500| 135| 1| 0.530873| 36.578900| 30.080800| 34.764800| 35.789300| 19.970000 | |
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| 0.597800| 150| 1| 0.528142| 36.219800| 29.791800| 34.459700| 35.407700| 19.974000 | |
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| 0.626600| 165| 1| 0.510571| 36.251200| 29.698900| 34.422100| 35.432400| 19.972500 | |
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| 0.585100| 180| 1| 0.504067| 36.191500| 29.743700| 34.408400| 35.401300| 19.969000 | |
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| 0.576700| 195| 1| 0.495318| 36.648900| 30.248700| 34.869300| 35.885300| 19.974000 | |
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| 0.549200| 210| 1| 0.494409| 36.392600| 30.035800| 34.577200| 35.623000| 19.972000 | |
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| 0.570000| 225| 1| 0.479456| 36.339100| 29.928200| 34.589300| 35.569900| 19.965500 | |
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| 0.550600| 240| 1| 0.473431| 36.646300| 30.312000| 34.851800| 35.861300| 19.964500 | |
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| 0.566200| 255| 1| 0.471991| 36.514700| 30.070500| 34.630700| 35.685000| 19.968500 | |
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| 0.539100| 270| 1| 0.459127| 36.328600| 29.984900| 34.568200| 35.487200| 19.968500 | |
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| 0.527300| 285| 1| 0.449097| 36.541300| 30.132600| 34.705300| 35.714000| 19.968500 | |
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| 0.521300| 300| 2| 0.448960| 35.926800| 29.508400| 34.115800| 35.147400| 19.973000 | |
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| 0.471900| 315| 2| 0.443209| 36.748400| 30.365400| 34.966500| 35.956900| 19.968500 | |
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| 0.499300| 330| 2| 0.439178| 36.783700| 30.461400| 35.037900| 36.023900| 19.968500 | |
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| 0.473100| 345| 2| 0.422886| 36.773600| 30.514500| 35.021000| 35.998200| 19.973500 | |
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| 0.459500| 360| 2| 0.422479| 37.235700| 30.945100| 35.394200| 36.474400| 19.970000 | |
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| 0.454900| 375| 2| 0.421957| 36.685800| 30.390300| 34.903800| 35.925700| 19.968500 | |
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| 0.456400| 390| 2| 0.427490| 36.233400| 29.811500| 34.441800| 35.424200| 19.971000 | |
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| 0.446300| 405| 2| 0.420770| 36.860900| 30.457600| 35.035000| 36.068700| 19.968500 | |
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| 0.462600| 420| 2| 0.421138| 36.468000| 29.979500| 34.586800| 35.633500| 19.971000 | |
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| 0.432000| 435| 2| 0.411133| 37.028300| 30.761300| 35.271100| 36.271500| 19.971500 | |
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| 0.470200| 450| 2| 0.411541| 36.740200| 30.499000| 34.988000| 35.977300| 19.968000 | |
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| 0.447200| 465| 2| 0.402041| 37.204600| 30.997600| 35.446300| 36.492300| 19.960500 | |
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| 0.461100| 480| 2| 0.409818| 36.912900| 30.706900| 35.156600| 36.150000| 19.966500 | |
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| 0.448500| 495| 2| 0.412397| 36.813800| 30.550000| 35.086000| 36.037500| 19.965000 | |
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| 0.440700| 510| 2| 0.409341| 36.976300| 30.703900| 35.230000| 36.203300| 19.968000 | |
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| 0.463100| 525| 2| 0.409853| 37.053500| 30.862000| 35.364300| 36.332600| 19.971000 | |
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| 0.460100| 540| 2| 0.405348| 36.580600| 30.349600| 34.859000| 35.823700| 19.966000 | |
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| 0.449700| 555| 2| 0.404055| 36.880000| 30.500300| 34.966900| 36.023600| 19.973500 | |
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| 0.445900| 570| 2| 0.401167| 37.105100| 30.894400| 35.349100| 36.337700| 19.969500 | |
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| 0.473600| 585| 2| 0.401274| 36.506000| 30.272000| 34.790700| 35.759000| 19.971000 | |
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| 0.435400| 600| 3| 0.404944| 37.093100| 30.850100| 35.391800| 36.369500| 19.971500 | |
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| 0.414500| 615| 3| 0.400146| 36.936300| 30.789200| 35.195400| 36.203700| 19.966500 | |
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| 0.395000| 630| 3| 0.400189| 37.110100| 30.915400| 35.420800| 36.338100| 19.966500 | |
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| 0.405000| 645| 3| 0.401724| 36.860300| 30.623400| 35.093600| 36.080900| 19.969500 | |
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| 0.403400| 660| 3| 0.405606| 36.777100| 30.546200| 35.065500| 36.000200| 19.969500 | |
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| 0.398700| 675| 3| 0.403438| 36.531700| 30.283400| 34.829400| 35.730400| 19.969500 | |
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| 0.398900| 690| 3| 0.396970| 36.871100| 30.672100| 35.157400| 36.047400| 19.970000 | |
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| 0.378900| 705| 3| 0.413375| 37.082500| 30.848200| 35.339000| 36.312200| 19.966000 | |
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| 0.391600| 720| 3| 0.395604| 37.091600| 30.925600| 35.404200| 36.360200| 19.969500 | |
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| 0.374400| 735| 3| 0.398041| 37.287600| 31.112700| 35.548900| 36.543700| 19.969000 | |
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| 0.390600| 750| 3| 0.399400| 37.050800| 30.844900| 35.278000| 36.281900| 19.969500 | |
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| 0.398800| 765| 3| 0.391213| 37.260900| 31.090300| 35.493200| 36.499800| 19.961500 | |
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| 0.391300| 780| 3| 0.392255| 37.062100| 30.859300| 35.327400| 36.311500| 19.968000 | |
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| 0.414400| 795| 3| 0.390236| 37.043600| 30.738100| 35.249800| 36.285500| 19.968000 | |
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| 0.369700| 810| 3| 0.390666| 36.889500| 30.710500| 35.129200| 36.129500| 19.968000 | |
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| 0.372800| 825| 3| 0.389744| 37.012200| 30.853800| 35.225400| 36.279300| 19.966000 | |
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| 0.380400| 840| 3| 0.389610| 36.834300| 30.671600| 35.048900| 36.063700| 19.966000 | |
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| 0.369000| 855| 3| 0.385031| 37.137800| 31.043000| 35.421100| 36.393500| 19.964500 | |
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| 0.386700| 870| 3| 0.394869| 36.993300| 30.773100| 35.204100| 36.215400| 19.966000 | |
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| 0.389100| 885| 3| 0.387872| 36.994300| 30.764100| 35.276000| 36.250300| 19.969500 | |
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| 0.381400| 900| 4| 0.384406| 37.118600| 30.899300| 35.351600| 36.380200| 19.969500 | |
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| 0.372500| 915| 4| 0.386666| 37.036800| 31.053500| 35.317800| 36.293100| 19.966000 | |
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| 0.351100| 930| 4| 0.390876| 36.950600| 30.806400| 35.247800| 36.190500| 19.963000 | |
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| 0.349200| 945| 4| 0.391693| 37.173400| 31.020000| 35.406700| 36.414900| 19.966000 | |
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| 0.350500| 960| 4| 0.383120| 37.257700| 31.094200| 35.502400| 36.498700| 19.966000 | |
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| 0.390000| 975| 4| 0.384534| 37.103900| 30.999200| 35.392100| 36.383800| 19.966000 | |
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| 0.343500| 990| 4| 0.384099| 37.074300| 30.941700| 35.361400| 36.334900| 19.969500 | |
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| 0.347800| 1005| 4| 0.387656| 37.011900| 30.834300| 35.252600| 36.246700| 19.968 | |
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| 0.359200| 1020| 4| 0.385008| 37.240300| 31.078300| 35.499300| 36.470500| 19.968 | |
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| 0.344100| 1035| 4| 0.384319| 37.118000| 31.010800| 35.419600| 36.401000| 19.966 | |
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| 0.344200| 1050| 4| 0.390927| 36.891900| 30.697800| 35.141600| 36.116600| 19.969 | |
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| 0.353900| 1065| 4| 0.384563| 36.790300| 30.613100| 35.060500| 36.012600| 19.969 | |
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| 0.354300| 1080| 4| 0.380220| 37.132800| 31.021100| 35.420000| 36.377800| 19.964 | |
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| 0.348800| 1095| 4| 0.381104| 37.158700| 31.000300| 35.437500| 36.430800| 19.961 | |
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| 0.349900| 1110| 4| 0.385718| 37.154600| 30.992800| 35.406500| 36.413500| 19.966 | |
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| 0.349200| 1125| 4| 0.382857| 37.023900| 30.929500| 35.318300| 36.293200| 19.970 | |
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| 0.351800| 1140| 4| 0.380331| 37.171800| 31.037000| 35.480200| 36.478400| 19.965 | |
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| 0.348700| 1155| 4| 0.384382| 37.249000| 31.114500| 35.577100| 36.544200| 19.970 | |
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| 0.325800| 1170| 4| 0.382947| 37.177400| 31.042000| 35.460600| 36.450300| 19.968 | |
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| 0.351700| 1185| 4| 0.379098| 37.160700| 30.966800| 35.463100| 36.449000| 19.969 | |
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| 0.329400| 1200| 5| 0.379832| 37.211700| 31.117400| 35.520400| 36.500100| 19.965 | |
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| 0.309000| 1215| 5| 0.383461| 37.303500| 31.183800| 35.599000| 36.614000| 19.970 | |
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| 0.321000| 1230| 5| 0.380275| 37.177500| 31.081100| 35.462400| 36.473800| 19.963 | |
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| 0.309200| 1245| 5| 0.381899| 37.235800| 31.197100| 35.568800| 36.528000| 19.966 | |
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| 0.326700| 1260| 5| 0.381356| 37.410200| 31.257300| 35.671300| 36.697000| 19.969 | |
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| 0.324700| 1275| 5| 0.378781| 37.407900| 31.322100| 35.681000| 36.683100| 19.965 | |
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| 0.303200| 1290| 5| 0.381087| 37.355700| 31.308400| 35.665500| 36.628000| 19.965 | |
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| 0.335000| 1305| 5| 0.380627| 37.274800| 31.243800| 35.603400| 36.559800| 19.966 | |
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| 0.349300| 1320| 5| 0.376487| 37.299100| 31.221000| 35.611200| 36.573400| 19.963 | |
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| 0.302400| 1335| 5| 0.380785| 37.333500| 31.293000| 35.679900| 36.650200| 19.966 | |
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| 0.309400| 1350| 5| 0.381105| 37.280400| 31.195800| 35.611700| 36.565100| 19.969 | |
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| 0.322900| 1365| 5| 0.379658| 37.368200| 31.276900| 35.680000| 36.654900| 19.969 | |
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| 0.334700| 1380| 5| 0.381676| 37.362700| 31.288900| 35.680600| 36.643600| 19.968 | |
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| 0.323700| 1395| 5| 0.379920| 37.312300| 31.204800| 35.614800| 36.583400| 19.968 | |
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| 0.334700| 1410| 5| 0.379366| 37.310300| 31.205600| 35.636400| 36.595200| 19.969 | |
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| 0.327300| 1425| 5| 0.378289| 37.275400| 31.172700| 35.575500| 36.549500| 19.969 | |
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| 0.326400| 1440| 5| 0.378255| 37.270000| 31.164000| 35.582100| 36.543800| 19.969 | |
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| 0.326600| 1455| 5| 0.377739| 37.300000| 31.205400| 35.621500| 36.586100| 19.969 | |
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| 0.335700| 1470| 5| 0.377524| 37.287400| 31.189800| 35.608700| 36.578000| 19.970 | |
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| 0.309600| 1485| 5| 0.377617| 37.346600| 31.232000| 35.649300| 36.620700| 19.969 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
