--- license: mit tags: - generated_from_trainer base_model: microsoft/mdeberta-v3-base model-index: - name: mdeberta_all results: [] --- # mdeberta_all This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.2148 - Aerospacemanufacturer Precision: 0.7073 - Aerospacemanufacturer Recall: 0.8406 - Aerospacemanufacturer F1: 0.7682 - Aerospacemanufacturer Number: 138 - Anatomicalstructure Precision: 0.6762 - Anatomicalstructure Recall: 0.7269 - Anatomicalstructure F1: 0.7006 - Anatomicalstructure Number: 227 - Artwork Precision: 0.5802 - Artwork Recall: 0.5802 - Artwork F1: 0.5802 - Artwork Number: 131 - Artist Precision: 0.7565 - Artist Recall: 0.7938 - Artist F1: 0.7747 - Artist Number: 1722 - Athlete Precision: 0.7195 - Athlete Recall: 0.7636 - Athlete F1: 0.7409 - Athlete Number: 719 - Carmanufacturer Precision: 0.6806 - Carmanufacturer Recall: 0.8176 - Carmanufacturer F1: 0.7429 - Carmanufacturer Number: 159 - Cleric Precision: 0.6867 - Cleric Recall: 0.5124 - Cleric F1: 0.5869 - Cleric Number: 201 - Clothing Precision: 0.5797 - Clothing Recall: 0.625 - Clothing F1: 0.6015 - Clothing Number: 128 - Disease Precision: 0.6262 - Disease Recall: 0.6768 - Disease F1: 0.6505 - Disease Number: 198 - Drink Precision: 0.7296 - Drink Recall: 0.8112 - Drink F1: 0.7682 - Drink Number: 143 - Facility Precision: 0.6439 - Facility Recall: 0.7203 - Facility F1: 0.6800 - Facility Number: 497 - Food Precision: 0.6786 - Food Recall: 0.5327 - Food F1: 0.5969 - Food Number: 214 - Humansettlement Precision: 0.8594 - Humansettlement Recall: 0.8792 - Humansettlement F1: 0.8692 - Humansettlement Number: 1689 - Medicalprocedure Precision: 0.6545 - Medicalprocedure Recall: 0.7606 - Medicalprocedure F1: 0.7036 - Medicalprocedure Number: 142 - Medication/vaccine Precision: 0.7183 - Medication/vaccine Recall: 0.765 - Medication/vaccine F1: 0.7409 - Medication/vaccine Number: 200 - Musicalgrp Precision: 0.7132 - Musicalgrp Recall: 0.7688 - Musicalgrp F1: 0.7400 - Musicalgrp Number: 372 - Musicalwork Precision: 0.7513 - Musicalwork Recall: 0.7052 - Musicalwork F1: 0.7275 - Musicalwork Number: 407 - Org Precision: 0.6335 - Org Recall: 0.6117 - Org F1: 0.6224 - Org Number: 667 - Otherloc Precision: 0.7514 - Otherloc Recall: 0.6205 - Otherloc F1: 0.6797 - Otherloc Number: 224 - Otherper Precision: 0.4558 - Otherper Recall: 0.5821 - Otherper F1: 0.5112 - Otherper Number: 859 - Otherprod Precision: 0.6076 - Otherprod Recall: 0.5543 - Otherprod F1: 0.5797 - Otherprod Number: 433 - Politician Precision: 0.6228 - Politician Recall: 0.4793 - Politician F1: 0.5417 - Politician Number: 603 - Privatecorp Precision: 0.7159 - Privatecorp Recall: 0.4884 - Privatecorp F1: 0.5806 - Privatecorp Number: 129 - Publiccorp Precision: 0.56 - Publiccorp Recall: 0.6914 - Publiccorp F1: 0.6188 - Publiccorp Number: 243 - Scientist Precision: 0.4545 - Scientist Recall: 0.4497 - Scientist F1: 0.4521 - Scientist Number: 189 - Software Precision: 0.7159 - Software Recall: 0.8046 - Software F1: 0.7577 - Software Number: 307 - Sportsgrp Precision: 0.7845 - Sportsgrp Recall: 0.8701 - Sportsgrp F1: 0.8251 - Sportsgrp Number: 385 - Sportsmanager Precision: 0.6667 - Sportsmanager Recall: 0.5361 - Sportsmanager F1: 0.5943 - Sportsmanager Number: 194 - Station Precision: 0.7406 - Station Recall: 0.8093 - Station F1: 0.7734 - Station Number: 194 - Symptom Precision: 0.6316 - Symptom Recall: 0.5581 - Symptom F1: 0.5926 - Symptom Number: 129 - Vehicle Precision: 0.5514 - Vehicle Recall: 0.6505 - Vehicle F1: 0.5969 - Vehicle Number: 206 - Visualwork Precision: 0.7538 - Visualwork Recall: 0.7951 - Visualwork F1: 0.7739 - Visualwork Number: 693 - Writtenwork Precision: 0.6913 - Writtenwork Recall: 0.6803 - Writtenwork F1: 0.6858 - Writtenwork Number: 563 - Overall Precision: 0.6928 - Overall Recall: 0.7142 - Overall F1: 0.7033 - Overall Accuracy: 0.9355 ## 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: 1e-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: 15.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Aerospacemanufacturer Precision | Aerospacemanufacturer Recall | Aerospacemanufacturer F1 | Aerospacemanufacturer Number | Anatomicalstructure Precision | Anatomicalstructure Recall | Anatomicalstructure F1 | Anatomicalstructure Number | Artwork Precision | Artwork Recall | Artwork F1 | Artwork Number | Artist Precision | Artist Recall | Artist F1 | Artist Number | Athlete Precision | Athlete Recall | Athlete F1 | Athlete Number | Carmanufacturer Precision | Carmanufacturer Recall | Carmanufacturer F1 | Carmanufacturer Number | Cleric Precision | Cleric Recall | Cleric F1 | Cleric Number | Clothing Precision | Clothing Recall | Clothing F1 | Clothing Number | Disease Precision | Disease Recall | Disease F1 | Disease Number | Drink Precision | Drink Recall | Drink F1 | Drink Number | Facility Precision | Facility Recall | Facility F1 | Facility Number | Food Precision | Food Recall | Food F1 | Food Number | Humansettlement Precision | Humansettlement Recall | Humansettlement F1 | Humansettlement Number | Medicalprocedure Precision | Medicalprocedure Recall | Medicalprocedure F1 | Medicalprocedure Number | Medication/vaccine Precision | Medication/vaccine Recall | Medication/vaccine F1 | Medication/vaccine Number | Musicalgrp Precision | Musicalgrp Recall | Musicalgrp F1 | Musicalgrp Number | Musicalwork Precision | Musicalwork Recall | Musicalwork F1 | Musicalwork Number | Org Precision | Org Recall | Org F1 | Org Number | Otherloc Precision | Otherloc Recall | Otherloc F1 | Otherloc Number | Otherper Precision | Otherper Recall | Otherper F1 | Otherper Number | Otherprod Precision | Otherprod Recall | Otherprod F1 | Otherprod Number | Politician Precision | Politician Recall | Politician F1 | Politician Number | Privatecorp Precision | Privatecorp Recall | Privatecorp F1 | Privatecorp Number | Publiccorp Precision | Publiccorp Recall | Publiccorp F1 | Publiccorp Number | Scientist Precision | Scientist Recall | Scientist F1 | Scientist Number | Software Precision | Software Recall | Software F1 | Software Number | Sportsgrp Precision | Sportsgrp Recall | Sportsgrp F1 | Sportsgrp Number | Sportsmanager Precision | Sportsmanager Recall | Sportsmanager F1 | Sportsmanager Number | Station Precision | Station Recall | Station F1 | Station Number | Symptom Precision | Symptom Recall | Symptom F1 | Symptom Number | Vehicle Precision | Vehicle Recall | Vehicle F1 | Vehicle Number | Visualwork Precision | Visualwork Recall | Visualwork F1 | Visualwork Number | Writtenwork Precision | Writtenwork Recall | Writtenwork F1 | Writtenwork Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | |:-------------:|:-----:|:------:|:---------------:|:-------------------------------:|:----------------------------:|:------------------------:|:----------------------------:|:-----------------------------:|:--------------------------:|:----------------------:|:--------------------------:|:-----------------:|:--------------:|:----------:|:--------------:|:----------------:|:-------------:|:---------:|:-------------:|:-----------------:|:--------------:|:----------:|:--------------:|:-------------------------:|:----------------------:|:------------------:|:----------------------:|:----------------:|:-------------:|:---------:|:-------------:|:------------------:|:---------------:|:-----------:|:---------------:|:-----------------:|:--------------:|:----------:|:--------------:|:---------------:|:------------:|:--------:|:------------:|:------------------:|:---------------:|:-----------:|:---------------:|:--------------:|:-----------:|:-------:|:-----------:|:-------------------------:|:----------------------:|:------------------:|:----------------------:|:--------------------------:|:-----------------------:|:-------------------:|:-----------------------:|:----------------------------:|:-------------------------:|:---------------------:|:-------------------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:---------------------:|:------------------:|:--------------:|:------------------:|:-------------:|:----------:|:------:|:----------:|:------------------:|:---------------:|:-----------:|:---------------:|:------------------:|:---------------:|:-----------:|:---------------:|:-------------------:|:----------------:|:------------:|:----------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:---------------------:|:------------------:|:--------------:|:------------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:-------------------:|:----------------:|:------------:|:----------------:|:------------------:|:---------------:|:-----------:|:---------------:|:-------------------:|:----------------:|:------------:|:----------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:-----------------:|:--------------:|:----------:|:--------------:|:-----------------:|:--------------:|:----------:|:--------------:|:-----------------:|:--------------:|:----------:|:--------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:---------------------:|:------------------:|:--------------:|:------------------:|:-----------------:|:--------------:|:----------:|:----------------:| | 0.2881 | 1.0 | 21353 | 0.2534 | 0.5191 | 0.6884 | 0.5919 | 138 | 0.5693 | 0.6872 | 0.6228 | 227 | 0.4366 | 0.4733 | 0.4542 | 131 | 0.7109 | 0.8055 | 0.7552 | 1722 | 0.6782 | 0.6801 | 0.6792 | 719 | 0.6552 | 0.7170 | 0.6847 | 159 | 0.4874 | 0.4826 | 0.485 | 201 | 0.4639 | 0.6016 | 0.5238 | 128 | 0.4799 | 0.7222 | 0.5766 | 198 | 0.55 | 0.6923 | 0.6130 | 143 | 0.5305 | 0.6640 | 0.5898 | 497 | 0.4042 | 0.7196 | 0.5176 | 214 | 0.8164 | 0.8792 | 0.8466 | 1689 | 0.5799 | 0.6901 | 0.6302 | 142 | 0.5945 | 0.755 | 0.6652 | 200 | 0.7445 | 0.6425 | 0.6898 | 372 | 0.6667 | 0.6634 | 0.6650 | 407 | 0.5585 | 0.5652 | 0.5618 | 667 | 0.6724 | 0.5223 | 0.5879 | 224 | 0.3835 | 0.4773 | 0.4253 | 859 | 0.5237 | 0.4596 | 0.4895 | 433 | 0.5176 | 0.4643 | 0.4895 | 603 | 0.4688 | 0.1163 | 0.1863 | 129 | 0.4207 | 0.6008 | 0.4949 | 243 | 0.4099 | 0.3492 | 0.3771 | 189 | 0.6686 | 0.7362 | 0.7008 | 307 | 0.7688 | 0.7948 | 0.7816 | 385 | 0.5136 | 0.5825 | 0.5459 | 194 | 0.6667 | 0.8041 | 0.7290 | 194 | 0.5588 | 0.1473 | 0.2331 | 129 | 0.4910 | 0.5291 | 0.5093 | 206 | 0.6662 | 0.7489 | 0.7052 | 693 | 0.6180 | 0.5861 | 0.6016 | 563 | 0.6136 | 0.6640 | 0.6378 | 0.9220 | | 0.2195 | 2.0 | 42706 | 0.2288 | 0.6409 | 0.8406 | 0.7273 | 138 | 0.6908 | 0.6300 | 0.6590 | 227 | 0.5625 | 0.5496 | 0.5560 | 131 | 0.7336 | 0.8124 | 0.7710 | 1722 | 0.6466 | 0.8067 | 0.7178 | 719 | 0.6095 | 0.8050 | 0.6938 | 159 | 0.5848 | 0.4975 | 0.5376 | 201 | 0.5260 | 0.6328 | 0.5745 | 128 | 0.5427 | 0.6414 | 0.5880 | 198 | 0.7042 | 0.6993 | 0.7018 | 143 | 0.6157 | 0.7123 | 0.6604 | 497 | 0.6140 | 0.4907 | 0.5455 | 214 | 0.8454 | 0.8745 | 0.8597 | 1689 | 0.6125 | 0.6901 | 0.6490 | 142 | 0.6898 | 0.745 | 0.7163 | 200 | 0.7299 | 0.7339 | 0.7319 | 372 | 0.6901 | 0.7224 | 0.7059 | 407 | 0.6224 | 0.5907 | 0.6062 | 667 | 0.7312 | 0.6071 | 0.6634 | 224 | 0.4851 | 0.4750 | 0.4800 | 859 | 0.5994 | 0.4804 | 0.5333 | 433 | 0.5675 | 0.5091 | 0.5367 | 603 | 0.6905 | 0.4496 | 0.5446 | 129 | 0.5516 | 0.6379 | 0.5916 | 243 | 0.4570 | 0.3651 | 0.4059 | 189 | 0.7508 | 0.7459 | 0.7484 | 307 | 0.7833 | 0.8260 | 0.8040 | 385 | 0.7071 | 0.5103 | 0.5928 | 194 | 0.6920 | 0.7990 | 0.7416 | 194 | 0.4590 | 0.4341 | 0.4462 | 129 | 0.4717 | 0.7282 | 0.5725 | 206 | 0.7275 | 0.7821 | 0.7538 | 693 | 0.6618 | 0.6430 | 0.6523 | 563 | 0.6711 | 0.6946 | 0.6827 | 0.9317 | | 0.1965 | 3.0 | 64059 | 0.2148 | 0.7073 | 0.8406 | 0.7682 | 138 | 0.6762 | 0.7269 | 0.7006 | 227 | 0.5802 | 0.5802 | 0.5802 | 131 | 0.7565 | 0.7938 | 0.7747 | 1722 | 0.7195 | 0.7636 | 0.7409 | 719 | 0.6806 | 0.8176 | 0.7429 | 159 | 0.6867 | 0.5124 | 0.5869 | 201 | 0.5797 | 0.625 | 0.6015 | 128 | 0.6262 | 0.6768 | 0.6505 | 198 | 0.7296 | 0.8112 | 0.7682 | 143 | 0.6439 | 0.7203 | 0.6800 | 497 | 0.6786 | 0.5327 | 0.5969 | 214 | 0.8594 | 0.8792 | 0.8692 | 1689 | 0.6545 | 0.7606 | 0.7036 | 142 | 0.7183 | 0.765 | 0.7409 | 200 | 0.7132 | 0.7688 | 0.7400 | 372 | 0.7513 | 0.7052 | 0.7275 | 407 | 0.6335 | 0.6117 | 0.6224 | 667 | 0.7514 | 0.6205 | 0.6797 | 224 | 0.4558 | 0.5821 | 0.5112 | 859 | 0.6076 | 0.5543 | 0.5797 | 433 | 0.6228 | 0.4793 | 0.5417 | 603 | 0.7159 | 0.4884 | 0.5806 | 129 | 0.56 | 0.6914 | 0.6188 | 243 | 0.4545 | 0.4497 | 0.4521 | 189 | 0.7159 | 0.8046 | 0.7577 | 307 | 0.7845 | 0.8701 | 0.8251 | 385 | 0.6667 | 0.5361 | 0.5943 | 194 | 0.7406 | 0.8093 | 0.7734 | 194 | 0.6316 | 0.5581 | 0.5926 | 129 | 0.5514 | 0.6505 | 0.5969 | 206 | 0.7538 | 0.7951 | 0.7739 | 693 | 0.6913 | 0.6803 | 0.6858 | 563 | 0.6928 | 0.7142 | 0.7033 | 0.9355 | | 0.1665 | 4.0 | 85412 | 0.2193 | 0.7917 | 0.8261 | 0.8085 | 138 | 0.7069 | 0.7225 | 0.7146 | 227 | 0.5867 | 0.6718 | 0.6263 | 131 | 0.7710 | 0.7938 | 0.7823 | 1722 | 0.6962 | 0.7650 | 0.7290 | 719 | 0.7904 | 0.8302 | 0.8098 | 159 | 0.6221 | 0.5323 | 0.5737 | 201 | 0.5743 | 0.6641 | 0.6159 | 128 | 0.5966 | 0.7172 | 0.6514 | 198 | 0.7914 | 0.7692 | 0.7801 | 143 | 0.6395 | 0.7103 | 0.6730 | 497 | 0.6422 | 0.6121 | 0.6268 | 214 | 0.8338 | 0.9059 | 0.8683 | 1689 | 0.6711 | 0.7183 | 0.6939 | 142 | 0.7635 | 0.775 | 0.7692 | 200 | 0.7669 | 0.7608 | 0.7638 | 372 | 0.6872 | 0.7936 | 0.7366 | 407 | 0.7100 | 0.5982 | 0.6493 | 667 | 0.7181 | 0.7277 | 0.7228 | 224 | 0.4765 | 0.5553 | 0.5129 | 859 | 0.6225 | 0.5866 | 0.6040 | 433 | 0.6078 | 0.5191 | 0.5599 | 603 | 0.7222 | 0.5039 | 0.5936 | 129 | 0.6065 | 0.7737 | 0.6799 | 243 | 0.4783 | 0.5238 | 0.5 | 189 | 0.7313 | 0.7980 | 0.7632 | 307 | 0.8401 | 0.8597 | 0.8498 | 385 | 0.6058 | 0.6495 | 0.6269 | 194 | 0.7512 | 0.7938 | 0.7719 | 194 | 0.6983 | 0.6279 | 0.6612 | 129 | 0.5804 | 0.7184 | 0.6421 | 206 | 0.7571 | 0.8052 | 0.7804 | 693 | 0.6916 | 0.6892 | 0.6904 | 563 | 0.7012 | 0.7309 | 0.7158 | 0.9375 | | 0.1314 | 5.0 | 106765 | 0.2272 | 0.7707 | 0.8768 | 0.8203 | 138 | 0.7137 | 0.7577 | 0.7350 | 227 | 0.6058 | 0.6336 | 0.6194 | 131 | 0.7229 | 0.8513 | 0.7819 | 1722 | 0.7361 | 0.7761 | 0.7556 | 719 | 0.6839 | 0.8302 | 0.7500 | 159 | 0.5845 | 0.6020 | 0.5931 | 201 | 0.6148 | 0.6484 | 0.6312 | 128 | 0.6121 | 0.7172 | 0.6605 | 198 | 0.6970 | 0.8042 | 0.7468 | 143 | 0.6438 | 0.6982 | 0.6699 | 497 | 0.6197 | 0.6776 | 0.6473 | 214 | 0.8390 | 0.8887 | 0.8631 | 1689 | 0.7333 | 0.6972 | 0.7148 | 142 | 0.7443 | 0.815 | 0.7780 | 200 | 0.7217 | 0.7876 | 0.7532 | 372 | 0.7113 | 0.7568 | 0.7333 | 407 | 0.6682 | 0.6522 | 0.6601 | 667 | 0.7136 | 0.7009 | 0.7072 | 224 | 0.5351 | 0.4796 | 0.5058 | 859 | 0.5930 | 0.6259 | 0.6090 | 433 | 0.6112 | 0.5240 | 0.5643 | 603 | 0.7767 | 0.6202 | 0.6897 | 129 | 0.6254 | 0.7284 | 0.6730 | 243 | 0.4815 | 0.4815 | 0.4815 | 189 | 0.7654 | 0.8078 | 0.7861 | 307 | 0.7611 | 0.8935 | 0.8220 | 385 | 0.6667 | 0.6082 | 0.6361 | 194 | 0.7828 | 0.7990 | 0.7908 | 194 | 0.6692 | 0.6899 | 0.6794 | 129 | 0.5983 | 0.6942 | 0.6427 | 206 | 0.7584 | 0.8153 | 0.7858 | 693 | 0.6740 | 0.7052 | 0.6892 | 563 | 0.7006 | 0.7401 | 0.7198 | 0.9378 | | 0.1224 | 6.0 | 128118 | 0.2275 | 0.8286 | 0.8406 | 0.8345 | 138 | 0.6898 | 0.7445 | 0.7161 | 227 | 0.6013 | 0.7252 | 0.6574 | 131 | 0.7574 | 0.8415 | 0.7972 | 1722 | 0.7400 | 0.7483 | 0.7441 | 719 | 0.8084 | 0.8491 | 0.8282 | 159 | 0.7055 | 0.5721 | 0.6319 | 201 | 0.6061 | 0.625 | 0.6154 | 128 | 0.7090 | 0.6768 | 0.6925 | 198 | 0.7868 | 0.7483 | 0.7670 | 143 | 0.6454 | 0.7545 | 0.6957 | 497 | 0.6287 | 0.6963 | 0.6608 | 214 | 0.8548 | 0.8851 | 0.8697 | 1689 | 0.7669 | 0.7183 | 0.7418 | 142 | 0.75 | 0.825 | 0.7857 | 200 | 0.7130 | 0.8280 | 0.7662 | 372 | 0.6848 | 0.8059 | 0.7404 | 407 | 0.7112 | 0.6462 | 0.6771 | 667 | 0.7879 | 0.6964 | 0.7393 | 224 | 0.5378 | 0.5378 | 0.5378 | 859 | 0.6554 | 0.5797 | 0.6152 | 433 | 0.5946 | 0.5887 | 0.5917 | 603 | 0.8131 | 0.6744 | 0.7373 | 129 | 0.6483 | 0.7737 | 0.7054 | 243 | 0.5537 | 0.5185 | 0.5355 | 189 | 0.7704 | 0.7980 | 0.784 | 307 | 0.8415 | 0.8961 | 0.8679 | 385 | 0.6566 | 0.6701 | 0.6633 | 194 | 0.7879 | 0.8041 | 0.7959 | 194 | 0.6159 | 0.7829 | 0.6894 | 129 | 0.5887 | 0.7087 | 0.6432 | 206 | 0.7864 | 0.8023 | 0.7943 | 693 | 0.7388 | 0.6732 | 0.7045 | 563 | 0.7221 | 0.7475 | 0.7346 | 0.9406 | | 0.0964 | 7.0 | 149471 | 0.2456 | 0.7947 | 0.8696 | 0.8304 | 138 | 0.7107 | 0.7577 | 0.7335 | 227 | 0.6522 | 0.6870 | 0.6691 | 131 | 0.7780 | 0.8182 | 0.7976 | 1722 | 0.7546 | 0.7483 | 0.7514 | 719 | 0.7870 | 0.8365 | 0.8110 | 159 | 0.6020 | 0.6020 | 0.6020 | 201 | 0.58 | 0.6797 | 0.6259 | 128 | 0.6129 | 0.7677 | 0.6816 | 198 | 0.7468 | 0.8252 | 0.7841 | 143 | 0.6642 | 0.7284 | 0.6948 | 497 | 0.6840 | 0.6776 | 0.6808 | 214 | 0.8586 | 0.8810 | 0.8697 | 1689 | 0.7836 | 0.7394 | 0.7609 | 142 | 0.7082 | 0.825 | 0.7621 | 200 | 0.7731 | 0.7876 | 0.7803 | 372 | 0.7606 | 0.7494 | 0.7550 | 407 | 0.6726 | 0.6837 | 0.6781 | 667 | 0.7581 | 0.7277 | 0.7426 | 224 | 0.5176 | 0.5634 | 0.5396 | 859 | 0.6599 | 0.6005 | 0.6288 | 433 | 0.5938 | 0.5672 | 0.5802 | 603 | 0.8776 | 0.6667 | 0.7577 | 129 | 0.7198 | 0.7613 | 0.74 | 243 | 0.5078 | 0.5185 | 0.5131 | 189 | 0.7933 | 0.7752 | 0.7842 | 307 | 0.8033 | 0.8909 | 0.8448 | 385 | 0.6071 | 0.7010 | 0.6507 | 194 | 0.7429 | 0.8041 | 0.7723 | 194 | 0.7321 | 0.6357 | 0.6805 | 129 | 0.5775 | 0.7233 | 0.6422 | 206 | 0.7858 | 0.7994 | 0.7926 | 693 | 0.6678 | 0.7282 | 0.6967 | 563 | 0.7199 | 0.7475 | 0.7334 | 0.9403 | | 0.0838 | 8.0 | 170824 | 0.2562 | 0.7722 | 0.8841 | 0.8243 | 138 | 0.6929 | 0.7753 | 0.7318 | 227 | 0.6483 | 0.7176 | 0.6812 | 131 | 0.7859 | 0.8101 | 0.7978 | 1722 | 0.7419 | 0.7316 | 0.7367 | 719 | 0.7389 | 0.8365 | 0.7847 | 159 | 0.5797 | 0.5970 | 0.5882 | 201 | 0.5878 | 0.6797 | 0.6304 | 128 | 0.6574 | 0.7172 | 0.6860 | 198 | 0.7597 | 0.8182 | 0.7879 | 143 | 0.7108 | 0.7123 | 0.7116 | 497 | 0.6511 | 0.7150 | 0.6815 | 214 | 0.8791 | 0.8822 | 0.8806 | 1689 | 0.75 | 0.7606 | 0.7552 | 142 | 0.7594 | 0.805 | 0.7816 | 200 | 0.7842 | 0.8011 | 0.7926 | 372 | 0.7395 | 0.7813 | 0.7599 | 407 | 0.6965 | 0.6777 | 0.6869 | 667 | 0.7179 | 0.75 | 0.7336 | 224 | 0.5081 | 0.5809 | 0.5421 | 859 | 0.6327 | 0.6166 | 0.6246 | 433 | 0.6094 | 0.5821 | 0.5954 | 603 | 0.8776 | 0.6667 | 0.7577 | 129 | 0.7059 | 0.7407 | 0.7229 | 243 | 0.5444 | 0.5185 | 0.5312 | 189 | 0.7722 | 0.7948 | 0.7833 | 307 | 0.8067 | 0.8779 | 0.8408 | 385 | 0.6408 | 0.6804 | 0.6600 | 194 | 0.7546 | 0.8402 | 0.7951 | 194 | 0.6831 | 0.7519 | 0.7159 | 129 | 0.6255 | 0.7136 | 0.6667 | 206 | 0.7392 | 0.8427 | 0.7876 | 693 | 0.7289 | 0.7069 | 0.7178 | 563 | 0.7242 | 0.7514 | 0.7376 | 0.9414 | | 0.0753 | 9.0 | 192177 | 0.2708 | 0.8026 | 0.8841 | 0.8414 | 138 | 0.7054 | 0.8018 | 0.7505 | 227 | 0.6277 | 0.6565 | 0.6418 | 131 | 0.7762 | 0.8380 | 0.8059 | 1722 | 0.7552 | 0.7552 | 0.7552 | 719 | 0.7701 | 0.8428 | 0.8048 | 159 | 0.6610 | 0.5821 | 0.6190 | 201 | 0.5915 | 0.6562 | 0.6222 | 128 | 0.6575 | 0.7273 | 0.6906 | 198 | 0.7887 | 0.7832 | 0.7860 | 143 | 0.7050 | 0.7163 | 0.7106 | 497 | 0.6270 | 0.7383 | 0.6781 | 214 | 0.8441 | 0.8881 | 0.8656 | 1689 | 0.7589 | 0.7535 | 0.7562 | 142 | 0.7125 | 0.855 | 0.7773 | 200 | 0.755 | 0.8118 | 0.7824 | 372 | 0.7512 | 0.8010 | 0.7753 | 407 | 0.6788 | 0.6972 | 0.6879 | 667 | 0.7830 | 0.7411 | 0.7615 | 224 | 0.5155 | 0.5821 | 0.5467 | 859 | 0.6386 | 0.6490 | 0.6438 | 433 | 0.6629 | 0.5804 | 0.6189 | 603 | 0.8598 | 0.7132 | 0.7797 | 129 | 0.6667 | 0.7490 | 0.7054 | 243 | 0.4787 | 0.5344 | 0.505 | 189 | 0.7610 | 0.7883 | 0.7744 | 307 | 0.8285 | 0.8909 | 0.8586 | 385 | 0.7027 | 0.6701 | 0.6860 | 194 | 0.7778 | 0.8299 | 0.8030 | 194 | 0.6923 | 0.7674 | 0.7279 | 129 | 0.6396 | 0.6893 | 0.6636 | 206 | 0.7879 | 0.8095 | 0.7986 | 693 | 0.7110 | 0.7123 | 0.7116 | 563 | 0.7258 | 0.7593 | 0.7422 | 0.9424 | | 0.0574 | 10.0 | 213530 | 0.2862 | 0.8 | 0.8986 | 0.8464 | 138 | 0.7375 | 0.7797 | 0.7580 | 227 | 0.6471 | 0.6718 | 0.6592 | 131 | 0.7831 | 0.8008 | 0.7918 | 1722 | 0.6997 | 0.7747 | 0.7353 | 719 | 0.7714 | 0.8491 | 0.8084 | 159 | 0.6091 | 0.5970 | 0.6030 | 201 | 0.6357 | 0.6406 | 0.6381 | 128 | 0.7 | 0.7071 | 0.7035 | 198 | 0.7436 | 0.8112 | 0.7759 | 143 | 0.6729 | 0.7243 | 0.6977 | 497 | 0.6830 | 0.7150 | 0.6986 | 214 | 0.8627 | 0.8857 | 0.8741 | 1689 | 0.7483 | 0.7535 | 0.7509 | 142 | 0.7611 | 0.86 | 0.8075 | 200 | 0.7846 | 0.8226 | 0.8031 | 372 | 0.7640 | 0.7715 | 0.7677 | 407 | 0.6921 | 0.6942 | 0.6931 | 667 | 0.7478 | 0.7545 | 0.7511 | 224 | 0.5079 | 0.5960 | 0.5485 | 859 | 0.6457 | 0.6397 | 0.6427 | 433 | 0.6223 | 0.5821 | 0.6015 | 603 | 0.8704 | 0.7287 | 0.7932 | 129 | 0.7041 | 0.7737 | 0.7373 | 243 | 0.5073 | 0.5503 | 0.5279 | 189 | 0.7680 | 0.7980 | 0.7827 | 307 | 0.8658 | 0.8883 | 0.8769 | 385 | 0.7111 | 0.6598 | 0.6845 | 194 | 0.7681 | 0.8196 | 0.7930 | 194 | 0.7197 | 0.7364 | 0.7280 | 129 | 0.6192 | 0.7184 | 0.6652 | 206 | 0.7922 | 0.8196 | 0.8057 | 693 | 0.7206 | 0.7194 | 0.72 | 563 | 0.7282 | 0.7572 | 0.7424 | 0.9424 | | 0.0568 | 11.0 | 234883 | 0.2951 | 0.8026 | 0.8841 | 0.8414 | 138 | 0.7458 | 0.7753 | 0.7603 | 227 | 0.6241 | 0.6718 | 0.6471 | 131 | 0.7737 | 0.8240 | 0.7981 | 1722 | 0.7646 | 0.7455 | 0.7549 | 719 | 0.8121 | 0.8428 | 0.8272 | 159 | 0.6685 | 0.5920 | 0.6280 | 201 | 0.6870 | 0.6172 | 0.6502 | 128 | 0.7150 | 0.6970 | 0.7059 | 198 | 0.7872 | 0.7762 | 0.7817 | 143 | 0.6631 | 0.7485 | 0.7032 | 497 | 0.6842 | 0.6682 | 0.6761 | 214 | 0.8594 | 0.8828 | 0.8709 | 1689 | 0.7863 | 0.7254 | 0.7546 | 142 | 0.7824 | 0.845 | 0.8125 | 200 | 0.7628 | 0.8038 | 0.7827 | 372 | 0.7664 | 0.7740 | 0.7702 | 407 | 0.7232 | 0.6777 | 0.6997 | 667 | 0.7820 | 0.7366 | 0.7586 | 224 | 0.5362 | 0.5949 | 0.5640 | 859 | 0.6306 | 0.6467 | 0.6385 | 433 | 0.6472 | 0.5871 | 0.6157 | 603 | 0.8857 | 0.7209 | 0.7949 | 129 | 0.7138 | 0.7901 | 0.7500 | 243 | 0.5075 | 0.5397 | 0.5231 | 189 | 0.7834 | 0.8013 | 0.7923 | 307 | 0.8561 | 0.8961 | 0.8756 | 385 | 0.6809 | 0.6598 | 0.6702 | 194 | 0.7656 | 0.8247 | 0.7940 | 194 | 0.6736 | 0.7519 | 0.7106 | 129 | 0.6262 | 0.6505 | 0.6381 | 206 | 0.7892 | 0.8211 | 0.8048 | 693 | 0.7561 | 0.7105 | 0.7326 | 563 | 0.7390 | 0.7548 | 0.7468 | 0.9431 | | 0.0465 | 12.0 | 256236 | 0.3103 | 0.8194 | 0.9203 | 0.8669 | 138 | 0.7031 | 0.7930 | 0.7453 | 227 | 0.5867 | 0.6718 | 0.6263 | 131 | 0.7829 | 0.8211 | 0.8016 | 1722 | 0.7582 | 0.7413 | 0.7496 | 719 | 0.8059 | 0.8616 | 0.8328 | 159 | 0.6648 | 0.5920 | 0.6263 | 201 | 0.6385 | 0.6484 | 0.6434 | 128 | 0.6827 | 0.7172 | 0.6995 | 198 | 0.7778 | 0.8322 | 0.8041 | 143 | 0.6679 | 0.7324 | 0.6987 | 497 | 0.6864 | 0.7056 | 0.6959 | 214 | 0.8473 | 0.8905 | 0.8684 | 1689 | 0.7552 | 0.7606 | 0.7579 | 142 | 0.7362 | 0.865 | 0.7954 | 200 | 0.7487 | 0.8011 | 0.7740 | 372 | 0.7470 | 0.7764 | 0.7614 | 407 | 0.7042 | 0.7031 | 0.7037 | 667 | 0.7435 | 0.7634 | 0.7533 | 224 | 0.5438 | 0.5856 | 0.5639 | 859 | 0.6261 | 0.6536 | 0.6395 | 433 | 0.6442 | 0.6186 | 0.6311 | 603 | 0.8482 | 0.7364 | 0.7884 | 129 | 0.7283 | 0.7613 | 0.7445 | 243 | 0.5075 | 0.5397 | 0.5231 | 189 | 0.7915 | 0.7915 | 0.7915 | 307 | 0.8564 | 0.8987 | 0.8771 | 385 | 0.6211 | 0.7268 | 0.6698 | 194 | 0.7633 | 0.8144 | 0.7880 | 194 | 0.7313 | 0.7597 | 0.7452 | 129 | 0.6450 | 0.7233 | 0.6819 | 206 | 0.7758 | 0.8139 | 0.7944 | 693 | 0.7189 | 0.7176 | 0.7182 | 563 | 0.7312 | 0.7621 | 0.7464 | 0.9428 | | 0.0459 | 13.0 | 277589 | 0.3141 | 0.8267 | 0.8986 | 0.8611 | 138 | 0.7254 | 0.7797 | 0.7516 | 227 | 0.6099 | 0.6565 | 0.6324 | 131 | 0.7929 | 0.8182 | 0.8054 | 1722 | 0.7562 | 0.7677 | 0.7619 | 719 | 0.8084 | 0.8491 | 0.8282 | 159 | 0.6302 | 0.6020 | 0.6158 | 201 | 0.6412 | 0.6562 | 0.6486 | 128 | 0.6931 | 0.7071 | 0.7000 | 198 | 0.7770 | 0.8042 | 0.7904 | 143 | 0.6834 | 0.7384 | 0.7099 | 497 | 0.6967 | 0.6869 | 0.6918 | 214 | 0.8631 | 0.8845 | 0.8737 | 1689 | 0.7939 | 0.7324 | 0.7619 | 142 | 0.7830 | 0.83 | 0.8058 | 200 | 0.7822 | 0.8011 | 0.7915 | 372 | 0.7482 | 0.7740 | 0.7609 | 407 | 0.6982 | 0.6972 | 0.6977 | 667 | 0.7867 | 0.7411 | 0.7632 | 224 | 0.5323 | 0.5856 | 0.5576 | 859 | 0.6469 | 0.6559 | 0.6514 | 433 | 0.6512 | 0.6036 | 0.6265 | 603 | 0.8611 | 0.7209 | 0.7848 | 129 | 0.7287 | 0.7737 | 0.7505 | 243 | 0.5185 | 0.5185 | 0.5185 | 189 | 0.7910 | 0.8013 | 0.7961 | 307 | 0.8715 | 0.8987 | 0.8849 | 385 | 0.7283 | 0.6907 | 0.7090 | 194 | 0.7512 | 0.7938 | 0.7719 | 194 | 0.7313 | 0.7597 | 0.7452 | 129 | 0.6147 | 0.6893 | 0.6499 | 206 | 0.7947 | 0.8268 | 0.8105 | 693 | 0.7170 | 0.7247 | 0.7208 | 563 | 0.7406 | 0.7588 | 0.7496 | 0.9436 | | 0.0386 | 14.0 | 298942 | 0.3268 | 0.8333 | 0.9058 | 0.8681 | 138 | 0.7092 | 0.7841 | 0.7448 | 227 | 0.6028 | 0.6489 | 0.625 | 131 | 0.7848 | 0.8153 | 0.7998 | 1722 | 0.7701 | 0.7594 | 0.7647 | 719 | 0.8047 | 0.8553 | 0.8293 | 159 | 0.6373 | 0.6119 | 0.6244 | 201 | 0.6204 | 0.6641 | 0.6415 | 128 | 0.6794 | 0.7172 | 0.6978 | 198 | 0.7986 | 0.8042 | 0.8014 | 143 | 0.6691 | 0.7324 | 0.6993 | 497 | 0.7109 | 0.7009 | 0.7059 | 214 | 0.8624 | 0.8834 | 0.8728 | 1689 | 0.7754 | 0.7535 | 0.7643 | 142 | 0.7757 | 0.83 | 0.8019 | 200 | 0.7712 | 0.8065 | 0.7884 | 372 | 0.7621 | 0.7715 | 0.7668 | 407 | 0.6782 | 0.7076 | 0.6926 | 667 | 0.7661 | 0.7455 | 0.7557 | 224 | 0.5417 | 0.5669 | 0.5540 | 859 | 0.6388 | 0.6536 | 0.6461 | 433 | 0.6160 | 0.6119 | 0.6140 | 603 | 0.8889 | 0.7442 | 0.8101 | 129 | 0.7431 | 0.7737 | 0.7581 | 243 | 0.5025 | 0.5397 | 0.5204 | 189 | 0.7915 | 0.7915 | 0.7915 | 307 | 0.8618 | 0.8909 | 0.8761 | 385 | 0.6699 | 0.7113 | 0.6900 | 194 | 0.7621 | 0.8093 | 0.7850 | 194 | 0.7226 | 0.7674 | 0.7444 | 129 | 0.6384 | 0.6942 | 0.6651 | 206 | 0.7872 | 0.8167 | 0.8017 | 693 | 0.7140 | 0.7229 | 0.7184 | 563 | 0.7358 | 0.7585 | 0.7470 | 0.9435 | | 0.037 | 15.0 | 320295 | 0.3308 | 0.8117 | 0.9058 | 0.8562 | 138 | 0.716 | 0.7885 | 0.7505 | 227 | 0.6028 | 0.6489 | 0.625 | 131 | 0.7838 | 0.8252 | 0.8040 | 1722 | 0.7835 | 0.7552 | 0.7691 | 719 | 0.7953 | 0.8553 | 0.8242 | 159 | 0.6630 | 0.5970 | 0.6283 | 201 | 0.6296 | 0.6641 | 0.6464 | 128 | 0.6961 | 0.7172 | 0.7065 | 198 | 0.8 | 0.8112 | 0.8056 | 143 | 0.6849 | 0.7304 | 0.7069 | 497 | 0.7156 | 0.7056 | 0.7106 | 214 | 0.8631 | 0.8845 | 0.8737 | 1689 | 0.7852 | 0.7465 | 0.7653 | 142 | 0.7602 | 0.84 | 0.7981 | 200 | 0.7601 | 0.8091 | 0.7839 | 372 | 0.7506 | 0.7617 | 0.7561 | 407 | 0.6943 | 0.7151 | 0.7046 | 667 | 0.7767 | 0.7455 | 0.7608 | 224 | 0.5351 | 0.5588 | 0.5467 | 859 | 0.6453 | 0.6513 | 0.6483 | 433 | 0.6277 | 0.6153 | 0.6214 | 603 | 0.8981 | 0.7519 | 0.8186 | 129 | 0.7362 | 0.7695 | 0.7525 | 243 | 0.5178 | 0.5397 | 0.5285 | 189 | 0.7806 | 0.7883 | 0.7844 | 307 | 0.8804 | 0.8987 | 0.8895 | 385 | 0.6863 | 0.7216 | 0.7035 | 194 | 0.7696 | 0.8093 | 0.7889 | 194 | 0.7333 | 0.7674 | 0.7500 | 129 | 0.6471 | 0.6942 | 0.6698 | 206 | 0.7917 | 0.8225 | 0.8068 | 693 | 0.7255 | 0.7229 | 0.7242 | 563 | 0.7404 | 0.7600 | 0.7501 | 0.9437 | ### Framework versions - Transformers 4.26.0.dev0 - Pytorch 1.12.1+cu113 - Datasets 2.7.1 - Tokenizers 0.13.2