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---
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
model-index:
- name: multilabel_ner
results: []
language:
- ru
library_name: transformers
widget:
- text: "В России стали заменять одежду брендов H&M и Zara дорогими аналогами из Турции. Об этом сообщает издание NEWS.ru. По словам анонимного источника портала, среди подобных альтернатив оказались такие турецкие марки, как Perspective, Ketroy и Mexx, магазины которого закрылись в стране в 2017 году из-за нерентабельности."
- text: "В Новосибирске задержали безработного жителя Томска, который продавал наркотики через интернет-магазин."
- text: 'Компания «Читинские ключи» получила господдержку и запустила производство «Колы» для сохранения рабочих мест, сообщили в пресс-службе министерства экономического развития Забайкальского края. По словам замминистра экономического развития Забайкалья Дениса Рысева, у «Колы» особенный вкус. На производстве уверяют, что используется секретный ингредиент. Как и у той «Кока-колы», известной на весь мир. Благодаря запуску нового производства компании удалось сохранить 241 сотрудника, сообщает РИА «Новости». Уточняется, что первая партия «Колы» – 900 упаковок была изготовлена 5 октября. В этот же день 600 упаковок купили предприниматели региона для продажи в магазинах. «Это ожидаемый продукт в условиях импортозамещения. Скучали по «Кока-коле»? Вот же она – только еще лучше, своя! Гарантийный фонд Забайкалья стал поручителем по кредиту для компании «Читинские ключи». Сумма поручительства 25 миллионов рублей, сумма кредита – почти 50 миллионов рублей», – добавил Рысев. Ранее сообщалось, что в Московской области планируется запустить новое производство компрессоров и фильтров для жидкостей, этим займется компания «Полинет».'
---
<!-- 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. -->
Russian NER model fine-tuned on RURED2.
https://github.com/denis-gordeev/rured2
This model outputs multiple possible labels for a single token. So for proper usage you can use it like in the following code:
```
import torch
from torch import nn
from transformers import (AutoTokenizer, AutoModelForTokenClassification,
TrainingArguments, Trainer)
model_name = "denis-gordeev/rured2-ner-microsoft-mdeberta-v3-base"
model = AutoModelForTokenClassification.from_pretrained(
model_name).to('cuda')
tokenizer = AutoTokenizer.from_pretrained(model_name)
def predict(text:str, glue_tokens=False, output_together=True, glue_words=True):
sigmoid = nn.Sigmoid()
tokenized = tokenizer(text)
input_ids = torch.tensor(
[tokenized["input_ids"]], dtype=torch.long
).to("cuda")
token_type_ids = torch.tensor(
[tokenized["token_type_ids"]], dtype=torch.long
).to("cuda")
attention_mask = torch.tensor(
[tokenized["attention_mask"]], dtype=torch.long
).to("cuda")
preds = model(**{"input_ids": input_ids, "token_type_ids": token_type_ids, "attention_mask": attention_mask})
logits = sigmoid(preds.logits)
output_tokens = []
output_preds = []
id_to_label = {int(k): v for k, v in model.config.id2label.items()}
for i, token in enumerate(input_ids[0]):
if token > 3:
class_ids = (logits[0][i] > 0.5).nonzero()
if class_ids.shape[0] >= 1:
class_names = [id_to_label[int(cl)] for cl in class_ids]
else:
class_names = [id_to_label[int(logits[0][i].argmax())]]
converted_token = tokenizer.convert_ids_to_tokens([token])[0]
new_word_bool = converted_token.startswith("▁")
converted_token = converted_token.replace("▁", "")
if glue_words and not(new_word_bool) and output_tokens:
output_tokens[-1] += converted_token
else:
output_tokens.append(converted_token)
output_preds.append(class_names)
else:
class_names = []
if output_together:
return [[output_tokens[t_i], output_preds[t_i]] for t_i in range(len(output_tokens))]
return output_tokens, output_preds
```
# denis-gordeev/rured2-ner-microsoft-mdeberta-v3-base
This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0096
- F1 Micro: 0.5837
- O F1 Micro: 0.6370
- O Recall Micro: 0.9242
- O Precision Micro: 0.4860
- B-person F1 Micro: 0.9639
- B-person Recall Micro: 0.9816
- B-person Precision Micro: 0.9468
- B-norp F1 Micro: 0.6190
- B-norp Recall Micro: 0.8667
- B-norp Precision Micro: 0.4815
- B-commodity F1 Micro: 0.7553
- B-commodity Recall Micro: 0.9470
- B-commodity Precision Micro: 0.6281
- B-date F1 Micro: 0.8386
- B-date Recall Micro: 0.8471
- B-date Precision Micro: 0.8304
- I-date F1 Micro: 0.6419
- I-date Recall Micro: 0.9492
- I-date Precision Micro: 0.4849
- B-country F1 Micro: 0.6152
- B-country Recall Micro: 0.9765
- B-country Precision Micro: 0.4490
- B-economic Sector F1 Micro: 0.5576
- B-economic Sector Recall Micro: 0.5897
- B-economic Sector Precision Micro: 0.5287
- I-economic Sector F1 Micro: 0.2517
- I-economic Sector Recall Micro: 0.6667
- I-economic Sector Precision Micro: 0.1551
- B-news Source F1 Micro: 0.7988
- B-news Source Recall Micro: 0.8327
- B-news Source Precision Micro: 0.7677
- B-profession F1 Micro: 0.8088
- B-profession Recall Micro: 0.9464
- B-profession Precision Micro: 0.7061
- I-news Source F1 Micro: 0.4808
- I-news Source Recall Micro: 0.8400
- I-news Source Precision Micro: 0.3368
- I-person F1 Micro: 0.3381
- I-person Recall Micro: 0.996
- I-person Precision Micro: 0.2036
- B-organization F1 Micro: 0.8350
- B-organization Recall Micro: 0.8993
- B-organization Precision Micro: 0.7794
- I-profession F1 Micro: 0.2462
- I-profession Recall Micro: 0.8030
- I-profession Precision Micro: 0.1454
- B-event F1 Micro: 0.5658
- B-event Recall Micro: 0.5436
- B-event Precision Micro: 0.5899
- B-city F1 Micro: 0.625
- B-city Recall Micro: 0.8904
- B-city Precision Micro: 0.4815
- B-gpe F1 Micro: 0.6760
- B-gpe Recall Micro: 0.9380
- B-gpe Precision Micro: 0.5284
- I-event F1 Micro: 0.2577
- I-event Recall Micro: 0.3776
- I-event Precision Micro: 0.1956
- B-group F1 Micro: 0.6667
- B-group Recall Micro: 0.75
- B-group Precision Micro: 0.6
- B-ordinal F1 Micro: 0.5306
- B-ordinal Recall Micro: 0.8125
- B-ordinal Precision Micro: 0.3939
- B-product F1 Micro: 0.6683
- B-product Recall Micro: 0.8232
- B-product Precision Micro: 0.5625
- I-organization F1 Micro: 0.3128
- I-organization Recall Micro: 0.8425
- I-organization Precision Micro: 0.1921
- B-money F1 Micro: 0.8530
- B-money Recall Micro: 0.8947
- B-money Precision Micro: 0.8151
- I-money F1 Micro: 0.6259
- I-money Recall Micro: 0.9644
- I-money Precision Micro: 0.4632
- B-currency F1 Micro: 0.7441
- B-currency Recall Micro: 0.9658
- B-currency Precision Micro: 0.6052
- B-percent F1 Micro: 0.8639
- B-percent Recall Micro: 0.8902
- B-percent Precision Micro: 0.8391
- I-percent F1 Micro: 0.6995
- I-percent Recall Micro: 0.9846
- I-percent Precision Micro: 0.5424
- I-group F1 Micro: 0.1844
- I-group Recall Micro: 0.4836
- I-group Precision Micro: 0.1139
- B-cardinal F1 Micro: 0.6903
- B-cardinal Recall Micro: 0.7358
- B-cardinal Precision Micro: 0.65
- B-law F1 Micro: 0.3704
- B-law Recall Micro: 0.3571
- B-law Precision Micro: 0.3846
- I-law F1 Micro: 0.3246
- I-law Recall Micro: 0.3936
- I-law Precision Micro: 0.2761
- B-fac F1 Micro: 0.6910
- B-fac Recall Micro: 0.6910
- B-fac Precision Micro: 0.6910
- I-fac F1 Micro: 0.3007
- I-fac Recall Micro: 0.7151
- I-fac Precision Micro: 0.1904
- B-age F1 Micro: 0.8649
- B-age Recall Micro: 0.7619
- B-age Precision Micro: 1.0
- I-city F1 Micro: 0.1047
- I-city Recall Micro: 0.6429
- I-city Precision Micro: 0.0570
- B-work Of Art F1 Micro: 0.3158
- B-work Of Art Recall Micro: 0.375
- B-work Of Art Precision Micro: 0.2727
- I-work Of Art F1 Micro: 0.3721
- I-work Of Art Recall Micro: 0.5
- I-work Of Art Precision Micro: 0.2963
- B-region F1 Micro: 0.8070
- B-region Recall Micro: 0.7731
- B-region Precision Micro: 0.8440
- I-region F1 Micro: 0.2817
- I-region Recall Micro: 0.8197
- I-region Precision Micro: 0.1701
- I-cardinal F1 Micro: 0.3851
- I-cardinal Recall Micro: 0.4831
- I-cardinal Precision Micro: 0.3202
- I-currency F1 Micro: 0.0
- I-currency Recall Micro: 0.0
- I-currency Precision Micro: 0.0
- B-quantity F1 Micro: 0.7311
- B-quantity Recall Micro: 0.7311
- B-quantity Precision Micro: 0.7311
- I-quantity F1 Micro: 0.4889
- I-quantity Recall Micro: 0.7989
- I-quantity Precision Micro: 0.3522
- B-crime F1 Micro: 0.3736
- B-crime Recall Micro: 0.4048
- B-crime Precision Micro: 0.3469
- I-crime F1 Micro: 0.3245
- I-crime Recall Micro: 0.5648
- I-crime Precision Micro: 0.2276
- B-trade Agreement F1 Micro: 0.7170
- B-trade Agreement Recall Micro: 0.7037
- B-trade Agreement Precision Micro: 0.7308
- B-nationality F1 Micro: 0.0
- B-nationality Recall Micro: 0.0
- B-nationality Precision Micro: 0.0
- B-family F1 Micro: 0.5
- B-family Recall Micro: 0.8889
- B-family Precision Micro: 0.3478
- I-family F1 Micro: 0.0
- I-family Recall Micro: 0.0
- I-family Precision Micro: 0.0
- I-product F1 Micro: 0.2021
- I-product Recall Micro: 0.6824
- I-product Precision Micro: 0.1186
- B-time F1 Micro: 0.6538
- B-time Recall Micro: 0.6296
- B-time Precision Micro: 0.68
- I-time F1 Micro: 0.6118
- I-time Recall Micro: 0.9811
- I-time Precision Micro: 0.4444
- I-commodity F1 Micro: 0.0444
- I-commodity Recall Micro: 0.1667
- I-commodity Precision Micro: 0.0256
- B-application F1 Micro: 0.0
- B-application Recall Micro: 0.0
- B-application Precision Micro: 0.0
- I-application F1 Micro: 0.0
- I-application Recall Micro: 0.0
- I-application Precision Micro: 0.0
- I-country F1 Micro: 0.1695
- I-country Recall Micro: 0.7895
- I-country Precision Micro: 0.0949
- B-award F1 Micro: 0.5455
- B-award Recall Micro: 0.4615
- B-award Precision Micro: 0.6667
- I-award F1 Micro: 0.4459
- I-award Recall Micro: 0.8049
- I-award Precision Micro: 0.3084
- I-gpe F1 Micro: 0.3284
- I-gpe Recall Micro: 0.9167
- I-gpe Precision Micro: 0.2
- B-location F1 Micro: 0.4885
- B-location Recall Micro: 0.5161
- B-location Precision Micro: 0.4638
- I-location F1 Micro: 0.3189
- I-location Recall Micro: 0.6316
- I-location Precision Micro: 0.2133
- I-ordinal F1 Micro: 0.5
- I-ordinal Recall Micro: 0.4
- I-ordinal Precision Micro: 0.6667
- I-trade Agreement F1 Micro: 0.1163
- I-trade Agreement Recall Micro: 0.3846
- I-trade Agreement Precision Micro: 0.0685
- B-religion F1 Micro: 0.0
- B-religion Recall Micro: 0.0
- B-religion Precision Micro: 0.0
- I-age F1 Micro: 0.4324
- I-age Recall Micro: 0.5714
- I-age Precision Micro: 0.3478
- B-investment Program F1 Micro: 0.0
- B-investment Program Recall Micro: 0.0
- B-investment Program Precision Micro: 0.0
- I-investment Program F1 Micro: 0.0
- I-investment Program Recall Micro: 0.0
- I-investment Program Precision Micro: 0.0
- B-borough F1 Micro: 0.7059
- B-borough Recall Micro: 0.6667
- B-borough Precision Micro: 0.75
- B-price F1 Micro: 0.0
- B-price Recall Micro: 0.0
- B-price Precision Micro: 0.0
- I-price F1 Micro: 0.0
- I-price Recall Micro: 0.0
- I-price Precision Micro: 0.0
- B-character F1 Micro: 0.0
- B-character Recall Micro: 0.0
- B-character Precision Micro: 0.0
- I-character F1 Micro: 0.0
- I-character Recall Micro: 0.0
- I-character Precision Micro: 0.0
- B-website F1 Micro: 0.0
- B-website Recall Micro: 0.0
- B-website Precision Micro: 0.0
- B-street F1 Micro: 0.4000
- B-street Recall Micro: 0.4286
- B-street Precision Micro: 0.375
- I-street F1 Micro: 0.3256
- I-street Recall Micro: 1.0
- I-street Precision Micro: 0.1944
- B-village F1 Micro: 0.6667
- B-village Recall Micro: 0.7
- B-village Precision Micro: 0.6364
- I-village F1 Micro: 0.2222
- I-village Recall Micro: 0.875
- I-village Precision Micro: 0.1273
- B-disease F1 Micro: 0.5965
- B-disease Recall Micro: 0.7083
- B-disease Precision Micro: 0.5152
- I-disease F1 Micro: 0.3704
- I-disease Recall Micro: 0.7812
- I-disease Precision Micro: 0.2427
- B-penalty F1 Micro: 0.1579
- B-penalty Recall Micro: 0.1579
- B-penalty Precision Micro: 0.1579
- I-penalty F1 Micro: 0.1674
- I-penalty Recall Micro: 0.3175
- I-penalty Precision Micro: 0.1136
- B-weapon F1 Micro: 0.6715
- B-weapon Recall Micro: 0.7302
- B-weapon Precision Micro: 0.6216
- I-weapon F1 Micro: 0.2455
- I-weapon Recall Micro: 0.5965
- I-weapon Precision Micro: 0.1545
- I-borough F1 Micro: 0.4091
- I-borough Recall Micro: 0.6923
- I-borough Precision Micro: 0.2903
- B-vehicle F1 Micro: 0.6349
- B-vehicle Recall Micro: 0.5882
- B-vehicle Precision Micro: 0.6897
- I-vehicle F1 Micro: 0.4174
- I-vehicle Recall Micro: 0.7273
- I-vehicle Precision Micro: 0.2927
- B-language F1 Micro: 0.0
- B-language Recall Micro: 0.0
- B-language Precision Micro: 0.0
- I-language F1 Micro: 0.0
- I-language Recall Micro: 0.0
- I-language Precision Micro: 0.0
- B-house F1 Micro: 0.0
- B-house Recall Micro: 0.0
- B-house Precision Micro: 0.0
- I-norp F1 Micro: 0.0
- I-norp Recall Micro: 0.0
- I-norp Precision Micro: 0.0
- I-house F1 Micro: 0.0
- I-house Recall Micro: 0.0
- I-house Precision Micro: 0.0
- I-website F1 Micro: 0.0
- I-website Recall Micro: 0.0
- I-website Precision Micro: 0.0
- F1 Macro: 0.3969
- Recall Macro: 0.5603
- Precision Macro: 0.3447
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | O F1 Micro | O Recall Micro | O Precision Micro | B-person F1 Micro | B-person Recall Micro | B-person Precision Micro | B-norp F1 Micro | B-norp Recall Micro | B-norp Precision Micro | B-commodity F1 Micro | B-commodity Recall Micro | B-commodity Precision Micro | B-date F1 Micro | B-date Recall Micro | B-date Precision Micro | I-date F1 Micro | I-date Recall Micro | I-date Precision Micro | B-country F1 Micro | B-country Recall Micro | B-country Precision Micro | B-economic Sector F1 Micro | B-economic Sector Recall Micro | B-economic Sector Precision Micro | I-economic Sector F1 Micro | I-economic Sector Recall Micro | I-economic Sector Precision Micro | B-news Source F1 Micro | B-news Source Recall Micro | B-news Source Precision Micro | B-profession F1 Micro | B-profession Recall Micro | B-profession Precision Micro | I-news Source F1 Micro | I-news Source Recall Micro | I-news Source Precision Micro | I-person F1 Micro | I-person Recall Micro | I-person Precision Micro | B-organization F1 Micro | B-organization Recall Micro | B-organization Precision Micro | I-profession F1 Micro | I-profession Recall Micro | I-profession Precision Micro | B-event F1 Micro | B-event Recall Micro | B-event Precision Micro | B-city F1 Micro | B-city Recall Micro | B-city Precision Micro | B-gpe F1 Micro | B-gpe Recall Micro | B-gpe Precision Micro | I-event F1 Micro | I-event Recall Micro | I-event Precision Micro | B-group F1 Micro | B-group Recall Micro | B-group Precision Micro | B-ordinal F1 Micro | B-ordinal Recall Micro | B-ordinal Precision Micro | B-product F1 Micro | B-product Recall Micro | B-product Precision Micro | I-organization F1 Micro | I-organization Recall Micro | I-organization Precision Micro | B-money F1 Micro | B-money Recall Micro | B-money Precision Micro | I-money F1 Micro | I-money Recall Micro | I-money Precision Micro | B-currency F1 Micro | B-currency Recall Micro | B-currency Precision Micro | B-percent F1 Micro | B-percent Recall Micro | B-percent Precision Micro | I-percent F1 Micro | I-percent Recall Micro | I-percent Precision Micro | I-group F1 Micro | I-group Recall Micro | I-group Precision Micro | B-cardinal F1 Micro | B-cardinal Recall Micro | B-cardinal Precision Micro | B-law F1 Micro | B-law Recall Micro | B-law Precision Micro | I-law F1 Micro | I-law Recall Micro | I-law Precision Micro | B-fac F1 Micro | B-fac Recall Micro | B-fac Precision Micro | I-fac F1 Micro | I-fac Recall Micro | I-fac Precision Micro | B-age F1 Micro | B-age Recall Micro | B-age Precision Micro | I-city F1 Micro | I-city Recall Micro | I-city Precision Micro | B-work Of Art F1 Micro | B-work Of Art Recall Micro | B-work Of Art Precision Micro | I-work Of Art F1 Micro | I-work Of Art Recall Micro | I-work Of Art Precision Micro | B-region F1 Micro | B-region Recall Micro | B-region Precision Micro | I-region F1 Micro | I-region Recall Micro | I-region Precision Micro | I-cardinal F1 Micro | I-cardinal Recall Micro | I-cardinal Precision Micro | I-currency F1 Micro | I-currency Recall Micro | I-currency Precision Micro | B-quantity F1 Micro | B-quantity Recall Micro | B-quantity Precision Micro | I-quantity F1 Micro | I-quantity Recall Micro | I-quantity Precision Micro | B-crime F1 Micro | B-crime Recall Micro | B-crime Precision Micro | I-crime F1 Micro | I-crime Recall Micro | I-crime Precision Micro | B-trade Agreement F1 Micro | B-trade Agreement Recall Micro | B-trade Agreement Precision Micro | B-nationality F1 Micro | B-nationality Recall Micro | B-nationality Precision Micro | B-family F1 Micro | B-family Recall Micro | B-family Precision Micro | I-family F1 Micro | I-family Recall Micro | I-family Precision Micro | I-product F1 Micro | I-product Recall Micro | I-product Precision Micro | B-time F1 Micro | B-time Recall Micro | B-time Precision Micro | I-time F1 Micro | I-time Recall Micro | I-time Precision Micro | I-commodity F1 Micro | I-commodity Recall Micro | I-commodity Precision Micro | B-application F1 Micro | B-application Recall Micro | B-application Precision Micro | I-application F1 Micro | I-application Recall Micro | I-application Precision Micro | I-country F1 Micro | I-country Recall Micro | I-country Precision Micro | B-award F1 Micro | B-award Recall Micro | B-award Precision Micro | I-award F1 Micro | I-award Recall Micro | I-award Precision Micro | I-gpe F1 Micro | I-gpe Recall Micro | I-gpe Precision Micro | B-location F1 Micro | B-location Recall Micro | B-location Precision Micro | I-location F1 Micro | I-location Recall Micro | I-location Precision Micro | I-ordinal F1 Micro | I-ordinal Recall Micro | I-ordinal Precision Micro | I-trade Agreement F1 Micro | I-trade Agreement Recall Micro | I-trade Agreement Precision Micro | B-religion F1 Micro | B-religion Recall Micro | B-religion Precision Micro | I-age F1 Micro | I-age Recall Micro | I-age Precision Micro | B-investment Program F1 Micro | B-investment Program Recall Micro | B-investment Program Precision Micro | I-investment Program F1 Micro | I-investment Program Recall Micro | I-investment Program Precision Micro | B-borough F1 Micro | B-borough Recall Micro | B-borough Precision Micro | B-price F1 Micro | B-price Recall Micro | B-price Precision Micro | I-price F1 Micro | I-price Recall Micro | I-price Precision Micro | B-character F1 Micro | B-character Recall Micro | B-character Precision Micro | I-character F1 Micro | I-character Recall Micro | I-character Precision Micro | B-website F1 Micro | B-website Recall Micro | B-website Precision Micro | B-street F1 Micro | B-street Recall Micro | B-street Precision Micro | I-street F1 Micro | I-street Recall Micro | I-street Precision Micro | B-village F1 Micro | B-village Recall Micro | B-village Precision Micro | I-village F1 Micro | I-village Recall Micro | I-village Precision Micro | B-disease F1 Micro | B-disease Recall Micro | B-disease Precision Micro | I-disease F1 Micro | I-disease Recall Micro | I-disease Precision Micro | B-penalty F1 Micro | B-penalty Recall Micro | B-penalty Precision Micro | I-penalty F1 Micro | I-penalty Recall Micro | I-penalty Precision Micro | B-weapon F1 Micro | B-weapon Recall Micro | B-weapon Precision Micro | I-weapon F1 Micro | I-weapon Recall Micro | I-weapon Precision Micro | I-borough F1 Micro | I-borough Recall Micro | I-borough Precision Micro | B-vehicle F1 Micro | B-vehicle Recall Micro | B-vehicle Precision Micro | I-vehicle F1 Micro | I-vehicle Recall Micro | I-vehicle Precision Micro | B-language F1 Micro | B-language Recall Micro | B-language Precision Micro | I-language F1 Micro | I-language Recall Micro | I-language Precision Micro | B-house F1 Micro | B-house Recall Micro | B-house Precision Micro | I-norp F1 Micro | I-norp Recall Micro | I-norp Precision Micro | I-house F1 Micro | I-house Recall Micro | I-house Precision Micro | I-website F1 Micro | I-website Recall Micro | I-website Precision Micro | F1 Macro | Recall Macro | Precision Macro |
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| 0.0033 | 1.0 | 3014 | 0.0092 | 0.5876 | 0.6385 | 0.9365 | 0.4844 | 0.9705 | 0.9816 | 0.9596 | 0.6118 | 0.8667 | 0.4727 | 0.7873 | 0.9394 | 0.6776 | 0.8436 | 0.8571 | 0.8304 | 0.6416 | 0.9669 | 0.4801 | 0.6229 | 0.9831 | 0.4559 | 0.6024 | 0.6410 | 0.5682 | 0.2491 | 0.5965 | 0.1574 | 0.7954 | 0.8306 | 0.7630 | 0.8659 | 0.9184 | 0.8191 | 0.4757 | 0.8461 | 0.3309 | 0.3331 | 0.996 | 0.2 | 0.8277 | 0.9038 | 0.7633 | 0.2675 | 0.7652 | 0.1621 | 0.5617 | 0.5291 | 0.5987 | 0.7347 | 0.8630 | 0.6396 | 0.6989 | 0.9535 | 0.5516 | 0.2461 | 0.3922 | 0.1793 | 0.7073 | 0.7143 | 0.7004 | 0.592 | 0.7708 | 0.4805 | 0.7213 | 0.8049 | 0.6535 | 0.3127 | 0.8040 | 0.1941 | 0.88 | 0.9098 | 0.8521 | 0.6312 | 0.9502 | 0.4726 | 0.7622 | 0.9658 | 0.6295 | 0.8824 | 0.9146 | 0.8523 | 0.6952 | 1.0 | 0.5328 | 0.1762 | 0.4426 | 0.1100 | 0.6688 | 0.6604 | 0.6774 | 0.3846 | 0.3571 | 0.4167 | 0.2473 | 0.3617 | 0.1878 | 0.7348 | 0.7253 | 0.7445 | 0.3085 | 0.6977 | 0.1980 | 0.8333 | 0.7143 | 1.0 | 0.1010 | 0.7143 | 0.0543 | 0.3333 | 0.25 | 0.5 | 0.4242 | 0.4375 | 0.4118 | 0.7729 | 0.8151 | 0.7348 | 0.2865 | 0.8033 | 0.1744 | 0.4196 | 0.5085 | 0.3571 | 0.0 | 0.0 | 0.0 | 0.7177 | 0.7479 | 0.6899 | 0.4931 | 0.7933 | 0.3577 | 0.3789 | 0.4286 | 0.3396 | 0.3341 | 0.6574 | 0.2240 | 0.6415 | 0.6296 | 0.6538 | 0.0 | 0.0 | 0.0 | 0.4737 | 1.0 | 0.3103 | 0.0 | 0.0 | 0.0 | 0.2270 | 0.5647 | 0.1420 | 0.6667 | 0.6667 | 0.6667 | 0.5854 | 0.9057 | 0.4324 | 0.0741 | 0.1667 | 0.0476 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1867 | 0.7368 | 0.1069 | 0.4444 | 0.3077 | 0.8 | 0.4706 | 0.7805 | 0.3368 | 0.2619 | 0.9167 | 0.1528 | 0.4878 | 0.4839 | 0.4918 | 0.2997 | 0.6053 | 0.1991 | 0.25 | 0.2 | 0.3333 | 0.1154 | 0.2308 | 0.0769 | 0.0 | 0.0 | 0.0 | 0.3750 | 0.6429 | 0.2647 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6667 | 0.6667 | 0.6667 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5 | 0.5714 | 0.4444 | 0.3333 | 1.0 | 0.2 | 0.6222 | 0.7 | 0.56 | 0.2424 | 1.0 | 0.1379 | 0.5778 | 0.5417 | 0.6190 | 0.3425 | 0.7812 | 0.2193 | 0.1212 | 0.1053 | 0.1429 | 0.1847 | 0.3651 | 0.1237 | 0.7015 | 0.7460 | 0.6620 | 0.2256 | 0.5263 | 0.1435 | 0.4045 | 0.6923 | 0.2857 | 0.7143 | 0.7353 | 0.6944 | 0.3826 | 0.6667 | 0.2683 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3969 | 0.5513 | 0.3515 |
| 0.0032 | 2.0 | 6028 | 0.0096 | 0.5837 | 0.6370 | 0.9242 | 0.4860 | 0.9639 | 0.9816 | 0.9468 | 0.6190 | 0.8667 | 0.4815 | 0.7553 | 0.9470 | 0.6281 | 0.8386 | 0.8471 | 0.8304 | 0.6419 | 0.9492 | 0.4849 | 0.6152 | 0.9765 | 0.4490 | 0.5576 | 0.5897 | 0.5287 | 0.2517 | 0.6667 | 0.1551 | 0.7988 | 0.8327 | 0.7677 | 0.8088 | 0.9464 | 0.7061 | 0.4808 | 0.8400 | 0.3368 | 0.3381 | 0.996 | 0.2036 | 0.8350 | 0.8993 | 0.7794 | 0.2462 | 0.8030 | 0.1454 | 0.5658 | 0.5436 | 0.5899 | 0.625 | 0.8904 | 0.4815 | 0.6760 | 0.9380 | 0.5284 | 0.2577 | 0.3776 | 0.1956 | 0.6667 | 0.75 | 0.6 | 0.5306 | 0.8125 | 0.3939 | 0.6683 | 0.8232 | 0.5625 | 0.3128 | 0.8425 | 0.1921 | 0.8530 | 0.8947 | 0.8151 | 0.6259 | 0.9644 | 0.4632 | 0.7441 | 0.9658 | 0.6052 | 0.8639 | 0.8902 | 0.8391 | 0.6995 | 0.9846 | 0.5424 | 0.1844 | 0.4836 | 0.1139 | 0.6903 | 0.7358 | 0.65 | 0.3704 | 0.3571 | 0.3846 | 0.3246 | 0.3936 | 0.2761 | 0.6910 | 0.6910 | 0.6910 | 0.3007 | 0.7151 | 0.1904 | 0.8649 | 0.7619 | 1.0 | 0.1047 | 0.6429 | 0.0570 | 0.3158 | 0.375 | 0.2727 | 0.3721 | 0.5 | 0.2963 | 0.8070 | 0.7731 | 0.8440 | 0.2817 | 0.8197 | 0.1701 | 0.3851 | 0.4831 | 0.3202 | 0.0 | 0.0 | 0.0 | 0.7311 | 0.7311 | 0.7311 | 0.4889 | 0.7989 | 0.3522 | 0.3736 | 0.4048 | 0.3469 | 0.3245 | 0.5648 | 0.2276 | 0.7170 | 0.7037 | 0.7308 | 0.0 | 0.0 | 0.0 | 0.5 | 0.8889 | 0.3478 | 0.0 | 0.0 | 0.0 | 0.2021 | 0.6824 | 0.1186 | 0.6538 | 0.6296 | 0.68 | 0.6118 | 0.9811 | 0.4444 | 0.0444 | 0.1667 | 0.0256 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1695 | 0.7895 | 0.0949 | 0.5455 | 0.4615 | 0.6667 | 0.4459 | 0.8049 | 0.3084 | 0.3284 | 0.9167 | 0.2 | 0.4885 | 0.5161 | 0.4638 | 0.3189 | 0.6316 | 0.2133 | 0.5 | 0.4 | 0.6667 | 0.1163 | 0.3846 | 0.0685 | 0.0 | 0.0 | 0.0 | 0.4324 | 0.5714 | 0.3478 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.7059 | 0.6667 | 0.75 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4000 | 0.4286 | 0.375 | 0.3256 | 1.0 | 0.1944 | 0.6667 | 0.7 | 0.6364 | 0.2222 | 0.875 | 0.1273 | 0.5965 | 0.7083 | 0.5152 | 0.3704 | 0.7812 | 0.2427 | 0.1579 | 0.1579 | 0.1579 | 0.1674 | 0.3175 | 0.1136 | 0.6715 | 0.7302 | 0.6216 | 0.2455 | 0.5965 | 0.1545 | 0.4091 | 0.6923 | 0.2903 | 0.6349 | 0.5882 | 0.6897 | 0.4174 | 0.7273 | 0.2927 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3969 | 0.5603 | 0.3447 |
| 0.0029 | 3.0 | 9042 | 0.0102 | 0.5857 | 0.6369 | 0.9367 | 0.4824 | 0.9555 | 0.9862 | 0.9266 | 0.5909 | 0.8667 | 0.4483 | 0.7590 | 0.9545 | 0.63 | 0.8374 | 0.8551 | 0.8205 | 0.6347 | 0.9752 | 0.4704 | 0.6097 | 0.9817 | 0.4422 | 0.6286 | 0.7051 | 0.5670 | 0.2581 | 0.6316 | 0.1622 | 0.7871 | 0.8347 | 0.7446 | 0.8664 | 0.9371 | 0.8056 | 0.4789 | 0.8564 | 0.3324 | 0.3383 | 0.996 | 0.2038 | 0.8071 | 0.8929 | 0.7364 | 0.2440 | 0.8106 | 0.1436 | 0.5397 | 0.4738 | 0.6269 | 0.7014 | 0.8767 | 0.5845 | 0.6503 | 0.9225 | 0.5021 | 0.2354 | 0.3306 | 0.1828 | 0.6799 | 0.75 | 0.6217 | 0.592 | 0.7708 | 0.4805 | 0.7163 | 0.7622 | 0.6757 | 0.3133 | 0.8077 | 0.1944 | 0.8278 | 0.8496 | 0.8071 | 0.6187 | 0.9644 | 0.4555 | 0.7749 | 0.9315 | 0.6634 | 0.8606 | 0.8659 | 0.8554 | 0.688 | 0.9923 | 0.5265 | 0.1872 | 0.4918 | 0.1156 | 0.6826 | 0.7170 | 0.6514 | 0.4286 | 0.4286 | 0.4286 | 0.2900 | 0.4149 | 0.2229 | 0.7124 | 0.6910 | 0.7352 | 0.3132 | 0.7093 | 0.2010 | 0.8649 | 0.7619 | 1.0 | 0.0988 | 0.5714 | 0.0541 | 0.1429 | 0.125 | 0.1667 | 0.3889 | 0.4375 | 0.35 | 0.7317 | 0.7563 | 0.7087 | 0.2889 | 0.8525 | 0.1739 | 0.4224 | 0.5763 | 0.3333 | 0.0 | 0.0 | 0.0 | 0.7265 | 0.7143 | 0.7391 | 0.4936 | 0.7598 | 0.3656 | 0.3564 | 0.4286 | 0.3051 | 0.2857 | 0.6944 | 0.1799 | 0.6471 | 0.8148 | 0.5366 | 0.0 | 0.0 | 0.0 | 0.5455 | 1.0 | 0.375 | 0.0 | 0.0 | 0.0 | 0.2392 | 0.5529 | 0.1526 | 0.6415 | 0.6296 | 0.6538 | 0.6 | 0.9057 | 0.4486 | 0.1176 | 0.6667 | 0.0645 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1436 | 0.7368 | 0.0795 | 0.4286 | 0.4615 | 0.4 | 0.4595 | 0.8293 | 0.3178 | 0.3548 | 0.9167 | 0.22 | 0.5197 | 0.5323 | 0.5077 | 0.3300 | 0.6447 | 0.2217 | 0.4444 | 0.4 | 0.5 | 0.0870 | 0.2308 | 0.0536 | 0.0 | 0.0 | 0.0 | 0.3902 | 0.5714 | 0.2963 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6471 | 0.6111 | 0.6875 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4000 | 0.4286 | 0.375 | 0.3256 | 1.0 | 0.1944 | 0.6829 | 0.7 | 0.6667 | 0.2258 | 0.875 | 0.1296 | 0.4928 | 0.7083 | 0.3778 | 0.3521 | 0.7812 | 0.2273 | 0.15 | 0.1579 | 0.1429 | 0.2128 | 0.3175 | 0.16 | 0.7059 | 0.7619 | 0.6575 | 0.2581 | 0.7018 | 0.1581 | 0.3956 | 0.6923 | 0.2769 | 0.7143 | 0.7353 | 0.6944 | 0.4915 | 0.8788 | 0.3412 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3958 | 0.5647 | 0.3398 |
| 0.0026 | 4.0 | 12056 | 0.0105 | 0.5820 | 0.6363 | 0.9236 | 0.4854 | 0.9661 | 0.9839 | 0.9490 | 0.6118 | 0.8667 | 0.4727 | 0.7568 | 0.9545 | 0.6269 | 0.8481 | 0.8370 | 0.8595 | 0.6525 | 0.9587 | 0.4945 | 0.6156 | 0.9844 | 0.4478 | 0.6125 | 0.6282 | 0.5976 | 0.2618 | 0.6316 | 0.1651 | 0.8011 | 0.8448 | 0.7618 | 0.8447 | 0.9254 | 0.7769 | 0.4769 | 0.8303 | 0.3346 | 0.3379 | 0.996 | 0.2034 | 0.8171 | 0.8938 | 0.7525 | 0.2480 | 0.8182 | 0.1461 | 0.5205 | 0.5174 | 0.5235 | 0.6432 | 0.8767 | 0.5079 | 0.6821 | 0.9147 | 0.5438 | 0.2270 | 0.4441 | 0.1525 | 0.6405 | 0.7460 | 0.5612 | 0.6016 | 0.7708 | 0.4933 | 0.7299 | 0.7744 | 0.6902 | 0.3177 | 0.8059 | 0.1978 | 0.8699 | 0.8797 | 0.8603 | 0.6308 | 0.9395 | 0.4748 | 0.7637 | 0.9521 | 0.6376 | 0.8571 | 0.8780 | 0.8372 | 0.688 | 0.9923 | 0.5265 | 0.1887 | 0.4918 | 0.1167 | 0.6879 | 0.7484 | 0.6364 | 0.3333 | 0.3571 | 0.3125 | 0.2439 | 0.3723 | 0.1813 | 0.6925 | 0.6910 | 0.6940 | 0.3186 | 0.7326 | 0.2036 | 0.8333 | 0.7143 | 1.0 | 0.1046 | 0.5714 | 0.0576 | 0.2857 | 0.25 | 0.3333 | 0.3333 | 0.4375 | 0.2692 | 0.7583 | 0.7647 | 0.7521 | 0.2985 | 0.8197 | 0.1825 | 0.3416 | 0.4661 | 0.2696 | 0.0 | 0.0 | 0.0 | 0.7113 | 0.7143 | 0.7083 | 0.4965 | 0.7877 | 0.3625 | 0.3800 | 0.4524 | 0.3276 | 0.3125 | 0.6944 | 0.2016 | 0.6545 | 0.6667 | 0.6429 | 0.0 | 0.0 | 0.0 | 0.5143 | 1.0 | 0.3462 | 0.0 | 0.0 | 0.0 | 0.2338 | 0.5294 | 0.15 | 0.6429 | 0.6667 | 0.6207 | 0.5561 | 0.9811 | 0.3881 | 0.1481 | 0.6667 | 0.0833 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1172 | 0.7368 | 0.0636 | 0.4762 | 0.3846 | 0.625 | 0.4648 | 0.8049 | 0.3267 | 0.2299 | 0.8333 | 0.1333 | 0.4429 | 0.5 | 0.3974 | 0.3009 | 0.6711 | 0.1939 | 0.4444 | 0.4 | 0.5 | 0.0714 | 0.1538 | 0.0465 | 0.0 | 0.0 | 0.0 | 0.4118 | 0.5 | 0.35 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.7568 | 0.7778 | 0.7368 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3077 | 0.2857 | 0.3333 | 0.3333 | 1.0 | 0.2 | 0.6667 | 0.75 | 0.6 | 0.2222 | 0.875 | 0.1273 | 0.5246 | 0.6667 | 0.4324 | 0.3145 | 0.7812 | 0.1969 | 0.1818 | 0.2105 | 0.16 | 0.1910 | 0.3016 | 0.1397 | 0.6341 | 0.8254 | 0.5149 | 0.2434 | 0.6491 | 0.1498 | 0.3925 | 0.8077 | 0.2593 | 0.7042 | 0.7353 | 0.6757 | 0.4265 | 0.8788 | 0.2816 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3908 | 0.5625 | 0.3356 |
| 0.0024 | 5.0 | 15070 | 0.0106 | 0.5861 | 0.6371 | 0.9416 | 0.4815 | 0.9805 | 0.9839 | 0.9772 | 0.5909 | 0.8667 | 0.4483 | 0.8039 | 0.9470 | 0.6983 | 0.7907 | 0.7827 | 0.7988 | 0.6354 | 0.9126 | 0.4874 | 0.6076 | 0.9791 | 0.4405 | 0.5590 | 0.5769 | 0.5422 | 0.2528 | 0.5965 | 0.1604 | 0.7992 | 0.8508 | 0.7536 | 0.8109 | 0.9347 | 0.7161 | 0.4823 | 0.8485 | 0.3369 | 0.3381 | 0.996 | 0.2036 | 0.8518 | 0.9103 | 0.8003 | 0.2566 | 0.8106 | 0.1524 | 0.5482 | 0.5203 | 0.5793 | 0.6995 | 0.8767 | 0.5818 | 0.6629 | 0.8992 | 0.5249 | 0.2411 | 0.3355 | 0.1882 | 0.6858 | 0.7103 | 0.6630 | 0.5455 | 0.8125 | 0.4105 | 0.6468 | 0.7927 | 0.5462 | 0.3140 | 0.8498 | 0.1926 | 0.8722 | 0.8722 | 0.8722 | 0.6272 | 0.9431 | 0.4699 | 0.7363 | 0.9658 | 0.5949 | 0.8690 | 0.8902 | 0.8488 | 0.6904 | 0.9692 | 0.5362 | 0.1986 | 0.4590 | 0.1267 | 0.7049 | 0.7736 | 0.6474 | 0.3125 | 0.3571 | 0.2778 | 0.2397 | 0.4043 | 0.1704 | 0.6680 | 0.6953 | 0.6429 | 0.3102 | 0.7267 | 0.1972 | 0.8649 | 0.7619 | 1.0 | 0.0859 | 0.5 | 0.0470 | 0.2667 | 0.25 | 0.2857 | 0.3333 | 0.4375 | 0.2692 | 0.7819 | 0.7983 | 0.7661 | 0.2779 | 0.8361 | 0.1667 | 0.4099 | 0.5593 | 0.3235 | 0.0 | 0.0 | 0.0 | 0.7378 | 0.6975 | 0.7830 | 0.4953 | 0.7318 | 0.3743 | 0.3191 | 0.3571 | 0.2885 | 0.3052 | 0.5185 | 0.2162 | 0.6667 | 0.8519 | 0.5476 | 0.0 | 0.0 | 0.0 | 0.5625 | 1.0 | 0.3913 | 0.0 | 0.0 | 0.0 | 0.25 | 0.5765 | 0.1596 | 0.5926 | 0.5926 | 0.5926 | 0.56 | 0.9245 | 0.4016 | 0.1067 | 0.6667 | 0.0580 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1266 | 0.7895 | 0.0688 | 0.3478 | 0.3077 | 0.4 | 0.4828 | 0.6829 | 0.3733 | 0.2933 | 0.9167 | 0.1746 | 0.4885 | 0.5161 | 0.4638 | 0.3055 | 0.5526 | 0.2111 | 0.4615 | 0.6 | 0.375 | 0.1034 | 0.2308 | 0.0667 | 0.0 | 0.0 | 0.0 | 0.4091 | 0.6429 | 0.3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.7647 | 0.7222 | 0.8125 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4000 | 0.4286 | 0.375 | 0.3333 | 1.0 | 0.2 | 0.6341 | 0.65 | 0.6190 | 0.2034 | 0.75 | 0.1176 | 0.3404 | 0.6667 | 0.2286 | 0.3356 | 0.7812 | 0.2137 | 0.2041 | 0.2632 | 0.1667 | 0.3077 | 0.4444 | 0.2353 | 0.6483 | 0.7460 | 0.5732 | 0.2628 | 0.6316 | 0.1659 | 0.4368 | 0.7308 | 0.3115 | 0.7385 | 0.7059 | 0.7742 | 0.448 | 0.8485 | 0.3043 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3916 | 0.5600 | 0.3347 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.2.2
- Tokenizers 0.14.1 |