模型:

tartuNLP/EstBERT_NER_v2

英文

基于EstBERT的爱沙尼亚NER模型

这个模型是基于Estonian NER数据集对 tartuNLP/EstBERT 进行微调的版本。该模型由塔尔图大学计算机科学学院的自然语言处理研究小组tartuNLP训练。

该模型在测试集上实现了以下结果:

  • 损失:0.3565
  • 精确率:0.7612
  • 召回率:0.7744
  • F1值:0.7678
  • 准确率:0.9672

实体级别结果如下:

Precision Recall F1 Number
DATE 0.7278 0.7258 0.7268 372
EVENT 0.3721 0.5714 0.4507 28
GPE 0.8679 0.8369 0.8521 840
LOC 0.6545 0.4832 0.5560 149
MONEY 0.6625 0.6023 0.6310 88
ORG 0.6761 0.7267 0.7005 589
PER 0.8255 0.9068 0.8642 751
PERCENT 1.0 0.9589 0.9790 73
PROD 0.6030 0.5430 0.5714 221
TIME 0.5682 0.5556 0.5618 45
TITLE 0.7 0.8063 0.7494 191

如何使用

您可以使用Transformers NER流水线与此模型进行命名实体识别。由于该模型偶尔会将子词标记为实体,因此可能需要对结果进行后处理。

from transformers import BertTokenizer, BertForTokenClassification
from transformers import pipeline

tokenizer = BertTokenizer.from_pretrained('tartuNLP/EstBERT_NER')
bertner = BertForTokenClassification.from_pretrained('tartuNLP/EstBERT_NER')

nlp = pipeline("ner", model=bertner, tokenizer=tokenizer)

text = "Kaia Kanepi (WTA 57.) langes USA-s Charlestonis toimuval WTA 500 kategooria tenniseturniiril konkurentsist kaheksandikfinaalis, kaotades poolatarile Magda Linette'ile (WTA 64.) 3 : 6, 6 : 4, 2 : 6."

ner_results = nlp(text)

tokens=tokenizer(text)
tokens=tokenizer.convert_ids_to_tokens(tokens['input_ids'])


print(f'tokens: {tokens}')
print(f'NER model:{ner_results}')
tokens: ['[CLS]', 'kai', '##a', 'kanepi', '(', 'w', '##ta', '57', '.', ')', 'langes', 'usa', '-', 's', 'cha', '##rl', '##est', '##onis', 'toimuval', 'w', '##ta', '500', 'kategooria', 'tennise', '##turniiril', 'konkurentsist', 'kaheksandik', '##finaalis', ',', 'kaotades', 'poola', '##tari', '##le', 'ma', '##gda', 'line', '##tte', "'", 'ile', '(', 'w', '##ta', '64', '.', ')', '3', ':', '6', ',', '6', ':', '4', ',', '2', ':', '6', '.', '[SEP]']
NER model: [{'entity': 'B-PER', 'score': 0.99999887, 'index': 1, 'word': 'kai', 'start': None, 'end': None}, {'entity': 'B-PER', 'score': 0.97371966, 'index': 2, 'word': '##a', 'start': None, 'end': None}, {'entity': 'I-PER', 'score': 0.99999815, 'index': 3, 'word': 'kanepi', 'start': None, 'end': None}, {'entity': 'B-ORG', 'score': 0.63085276, 'index': 5, 'word': 'w', 'start': None, 'end': None}, {'entity': 'B-GPE', 'score': 0.99999934, 'index': 11, 'word': 'usa', 'start': None, 'end': None}, {'entity': 'B-GPE', 'score': 0.9999685, 'index': 14, 'word': 'cha', 'start': None, 'end': None}, {'entity': 'I-GPE', 'score': 0.8875574, 'index': 15, 'word': '##rl', 'start': None, 'end': None}, {'entity': 'I-GPE', 'score': 0.9996168, 'index': 16, 'word': '##est', 'start': None, 'end': None}, {'entity': 'I-GPE', 'score': 0.9992657, 'index': 17, 'word': '##onis', 'start': None, 'end': None}, {'entity': 'B-EVENT', 'score': 0.99999064, 'index': 19, 'word': 'w', 'start': None, 'end': None}, {'entity': 'I-EVENT', 'score': 0.9772493, 'index': 20, 'word': '##ta', 'start': None, 'end': None}, {'entity': 'I-EVENT', 'score': 0.99999076, 'index': 21, 'word': '500', 'start': None, 'end': None}, {'entity': 'I-EVENT', 'score': 0.99955636, 'index': 22, 'word': 'kategooria', 'start': None, 'end': None}, {'entity': 'B-TITLE', 'score': 0.8771319, 'index': 30, 'word': 'poola', 'start': None, 'end': None}, {'entity': 'B-PER', 'score': 0.99999785, 'index': 33, 'word': 'ma', 'start': None, 'end': None}, {'entity': 'B-PER', 'score': 0.9998398, 'index': 34, 'word': '##gda', 'start': None, 'end': None}, {'entity': 'I-PER', 'score': 0.9999987, 'index': 35, 'word': 'line', 'start': None, 'end': None}, {'entity': 'I-PER', 'score': 0.9999976, 'index': 36, 'word': '##tte', 'start': None, 'end': None}, {'entity': 'I-PER', 'score': 0.99999285, 'index': 37, 'word': "'", 'start': None, 'end': None}, {'entity': 'I-PER', 'score': 0.9999794, 'index': 38, 'word': 'ile', 'start': None, 'end': None}, {'entity': 'B-ORG', 'score': 0.7664479, 'index': 40, 'word': 'w', 'start': None, 'end': None}]

使用限制

该模型可用于查找爱沙尼亚文本中的命名实体。该模型对任何人都是免费使用的。tartuNLP不保证该模型对任何人或任何事物都是有用的。tartuNLP不对其生成的任何结果负责。

训练和评估数据

该模型是在两个爱沙尼亚NER数据集上进行训练的:

这两个数据集都使用相同的注释方案进行了注释。为了训练这个模型,这些数据集被合并。

训练过程

训练超参数

训练时使用了以下超参数:

  • 学习率:1e-05
  • 训练批量大小:16
  • 评估批量大小:16
  • 种子:1024
  • 优化器:Adam with betas=(0.9,0.98) and epsilon=1e-06
  • lr_scheduler_type:polynomial
  • 最大num_epochs:150
  • 早停限制:20
  • 早停容差:0.0001
  • 混合精度训练:Native AMP

训练结果

最终模型在第53轮(用粗体显示)保存,此时开发集上的整体F1值最高。

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy Date Precision Date Recall Date F1 Date Number Event Precision Event Recall Event F1 Event Number Gpe Precision Gpe Recall Gpe F1 Gpe Number Loc Precision Loc Recall Loc F1 Loc Number Money Precision Money Recall Money F1 Money Number Org Precision Org Recall Org F1 Org Number Per Precision Per Recall Per F1 Per Number Percent Precision Percent Recall Percent F1 Percent Number Prod Precision Prod Recall Prod F1 Prod Number Time Precision Time Recall Time F1 Time Number Title Precision Title Recall Title F1 Title Number Overall Precision Overall Recall Overall F1 Overall Accuracy
0.3252 1 1061 0.1628 0.6835 0.6083 0.6437 0.9526 0.5910 0.6022 0.5965 372 0.0 0.0 0.0 28 0.8073 0.7631 0.7846 840 0.1389 0.0336 0.0541 149 0.4217 0.3977 0.4094 88 0.5381 0.5280 0.5330 589 0.7917 0.8655 0.8270 751 0.6471 0.3014 0.4112 73 0.2581 0.0724 0.1131 221 0.1429 0.0889 0.1096 45 0.7805 0.6702 0.7211 191 0.6835 0.6083 0.6437 0.9526
0.1513 2 2122 0.1332 0.6906 0.7329 0.7111 0.9615 0.6185 0.7366 0.6724 372 0.0857 0.1071 0.0952 28 0.7874 0.8595 0.8219 840 0.4767 0.2752 0.3489 149 0.6848 0.7159 0.7000 88 0.6158 0.6231 0.6194 589 0.7770 0.9001 0.8341 751 0.9565 0.9041 0.9296 73 0.5 0.3620 0.4199 221 0.3571 0.3333 0.3448 45 0.6033 0.7644 0.6744 191 0.6906 0.7329 0.7111 0.9615
0.1131 3 3183 0.1281 0.7224 0.7338 0.7280 0.9638 0.7054 0.7339 0.7194 372 0.1053 0.1429 0.1212 28 0.8013 0.85 0.8250 840 0.5476 0.3087 0.3948 149 0.6386 0.6023 0.6199 88 0.6371 0.6469 0.6420 589 0.8235 0.8762 0.8490 751 0.9859 0.9589 0.9722 73 0.5148 0.3937 0.4462 221 0.5116 0.4889 0.5 45 0.6245 0.7749 0.6916 191 0.7224 0.7338 0.7280 0.9638
0.0884 4 4244 0.1354 0.7283 0.7386 0.7334 0.9639 0.6785 0.6694 0.6739 372 0.1795 0.25 0.2090 28 0.8231 0.8310 0.8270 840 0.6020 0.3960 0.4777 149 0.6092 0.6023 0.6057 88 0.6473 0.7012 0.6732 589 0.8351 0.8628 0.8487 751 1.0 0.9726 0.9861 73 0.5899 0.4751 0.5263 221 0.4524 0.4222 0.4368 45 0.6 0.7853 0.6803 191 0.7283 0.7386 0.7334 0.9639
0.0685 5 5305 0.1383 0.7224 0.7696 0.7453 0.9644 0.6635 0.7473 0.7029 372 0.26 0.4643 0.3333 28 0.8259 0.8357 0.8308 840 0.5913 0.4564 0.5152 149 0.6437 0.6364 0.64 88 0.6540 0.7284 0.6892 589 0.8070 0.8961 0.8492 751 0.9857 0.9452 0.9650 73 0.5693 0.5204 0.5437 221 0.5192 0.6 0.5567 45 0.6320 0.7644 0.6919 191 0.7224 0.7696 0.7453 0.9644
0.0532 6 6366 0.1493 0.7099 0.7613 0.7347 0.9631 0.6727 0.6962 0.6843 372 0.2308 0.5357 0.3226 28 0.8242 0.8262 0.8252 840 0.5877 0.4497 0.5095 149 0.6410 0.5682 0.6024 88 0.6232 0.7470 0.6795 589 0.8087 0.8895 0.8472 751 0.9672 0.8082 0.8806 73 0.5107 0.5385 0.5242 221 0.6190 0.5778 0.5977 45 0.6371 0.7906 0.7056 191 0.7099 0.7613 0.7347 0.9631
0.0403 7 7427 0.1592 0.7239 0.7592 0.7411 0.9642 0.6923 0.7016 0.6969 372 0.2857 0.5714 0.3810 28 0.8272 0.8262 0.8267 840 0.5752 0.4362 0.4962 149 0.6265 0.5909 0.6082 88 0.6402 0.6978 0.6677 589 0.8404 0.8762 0.8579 751 0.9859 0.9589 0.9722 73 0.5257 0.6018 0.5612 221 0.5870 0.6 0.5934 45 0.6235 0.8063 0.7032 191 0.7239 0.7592 0.7411 0.9642
0.0304 8 8488 0.1738 0.7301 0.7484 0.7392 0.9644 0.6866 0.6774 0.6820 372 0.3409 0.5357 0.4167 28 0.8393 0.8083 0.8235 840 0.5882 0.4698 0.5224 149 0.6429 0.6136 0.6279 88 0.6608 0.6978 0.6788 589 0.8268 0.8708 0.8482 751 0.9595 0.9726 0.9660 73 0.5351 0.5520 0.5434 221 0.5208 0.5556 0.5376 45 0.6204 0.7958 0.6972 191 0.7301 0.7484 0.7392 0.9644
0.0234 9 9549 0.1860 0.7248 0.7625 0.7432 0.9641 0.6947 0.7097 0.7021 372 0.2963 0.5714 0.3902 28 0.8317 0.8298 0.8308 840 0.5913 0.4564 0.5152 149 0.6118 0.5909 0.6012 88 0.6361 0.7063 0.6693 589 0.8410 0.8735 0.8570 751 0.9859 0.9589 0.9722 73 0.5212 0.6109 0.5625 221 0.5417 0.5778 0.5591 45 0.6414 0.7958 0.7103 191 0.7248 0.7625 0.7432 0.9641
0.0178 10 10610 0.2037 0.7434 0.7383 0.7408 0.9640 0.7159 0.6774 0.6961 372 0.2857 0.4286 0.3429 28 0.8333 0.8333 0.8333 840 0.6262 0.4497 0.5234 149 0.6324 0.4886 0.5513 88 0.6568 0.6757 0.6661 589 0.8291 0.8722 0.8501 751 1.0 0.8219 0.9023 73 0.5672 0.5158 0.5403 221 0.5 0.5333 0.5161 45 0.6952 0.7644 0.7282 191 0.7434 0.7383 0.7408 0.9640
0.0147 11 11671 0.2114 0.7440 0.7233 0.7335 0.9643 0.7009 0.6613 0.6805 372 0.3030 0.3571 0.3279 28 0.8352 0.8024 0.8185 840 0.6238 0.4228 0.504 149 0.65 0.5909 0.6190 88 0.6436 0.6469 0.6452 589 0.8407 0.8575 0.8490 751 0.9315 0.9315 0.9315 73 0.5812 0.5023 0.5388 221 0.5476 0.5111 0.5287 45 0.6835 0.7801 0.7286 191 0.7440 0.7233 0.7335 0.9643
0.0118 12 12732 0.2218 0.7331 0.7532 0.7430 0.9649 0.7119 0.6909 0.7012 372 0.3488 0.5357 0.4225 28 0.8325 0.8405 0.8365 840 0.5303 0.4698 0.4982 149 0.65 0.5909 0.6190 88 0.6690 0.6587 0.6638 589 0.8178 0.8908 0.8528 751 0.9677 0.8219 0.8889 73 0.5408 0.5701 0.5551 221 0.5102 0.5556 0.5319 45 0.6567 0.8010 0.7217 191 0.7331 0.7532 0.7430 0.9649
0.0093 13 13793 0.2283 0.7495 0.7359 0.7427 0.9644 0.7163 0.6989 0.7075 372 0.3810 0.5714 0.4571 28 0.8612 0.7905 0.8243 840 0.6111 0.4430 0.5136 149 0.6145 0.5795 0.5965 88 0.6775 0.6740 0.6757 589 0.8346 0.8802 0.8568 751 0.9710 0.9178 0.9437 73 0.5619 0.5339 0.5476 221 0.4 0.4889 0.4400 45 0.6812 0.7382 0.7085 191 0.7495 0.7359 0.7427 0.9644
0.0079 14 14854 0.2383 0.7371 0.7490 0.7430 0.9647 0.6727 0.7016 0.6868 372 0.3261 0.5357 0.4054 28 0.8453 0.8 0.8220 840 0.5963 0.4362 0.5039 149 0.625 0.5682 0.5952 88 0.6634 0.6927 0.6777 589 0.8433 0.8815 0.8620 751 0.9853 0.9178 0.9504 73 0.5427 0.5747 0.5582 221 0.5814 0.5556 0.5682 45 0.6513 0.8115 0.7226 191 0.7371 0.7490 0.7430 0.9647
0.0068 15 15915 0.2511 0.7255 0.7359 0.7306 0.9639 0.6826 0.6532 0.6676 372 0.3590 0.5 0.4179 28 0.8295 0.8167 0.8230 840 0.5263 0.4698 0.4965 149 0.6575 0.5455 0.5963 88 0.6549 0.6604 0.6577 589 0.8242 0.8802 0.8513 751 0.9833 0.8082 0.8872 73 0.5398 0.5520 0.5459 221 0.36 0.4 0.3789 45 0.6511 0.8010 0.7183 191 0.7255 0.7359 0.7306 0.9639
0.0061 16 16976 0.2497 0.7253 0.7690 0.7465 0.9648 0.6824 0.6989 0.6906 372 0.3333 0.5357 0.4110 28 0.8473 0.8321 0.8396 840 0.4583 0.5168 0.4858 149 0.6494 0.5682 0.6061 88 0.6556 0.7368 0.6938 589 0.8382 0.8828 0.8599 751 0.9841 0.8493 0.9118 73 0.5341 0.6380 0.5814 221 0.5 0.5333 0.5161 45 0.6622 0.7801 0.7163 191 0.7253 0.7690 0.7465 0.9648
0.0054 17 18037 0.2554 0.7323 0.7625 0.7471 0.9650 0.6870 0.6962 0.6916 372 0.3421 0.4643 0.3939 28 0.8463 0.8262 0.8361 840 0.5902 0.4832 0.5314 149 0.6753 0.5909 0.6303 88 0.6640 0.7148 0.6885 589 0.8317 0.8948 0.8621 751 0.9437 0.9178 0.9306 73 0.5210 0.5611 0.5403 221 0.5 0.5111 0.5055 45 0.6102 0.8115 0.6966 191 0.7323 0.7625 0.7471 0.9650
0.005 18 19098 0.2601 0.7273 0.7747 0.7503 0.9654 0.6970 0.7608 0.7275 372 0.2830 0.5357 0.3704 28 0.8320 0.8488 0.8403 840 0.5841 0.4430 0.5038 149 0.6477 0.6477 0.6477 88 0.6378 0.6995 0.6672 589 0.8501 0.8908 0.8700 751 0.9722 0.9589 0.9655 73 0.5323 0.5973 0.5629 221 0.4444 0.4444 0.4444 45 0.624 0.8168 0.7075 191 0.7273 0.7747 0.7503 0.9654
0.0044 19 20159 0.2602 0.7369 0.7616 0.7490 0.9656 0.7124 0.7124 0.7124 372 0.3415 0.5 0.4058 28 0.8239 0.8631 0.8430 840 0.6355 0.4564 0.5313 149 0.6667 0.6136 0.6391 88 0.6517 0.6638 0.6577 589 0.8405 0.8842 0.8618 751 0.9857 0.9452 0.9650 73 0.5144 0.5656 0.5388 221 0.5217 0.5333 0.5275 45 0.6550 0.7853 0.7143 191 0.7369 0.7616 0.7490 0.9656
0.004 20 21220 0.2677 0.7347 0.7702 0.7520 0.9658 0.7374 0.7097 0.7233 372 0.2857 0.4286 0.3429 28 0.8466 0.8345 0.8405 840 0.6050 0.4832 0.5373 149 0.6667 0.6136 0.6391 88 0.6593 0.7131 0.6852 589 0.8240 0.8975 0.8591 751 0.9857 0.9452 0.9650 73 0.4981 0.5837 0.5375 221 0.5102 0.5556 0.5319 45 0.6371 0.8272 0.7198 191 0.7347 0.7702 0.7520 0.9658
0.0034 21 22281 0.2743 0.7386 0.7717 0.7548 0.9657 0.6984 0.7097 0.704 372 0.3784 0.5 0.4308 28 0.8475 0.8333 0.8403 840 0.6333 0.5101 0.5651 149 0.6190 0.5909 0.6047 88 0.6512 0.7385 0.6921 589 0.8428 0.8921 0.8668 751 0.9846 0.8767 0.9275 73 0.5513 0.5837 0.5670 221 0.5106 0.5333 0.5217 45 0.6379 0.8115 0.7143 191 0.7386 0.7717 0.7548 0.9657
0.0033 22 23342 0.2788 0.7418 0.7520 0.7469 0.9652 0.7143 0.6989 0.7065 372 0.3182 0.5 0.3889 28 0.8367 0.8298 0.8332 840 0.6168 0.4430 0.5156 149 0.6235 0.6023 0.6127 88 0.6758 0.6689 0.6724 589 0.8327 0.8815 0.8564 751 0.9714 0.9315 0.9510 73 0.5458 0.5928 0.5683 221 0.4783 0.4889 0.4835 45 0.6637 0.7853 0.7194 191 0.7418 0.7520 0.7469 0.9652
0.0033 23 24403 0.2831 0.7342 0.7535 0.7437 0.9650 0.6981 0.6962 0.6972 372 0.3784 0.5 0.4308 28 0.8499 0.8024 0.8255 840 0.5034 0.4966 0.5 149 0.6067 0.6136 0.6102 88 0.6581 0.6961 0.6766 589 0.8350 0.8961 0.8645 751 0.9714 0.9315 0.9510 73 0.5424 0.5792 0.5602 221 0.3774 0.4444 0.4082 45 0.7048 0.7749 0.7382 191 0.7342 0.7535 0.7437 0.9650
0.0029 24 25464 0.2931 0.7544 0.7380 0.7461 0.9648 0.7365 0.6989 0.7172 372 0.3590 0.5 0.4179 28 0.8535 0.7976 0.8246 840 0.5849 0.4161 0.4863 149 0.6622 0.5568 0.6049 88 0.6672 0.6706 0.6689 589 0.8474 0.8802 0.8635 751 0.9701 0.8904 0.9286 73 0.5550 0.5475 0.5513 221 0.4889 0.4889 0.4889 45 0.7023 0.7906 0.7438 191 0.7544 0.7380 0.7461 0.9648
0.0028 25 26525 0.2899 0.7489 0.7574 0.7531 0.9654 0.7021 0.7097 0.7059 372 0.3902 0.5714 0.4638 28 0.8635 0.8131 0.8375 840 0.6182 0.4564 0.5251 149 0.6471 0.625 0.6358 88 0.6613 0.6995 0.6799 589 0.8454 0.9028 0.8731 751 0.9583 0.9452 0.9517 73 0.5681 0.5475 0.5576 221 0.4222 0.4222 0.4222 45 0.6608 0.7853 0.7177 191 0.7489 0.7574 0.7531 0.9654
0.0023 26 27586 0.2922 0.7413 0.7532 0.7472 0.9649 0.6897 0.6989 0.6943 372 0.35 0.5 0.4118 28 0.85 0.8298 0.8398 840 0.6161 0.4631 0.5287 149 0.6486 0.5455 0.5926 88 0.6486 0.6927 0.6700 589 0.8457 0.8828 0.8638 751 0.9853 0.9178 0.9504 73 0.5636 0.5611 0.5624 221 0.3958 0.4222 0.4086 45 0.6638 0.7958 0.7238 191 0.7413 0.7532 0.7472 0.9649
0.0021 27 28647 0.2967 0.7514 0.7568 0.7541 0.9656 0.7081 0.7043 0.7062 372 0.3659 0.5357 0.4348 28 0.8547 0.8190 0.8365 840 0.5641 0.4430 0.4962 149 0.6582 0.5909 0.6228 88 0.6677 0.7097 0.6881 589 0.8459 0.8842 0.8646 751 0.9710 0.9178 0.9437 73 0.5806 0.5701 0.5753 221 0.4898 0.5333 0.5106 45 0.7089 0.7906 0.7475 191 0.7514 0.7568 0.7541 0.9656
0.0025 28 29708 0.2957 0.7335 0.7622 0.7475 0.9651 0.7060 0.7231 0.7145 372 0.3077 0.4286 0.3582 28 0.8459 0.8429 0.8444 840 0.5069 0.4899 0.4983 149 0.6438 0.5341 0.5839 88 0.6838 0.7012 0.6924 589 0.8413 0.8895 0.8647 751 0.9552 0.8767 0.9143 73 0.4901 0.5611 0.5232 221 0.3818 0.4667 0.42 45 0.6580 0.7958 0.7204 191 0.7335 0.7622 0.7475 0.9651
0.0023 29 30769 0.3049 0.7455 0.7544 0.7499 0.9654 0.6997 0.7392 0.7190 372 0.3182 0.5 0.3889 28 0.8483 0.8119 0.8297 840 0.5630 0.5101 0.5352 149 0.6579 0.5682 0.6098 88 0.6791 0.7114 0.6949 589 0.8583 0.8628 0.8606 751 0.9853 0.9178 0.9504 73 0.5234 0.5566 0.5395 221 0.4565 0.4667 0.4615 45 0.7009 0.7853 0.7407 191 0.7455 0.7544 0.7499 0.9654
0.0018 30 31830 0.3042 0.7415 0.7679 0.7544 0.9654 0.6935 0.7419 0.7169 372 0.3333 0.5 0.4 28 0.8563 0.8226 0.8391 840 0.5878 0.5168 0.55 149 0.6582 0.5909 0.6228 88 0.6677 0.7470 0.7051 589 0.8544 0.8828 0.8684 751 0.9710 0.9178 0.9437 73 0.5300 0.5204 0.5251 221 0.4375 0.4667 0.4516 45 0.6417 0.8063 0.7146 191 0.7415 0.7679 0.7544 0.9654
0.0017 31 32891 0.3071 0.7540 0.7481 0.7510 0.9660 0.7083 0.7312 0.7196 372 0.4054 0.5357 0.4615 28 0.8552 0.8226 0.8386 840 0.6311 0.4362 0.5159 149 0.6220 0.5795 0.6 88 0.6734 0.6757 0.6746 589 0.8626 0.8775 0.8700 751 0.9855 0.9315 0.9577 73 0.5307 0.5475 0.5390 221 0.3830 0.4 0.3913 45 0.7019 0.7644 0.7318 191 0.7540 0.7481 0.7510 0.9660
0.0018 32 33952 0.3190 0.7499 0.7553 0.7526 0.9656 0.7182 0.7124 0.7152 372 0.3333 0.5357 0.4110 28 0.8586 0.7952 0.8257 840 0.6116 0.4966 0.5481 149 0.6463 0.6023 0.6235 88 0.6805 0.6978 0.6890 589 0.8360 0.8895 0.8619 751 0.9855 0.9315 0.9577 73 0.5633 0.5837 0.5733 221 0.5106 0.5333 0.5217 45 0.6711 0.8010 0.7303 191 0.7499 0.7553 0.7526 0.9656
0.0018 33 35013 0.3094 0.7460 0.7774 0.7614 0.9665 0.7147 0.7473 0.7306 372 0.3659 0.5357 0.4348 28 0.8556 0.8393 0.8474 840 0.6273 0.4631 0.5328 149 0.6506 0.6136 0.6316 88 0.6787 0.7351 0.7058 589 0.8344 0.8988 0.8654 751 0.9857 0.9452 0.9650 73 0.5702 0.6063 0.5877 221 0.3036 0.3778 0.3366 45 0.6567 0.8010 0.7217 191 0.7460 0.7774 0.7614 0.9665
0.0015 34 36074 0.3091 0.7441 0.7759 0.7597 0.9665 0.7113 0.7285 0.7198 372 0.3404 0.5714 0.4267 28 0.8266 0.8512 0.8387 840 0.5405 0.5369 0.5387 149 0.6707 0.625 0.6471 88 0.6856 0.7182 0.7015 589 0.8517 0.8868 0.8689 751 1.0 0.9452 0.9718 73 0.5752 0.5882 0.5817 221 0.3878 0.4222 0.4043 45 0.6830 0.8010 0.7373 191 0.7441 0.7759 0.7597 0.9665
0.0015 35 37135 0.3185 0.7487 0.7619 0.7552 0.9660 0.6982 0.7339 0.7156 372 0.3415 0.5 0.4058 28 0.8685 0.8179 0.8424 840 0.5504 0.4765 0.5108 149 0.6353 0.6136 0.6243 88 0.6636 0.7267 0.6937 589 0.8654 0.8815 0.8734 751 1.0 0.9315 0.9645 73 0.55 0.5475 0.5488 221 0.3673 0.4 0.3830 45 0.6937 0.8063 0.7458 191 0.7487 0.7619 0.7552 0.9660
0.0015 36 38196 0.3203 0.7438 0.7649 0.7542 0.9660 0.6961 0.7204 0.7081 372 0.3659 0.5357 0.4348 28 0.8617 0.8381 0.8497 840 0.5203 0.5168 0.5185 149 0.6667 0.5909 0.6265 88 0.6710 0.7063 0.6882 589 0.8495 0.8868 0.8678 751 0.9710 0.9178 0.9437 73 0.5561 0.5385 0.5471 221 0.42 0.4667 0.4421 45 0.6568 0.8115 0.7260 191 0.7438 0.7649 0.7542 0.9660
0.0013 37 39257 0.3298 0.7315 0.7732 0.7518 0.9656 0.6915 0.7231 0.7070 372 0.3333 0.5714 0.4211 28 0.8654 0.8190 0.8416 840 0.4793 0.5436 0.5094 149 0.6582 0.5909 0.6228 88 0.6656 0.7267 0.6948 589 0.8289 0.9028 0.8642 751 0.9857 0.9452 0.9650 73 0.5574 0.5928 0.5746 221 0.4043 0.4222 0.4130 45 0.6408 0.8220 0.7202 191 0.7315 0.7732 0.7518 0.9656
0.0012 38 40318 0.3311 0.7533 0.7610 0.7571 0.9664 0.7060 0.7231 0.7145 372 0.3571 0.5357 0.4286 28 0.8613 0.8357 0.8483 840 0.6339 0.4765 0.5441 149 0.6543 0.6023 0.6272 88 0.6528 0.7182 0.6839 589 0.8424 0.8828 0.8622 751 0.9857 0.9452 0.9650 73 0.6031 0.5294 0.5639 221 0.4130 0.4222 0.4176 45 0.7122 0.7644 0.7374 191 0.7533 0.7610 0.7571 0.9664
0.0012 39 41379 0.3328 0.7444 0.7553 0.7498 0.9657 0.6818 0.7258 0.7031 372 0.3478 0.5714 0.4324 28 0.8561 0.8143 0.8347 840 0.6055 0.4430 0.5116 149 0.6582 0.5909 0.6228 88 0.6715 0.7046 0.6877 589 0.8461 0.8708 0.8583 751 0.9706 0.9041 0.9362 73 0.5665 0.5973 0.5815 221 0.4082 0.4444 0.4255 45 0.6770 0.8010 0.7338 191 0.7444 0.7553 0.7498 0.9657
0.0014 40 42440 0.3415 0.7421 0.7437 0.7429 0.9641 0.6931 0.7043 0.6987 372 0.3488 0.5357 0.4225 28 0.8422 0.8262 0.8341 840 0.6190 0.4362 0.5118 149 0.6622 0.5568 0.6049 88 0.6888 0.6350 0.6608 589 0.8175 0.8828 0.8489 751 1.0 0.9178 0.9571 73 0.5584 0.5837 0.5708 221 0.4043 0.4222 0.4130 45 0.6580 0.7958 0.7204 191 0.7421 0.7437 0.7429 0.9641
0.0013 41 43501 0.3401 0.7501 0.7487 0.7494 0.9651 0.6915 0.7231 0.7070 372 0.3421 0.4643 0.3939 28 0.8545 0.8179 0.8358 840 0.6346 0.4430 0.5217 149 0.6812 0.5341 0.5987 88 0.6728 0.6808 0.6768 589 0.8380 0.8748 0.8560 751 0.9710 0.9178 0.9437 73 0.5860 0.5701 0.5780 221 0.4423 0.5111 0.4742 45 0.6787 0.7853 0.7282 191 0.7501 0.7487 0.7494 0.9651
0.0011 42 44562 0.3468 0.7426 0.7687 0.7554 0.9650 0.6965 0.7527 0.7235 372 0.3488 0.5357 0.4225 28 0.8667 0.8202 0.8428 840 0.6408 0.4430 0.5238 149 0.6709 0.6023 0.6347 88 0.6902 0.7148 0.7023 589 0.8404 0.8975 0.8680 751 0.9444 0.9315 0.9379 73 0.5191 0.6154 0.5631 221 0.3469 0.3778 0.3617 45 0.6210 0.8063 0.7016 191 0.7426 0.7687 0.7554 0.9650
0.0015 43 45623 0.3440 0.7566 0.7422 0.7493 0.9648 0.6937 0.7366 0.7145 372 0.3846 0.5357 0.4478 28 0.8608 0.8095 0.8344 840 0.6082 0.3960 0.4797 149 0.7 0.5568 0.6203 88 0.6766 0.6570 0.6667 589 0.8317 0.8881 0.8590 751 0.9701 0.8904 0.9286 73 0.6224 0.5520 0.5851 221 0.3913 0.4 0.3956 45 0.7081 0.7749 0.74 191 0.7566 0.7422 0.7493 0.9648
0.0011 44 46684 0.3354 0.7565 0.7640 0.7602 0.9664 0.7062 0.7366 0.7211 372 0.3659 0.5357 0.4348 28 0.8483 0.8452 0.8468 840 0.6095 0.4295 0.5039 149 0.6883 0.6023 0.6424 88 0.6880 0.6740 0.6810 589 0.8517 0.8948 0.8727 751 0.9710 0.9178 0.9437 73 0.6238 0.5928 0.6079 221 0.3830 0.4 0.3913 45 0.65 0.8168 0.7239 191 0.7565 0.7640 0.7602 0.9664
0.0011 45 47745 0.3347 0.7485 0.7622 0.7553 0.9655 0.7088 0.7392 0.7237 372 0.3636 0.5714 0.4444 28 0.8603 0.8286 0.8441 840 0.5882 0.4698 0.5224 149 0.6023 0.6023 0.6023 88 0.6770 0.6689 0.6729 589 0.8417 0.8921 0.8662 751 0.9857 0.9452 0.9650 73 0.6037 0.5928 0.5982 221 0.4583 0.4889 0.4731 45 0.6275 0.8115 0.7078 191 0.7485 0.7622 0.7553 0.9655
0.0011 46 48806 0.3421 0.7481 0.7640 0.7559 0.9657 0.7261 0.7339 0.7299 372 0.3171 0.4643 0.3768 28 0.8570 0.8202 0.8382 840 0.5691 0.4698 0.5147 149 0.6429 0.6136 0.6279 88 0.6769 0.7114 0.6937 589 0.8311 0.8908 0.8599 751 0.9857 0.9452 0.9650 73 0.5714 0.5611 0.5662 221 0.5 0.5556 0.5263 45 0.6638 0.7958 0.7238 191 0.7481 0.7640 0.7559 0.9657
0.0009 47 49867 0.3487 0.7496 0.7604 0.7550 0.9656 0.7158 0.7043 0.7100 372 0.3409 0.5357 0.4167 28 0.86 0.8190 0.8390 840 0.5496 0.4832 0.5143 149 0.7162 0.6023 0.6543 88 0.6745 0.7284 0.7004 589 0.8346 0.8802 0.8568 751 0.9857 0.9452 0.9650 73 0.5566 0.5339 0.5450 221 0.5349 0.5111 0.5227 45 0.6828 0.8115 0.7416 191 0.7496 0.7604 0.7550 0.9656
0.0009 48 50928 0.3470 0.7414 0.7649 0.7529 0.9651 0.7092 0.7473 0.7277 372 0.3333 0.5357 0.4110 28 0.8541 0.8226 0.8381 840 0.5847 0.4631 0.5169 149 0.6835 0.6136 0.6467 88 0.6801 0.7148 0.6970 589 0.8319 0.8895 0.8597 751 0.9571 0.9178 0.9371 73 0.5307 0.5475 0.5390 221 0.4583 0.4889 0.4731 45 0.6364 0.8063 0.7113 191 0.7414 0.7649 0.7529 0.9651
0.0011 49 51989 0.3389 0.7435 0.7664 0.7547 0.9659 0.6957 0.7312 0.7130 372 0.3590 0.5 0.4179 28 0.8561 0.8286 0.8421 840 0.6636 0.4899 0.5637 149 0.6136 0.6136 0.6136 88 0.6732 0.6995 0.6861 589 0.8251 0.8921 0.8573 751 0.9857 0.9452 0.9650 73 0.5746 0.5928 0.5835 221 0.4348 0.4444 0.4396 45 0.6390 0.8063 0.7130 191 0.7435 0.7664 0.7547 0.9659
0.0009 50 53050 0.3557 0.7490 0.7640 0.7564 0.9659 0.6948 0.6855 0.6901 372 0.3947 0.5357 0.4545 28 0.8584 0.8298 0.8438 840 0.6455 0.4765 0.5483 149 0.6933 0.5909 0.6380 88 0.6745 0.7317 0.7020 589 0.8296 0.8948 0.8610 751 0.9857 0.9452 0.9650 73 0.6082 0.5339 0.5687 221 0.4043 0.4222 0.4130 45 0.6270 0.8272 0.7133 191 0.7490 0.7640 0.7564 0.9659
0.0008 51 54111 0.3492 0.7516 0.7601 0.7558 0.9662 0.7104 0.6989 0.7046 372 0.3714 0.4643 0.4127 28 0.8545 0.8321 0.8432 840 0.6496 0.5101 0.5714 149 0.625 0.5682 0.5952 88 0.6722 0.6893 0.6806 589 0.8413 0.8895 0.8647 751 0.9857 0.9452 0.9650 73 0.5611 0.5611 0.5611 221 0.4792 0.5111 0.4946 45 0.6724 0.8168 0.7376 191 0.7516 0.7601 0.7558 0.9662
0.0008 52 55172 0.3432 0.7526 0.7625 0.7575 0.9661 0.7044 0.7366 0.7201 372 0.3571 0.5357 0.4286 28 0.8610 0.8262 0.8433 840 0.6140 0.4698 0.5323 149 0.6667 0.5909 0.6265 88 0.6766 0.6927 0.6846 589 0.8403 0.8895 0.8642 751 0.9857 0.9452 0.9650 73 0.5849 0.5611 0.5727 221 0.46 0.5111 0.4842 45 0.6681 0.8115 0.7329 191 0.7526 0.7625 0.7575 0.9661
0.0006 53 56233 0.3565 0.7615 0.7747 0.7681 0.9672 0.7305 0.7285 0.7295 372 0.3721 0.5714 0.4507 28 0.8679 0.8369 0.8521 840 0.6545 0.4832 0.5560 149 0.6625 0.6023 0.6310 88 0.6761 0.7267 0.7005 589 0.8255 0.9068 0.8642 751 1.0 0.9589 0.9790 73 0.6030 0.5430 0.5714 221 0.5682 0.5556 0.5618 45 0.7 0.8063 0.7494 191 0.7615 0.7747 0.7681 0.9672
0.0008 54 57294 0.3480 0.7590 0.7631 0.7610 0.9668 0.7452 0.7312 0.7381 372 0.3409 0.5357 0.4167 28 0.8589 0.8190 0.8385 840 0.5935 0.4899 0.5368 149 0.7027 0.5909 0.6420 88 0.6924 0.6842 0.6883 589 0.8432 0.8948 0.8682 751 0.9857 0.9452 0.9650 73 0.5856 0.5882 0.5869 221 0.5102 0.5556 0.5319 45 0.6513 0.8115 0.7226 191 0.7590 0.7631 0.7610 0.9668
0.0008 55 58355 0.3568 0.7601 0.7622 0.7612 0.9663 0.7228 0.7151 0.7189 372 0.3571 0.5357 0.4286 28 0.8429 0.8429 0.8429 840 0.6634 0.4497 0.536 149 0.7 0.5568 0.6203 88 0.6828 0.7165 0.6993 589 0.8655 0.8828 0.8741 751 0.9853 0.9178 0.9504 73 0.5909 0.5294 0.5585 221 0.5106 0.5333 0.5217 45 0.6429 0.8010 0.7133 191 0.7601 0.7622 0.7612 0.9663
0.0009 56 59416 0.3498 0.7542 0.7580 0.7561 0.9661 0.7178 0.7043 0.7110 372 0.3409 0.5357 0.4167 28 0.8379 0.8429 0.8404 840 0.6634 0.4497 0.536 149 0.6322 0.625 0.6286 88 0.6895 0.6825 0.6860 589 0.8513 0.8842 0.8674 751 0.9577 0.9315 0.9444 73 0.5613 0.5385 0.5497 221 0.5111 0.5111 0.5111 45 0.6667 0.8063 0.7299 191 0.7542 0.7580 0.7561 0.9661
0.0007 57 60477 0.3486 0.7479 0.7711 0.7593 0.9663 0.7143 0.7392 0.7266 372 0.3571 0.5357 0.4286 28 0.8417 0.8417 0.8417 840 0.5923 0.5168 0.5520 149 0.6667 0.6136 0.6391 88 0.6720 0.7165 0.6935 589 0.8562 0.8802 0.8680 751 0.9714 0.9315 0.9510 73 0.5670 0.5747 0.5708 221 0.4583 0.4889 0.4731 45 0.6623 0.8010 0.7251 191 0.7479 0.7711 0.7593 0.9663
0.0007 58 61538 0.3497 0.7539 0.7744 0.7640 0.9667 0.7143 0.7392 0.7266 372 0.3659 0.5357 0.4348 28 0.8449 0.8429 0.8439 840 0.6429 0.4832 0.5517 149 0.6667 0.5909 0.6265 88 0.6708 0.7267 0.6976 589 0.8499 0.8975 0.8731 751 0.9714 0.9315 0.9510 73 0.6108 0.5611 0.5849 221 0.5 0.4889 0.4944 45 0.6525 0.8063 0.7213 191 0.7539 0.7744 0.7640 0.9667
0.0008 59 62599 0.3581 0.7474 0.7762 0.7615 0.9662 0.7183 0.7473 0.7325 372 0.3409 0.5357 0.4167 28 0.8439 0.8429 0.8434 840 0.5467 0.5503 0.5485 149 0.6709 0.6023 0.6347 88 0.6693 0.7250 0.6960 589 0.8454 0.8881 0.8662 751 0.9714 0.9315 0.9510 73 0.5961 0.5475 0.5708 221 0.5 0.5333 0.5161 45 0.6769 0.8115 0.7381 191 0.7474 0.7762 0.7615 0.9662
0.0007 60 63660 0.3636 0.7494 0.7676 0.7584 0.9662 0.7016 0.7204 0.7109 372 0.3488 0.5357 0.4225 28 0.8489 0.8357 0.8422 840 0.6 0.4832 0.5353 149 0.6538 0.5795 0.6145 88 0.6828 0.7199 0.7008 589 0.8476 0.8815 0.8642 751 0.9714 0.9315 0.9510 73 0.5579 0.5882 0.5727 221 0.4762 0.4444 0.4598 45 0.6797 0.8220 0.7441 191 0.7494 0.7676 0.7584 0.9662
0.0008 61 64721 0.3646 0.7538 0.7574 0.7556 0.9660 0.6854 0.7204 0.7025 372 0.3659 0.5357 0.4348 28 0.8573 0.8369 0.8470 840 0.6306 0.4698 0.5385 149 0.6667 0.5909 0.6265 88 0.6896 0.6978 0.6937 589 0.8495 0.8722 0.8607 751 0.9714 0.9315 0.9510 73 0.5728 0.5520 0.5622 221 0.375 0.4 0.3871 45 0.6830 0.8010 0.7373 191 0.7538 0.7574 0.7556 0.9660
0.0006 62 65782 0.3697 0.7510 0.7460 0.7485 0.9651 0.6885 0.7070 0.6976 372 0.4286 0.5357 0.4762 28 0.8663 0.7869 0.8247 840 0.5902 0.4832 0.5314 149 0.6757 0.5682 0.6173 88 0.6667 0.6927 0.6794 589 0.8432 0.8948 0.8682 751 0.9851 0.9041 0.9429 73 0.5829 0.5566 0.5694 221 0.3673 0.4 0.3830 45 0.6995 0.7801 0.7376 191 0.7510 0.7460 0.7485 0.9651
0.0006 63 66843 0.3661 0.7504 0.7502 0.7503 0.9655 0.6909 0.6909 0.6909 372 0.4286 0.5357 0.4762 28 0.8571 0.8143 0.8352 840 0.5814 0.5034 0.5396 149 0.6582 0.5909 0.6228 88 0.7013 0.6655 0.6829 589 0.8348 0.8948 0.8638 751 0.9571 0.9178 0.9371 73 0.5570 0.5747 0.5657 221 0.3830 0.4 0.3913 45 0.6786 0.7958 0.7325 191 0.7504 0.7502 0.7503 0.9655
0.0006 64 67904 0.3711 0.7404 0.7628 0.7514 0.9656 0.6911 0.7097 0.7003 372 0.3784 0.5 0.4308 28 0.8455 0.8405 0.8430 840 0.6 0.5034 0.5474 149 0.65 0.5909 0.6190 88 0.6667 0.7029 0.6843 589 0.8350 0.8961 0.8645 751 0.9714 0.9315 0.9510 73 0.5673 0.5339 0.5501 221 0.2917 0.3111 0.3011 45 0.6568 0.8115 0.7260 191 0.7404 0.7628 0.7514 0.9656
0.0007 65 68965 0.3672 0.7377 0.7696 0.7533 0.9661 0.7005 0.7419 0.7206 372 0.3333 0.5357 0.4110 28 0.8433 0.8393 0.8413 840 0.5839 0.5369 0.5594 149 0.6506 0.6136 0.6316 88 0.6840 0.7131 0.6983 589 0.8412 0.8815 0.8609 751 0.9857 0.9452 0.9650 73 0.5427 0.5747 0.5582 221 0.3019 0.3556 0.3265 45 0.6360 0.7958 0.7070 191 0.7377 0.7696 0.7533 0.9661
0.0005 66 70026 0.3768 0.7496 0.7520 0.7508 0.9657 0.6903 0.7070 0.6985 372 0.3415 0.5 0.4058 28 0.8454 0.8333 0.8393 840 0.6372 0.4832 0.5496 149 0.6795 0.6023 0.6386 88 0.6914 0.6655 0.6782 589 0.8483 0.8788 0.8633 751 0.9577 0.9315 0.9444 73 0.5714 0.5792 0.5753 221 0.3 0.3333 0.3158 45 0.6696 0.7958 0.7273 191 0.7496 0.7520 0.7508 0.9657
0.0007 67 71087 0.3682 0.7461 0.7664 0.7561 0.9656 0.7094 0.7285 0.7188 372 0.3409 0.5357 0.4167 28 0.8563 0.8369 0.8465 840 0.6290 0.5235 0.5714 149 0.6974 0.6023 0.6463 88 0.6935 0.6876 0.6905 589 0.8363 0.8842 0.8595 751 0.9437 0.9178 0.9306 73 0.5175 0.6018 0.5565 221 0.4694 0.5111 0.4894 45 0.6483 0.8010 0.7166 191 0.7461 0.7664 0.7561 0.9656
0.0005 68 72148 0.3815 0.7590 0.7416 0.7502 0.9654 0.7092 0.7016 0.7054 372 0.4054 0.5357 0.4615 28 0.8489 0.8095 0.8288 840 0.6796 0.4698 0.5556 149 0.6456 0.5795 0.6108 88 0.6801 0.6570 0.6684 589 0.8476 0.8815 0.8642 751 0.9571 0.9178 0.9371 73 0.615 0.5566 0.5843 221 0.4348 0.4444 0.4396 45 0.6759 0.7644 0.7174 191 0.7590 0.7416 0.7502 0.9654
0.0006 69 73209 0.3919 0.7494 0.7487 0.7491 0.9650 0.6888 0.6962 0.6925 372 0.3590 0.5 0.4179 28 0.8416 0.8095 0.8252 840 0.5865 0.5235 0.5532 149 0.6901 0.5568 0.6164 88 0.6950 0.6808 0.6878 589 0.8490 0.8908 0.8694 751 1.0 0.9041 0.9496 73 0.5662 0.5611 0.5636 221 0.3265 0.3556 0.3404 45 0.6881 0.7853 0.7335 191 0.7494 0.7487 0.7491 0.9650
0.0006 70 74270 0.3704 0.7587 0.7619 0.7603 0.9666 0.6891 0.7151 0.7018 372 0.3947 0.5357 0.4545 28 0.8376 0.8536 0.8455 840 0.6697 0.4899 0.5659 149 0.6420 0.5909 0.6154 88 0.7018 0.6791 0.6903 589 0.8491 0.8842 0.8663 751 0.9857 0.9452 0.9650 73 0.6219 0.5656 0.5924 221 0.3913 0.4 0.3956 45 0.6802 0.7906 0.7312 191 0.7587 0.7619 0.7603 0.9666
0.0005 71 75331 0.3841 0.7501 0.7634 0.7567 0.9659 0.7005 0.6855 0.6929 372 0.4054 0.5357 0.4615 28 0.8531 0.8298 0.8413 840 0.6293 0.4899 0.5509 149 0.6410 0.5682 0.6024 88 0.6774 0.7165 0.6964 589 0.8264 0.9001 0.8617 751 0.9706 0.9041 0.9362 73 0.5882 0.5882 0.5882 221 0.4545 0.4444 0.4494 45 0.6864 0.7906 0.7348 191 0.7501 0.7634 0.7567 0.9659
0.0005 72 76392 0.3830 0.7605 0.7496 0.7550 0.9655 0.7036 0.6828 0.6930 372 0.3824 0.4643 0.4194 28 0.8618 0.8238 0.8424 840 0.6542 0.4698 0.5469 149 0.6582 0.5909 0.6228 88 0.6935 0.6723 0.6828 589 0.8476 0.8815 0.8642 751 0.9577 0.9315 0.9444 73 0.5830 0.5882 0.5856 221 0.4043 0.4222 0.4130 45 0.6892 0.8010 0.7409 191 0.7605 0.7496 0.7550 0.9655
0.0006 73 77453 0.3839 0.7611 0.7547 0.7579 0.9661 0.712 0.7177 0.7149 372 0.3429 0.4286 0.3810 28 0.8494 0.8393 0.8443 840 0.6542 0.4698 0.5469 149 0.6538 0.5795 0.6145 88 0.6877 0.6655 0.6764 589 0.8428 0.8921 0.8668 751 0.9710 0.9178 0.9437 73 0.6257 0.5294 0.5735 221 0.4468 0.4667 0.4565 45 0.6814 0.8063 0.7386 191 0.7611 0.7547 0.7579 0.9661

框架版本

  • Transformers 4.16.2
  • Pytorch 1.10.2+cu113
  • Datasets 1.18.3
  • Tokenizers 0.11.0