update model card README.md
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README.md
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| 1 |
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---
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license: cc-by-nc-sa-4.0
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tags:
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- generated_from_trainer
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datasets:
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- cord-layoutlmv3
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model-index:
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- name: layoutlmv2-finetuned-cord_500
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results: []
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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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# layoutlmv2-finetuned-cord_500
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This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on the cord-layoutlmv3 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2207
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- Menu.cnt Precision: 1.0
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| 21 |
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- Menu.cnt Recall: 0.9867
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| 22 |
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- Menu.cnt F1: 0.9933
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- Menu.cnt Number: 225
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| 24 |
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- Menu.discountprice Precision: 0.8889
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- Menu.discountprice Recall: 0.8
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| 26 |
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- Menu.discountprice F1: 0.8421
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- Menu.discountprice Number: 10
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| 28 |
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- Menu.etc Precision: 0.0
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| 29 |
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- Menu.etc Recall: 0.0
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| 30 |
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- Menu.etc F1: 0.0
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| 31 |
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- Menu.etc Number: 3
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- Menu.itemsubtotal Precision: 0.0
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| 33 |
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- Menu.itemsubtotal Recall: 0.0
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- Menu.itemsubtotal F1: 0.0
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| 35 |
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- Menu.itemsubtotal Number: 6
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| 36 |
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- Menu.nm Precision: 0.9764
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| 37 |
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- Menu.nm Recall: 0.9880
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| 38 |
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- Menu.nm F1: 0.9822
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- Menu.nm Number: 251
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- Menu.num Precision: 0.8462
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| 41 |
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- Menu.num Recall: 1.0
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| 42 |
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- Menu.num F1: 0.9167
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- Menu.num Number: 11
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- Menu.price Precision: 0.9723
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| 45 |
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- Menu.price Recall: 0.9919
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| 46 |
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- Menu.price F1: 0.9820
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| 47 |
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- Menu.price Number: 248
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- Menu.sub Cnt Precision: 0.85
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| 49 |
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- Menu.sub Cnt Recall: 1.0
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- Menu.sub Cnt F1: 0.9189
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| 51 |
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- Menu.sub Cnt Number: 17
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| 52 |
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- Menu.sub Nm Precision: 0.8421
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| 53 |
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- Menu.sub Nm Recall: 0.8649
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| 54 |
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- Menu.sub Nm F1: 0.8533
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- Menu.sub Nm Number: 37
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- Menu.sub Price Precision: 0.95
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| 57 |
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- Menu.sub Price Recall: 0.95
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| 58 |
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- Menu.sub Price F1: 0.9500
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| 59 |
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- Menu.sub Price Number: 20
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- Menu.unitprice Precision: 0.9855
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- Menu.unitprice Recall: 0.9855
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- Menu.unitprice F1: 0.9855
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- Menu.unitprice Number: 69
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- Sub Total.discount Price Precision: 0.8571
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- Sub Total.discount Price Recall: 0.8571
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- Sub Total.discount Price F1: 0.8571
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- Sub Total.discount Price Number: 7
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- Sub Total.etc Precision: 0.9231
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- Sub Total.etc Recall: 0.9231
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- Sub Total.etc F1: 0.9231
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- Sub Total.etc Number: 13
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- Sub Total.service Price Precision: 1.0
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| 73 |
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- Sub Total.service Price Recall: 1.0
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| 74 |
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- Sub Total.service Price F1: 1.0
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- Sub Total.service Price Number: 12
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- Sub Total.subtotal Price Precision: 0.9714
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- Sub Total.subtotal Price Recall: 0.9855
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- Sub Total.subtotal Price F1: 0.9784
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- Sub Total.subtotal Price Number: 69
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- Sub Total.tax Price Precision: 1.0
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| 81 |
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- Sub Total.tax Price Recall: 1.0
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| 82 |
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- Sub Total.tax Price F1: 1.0
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| 83 |
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- Sub Total.tax Price Number: 47
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| 84 |
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- Total.cashprice Precision: 1.0
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| 85 |
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- Total.cashprice Recall: 0.9167
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- Total.cashprice F1: 0.9565
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- Total.cashprice Number: 72
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- Total.changeprice Precision: 0.9672
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- Total.changeprice Recall: 1.0
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- Total.changeprice F1: 0.9833
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- Total.changeprice Number: 59
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- Total.creditcardprice Precision: 1.0
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- Total.creditcardprice Recall: 0.9412
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- Total.creditcardprice F1: 0.9697
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- Total.creditcardprice Number: 17
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- Total.emoneyprice Precision: 0.1667
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- Total.emoneyprice Recall: 0.5
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| 98 |
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- Total.emoneyprice F1: 0.25
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- Total.emoneyprice Number: 2
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- Total.menuqty Cnt Precision: 0.9667
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- Total.menuqty Cnt Recall: 1.0
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- Total.menuqty Cnt F1: 0.9831
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- Total.menuqty Cnt Number: 29
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- Total.menutype Cnt Precision: 1.0
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| 105 |
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- Total.menutype Cnt Recall: 0.7143
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| 106 |
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- Total.menutype Cnt F1: 0.8333
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| 107 |
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- Total.menutype Cnt Number: 7
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| 108 |
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- Total.total Etc Precision: 0.0
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| 109 |
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- Total.total Etc Recall: 0.0
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| 110 |
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- Total.total Etc F1: 0.0
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| 111 |
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- Total.total Etc Number: 4
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| 112 |
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- Total.total Price Precision: 0.9709
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| 113 |
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- Total.total Price Recall: 0.9901
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| 114 |
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- Total.total Price F1: 0.9804
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| 115 |
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- Total.total Price Number: 101
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| 116 |
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- Overall Precision: 0.9627
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| 117 |
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- Overall Recall: 0.9671
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- Overall F1: 0.9649
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- Overall Accuracy: 0.9690
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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: 5e-05
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- train_batch_size: 8
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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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- lr_scheduler_warmup_ratio: 0.1
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- training_steps: 3000
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Menu.cnt Precision | Menu.cnt Recall | Menu.cnt F1 | Menu.cnt Number | Menu.discountprice Precision | Menu.discountprice Recall | Menu.discountprice F1 | Menu.discountprice Number | Menu.etc Precision | Menu.etc Recall | Menu.etc F1 | Menu.etc Number | Menu.itemsubtotal Precision | Menu.itemsubtotal Recall | Menu.itemsubtotal F1 | Menu.itemsubtotal Number | Menu.nm Precision | Menu.nm Recall | Menu.nm F1 | Menu.nm Number | Menu.num Precision | Menu.num Recall | Menu.num F1 | Menu.num Number | Menu.price Precision | Menu.price Recall | Menu.price F1 | Menu.price Number | Menu.sub Cnt Precision | Menu.sub Cnt Recall | Menu.sub Cnt F1 | Menu.sub Cnt Number | Menu.sub Nm Precision | Menu.sub Nm Recall | Menu.sub Nm F1 | Menu.sub Nm Number | Menu.sub Price Precision | Menu.sub Price Recall | Menu.sub Price F1 | Menu.sub Price Number | Menu.unitprice Precision | Menu.unitprice Recall | Menu.unitprice F1 | Menu.unitprice Number | Sub Total.discount Price Precision | Sub Total.discount Price Recall | Sub Total.discount Price F1 | Sub Total.discount Price Number | Sub Total.etc Precision | Sub Total.etc Recall | Sub Total.etc F1 | Sub Total.etc Number | Sub Total.service Price Precision | Sub Total.service Price Recall | Sub Total.service Price F1 | Sub Total.service Price Number | Sub Total.subtotal Price Precision | Sub Total.subtotal Price Recall | Sub Total.subtotal Price F1 | Sub Total.subtotal Price Number | Sub Total.tax Price Precision | Sub Total.tax Price Recall | Sub Total.tax Price F1 | Sub Total.tax Price Number | Total.cashprice Precision | Total.cashprice Recall | Total.cashprice F1 | Total.cashprice Number | Total.changeprice Precision | Total.changeprice Recall | Total.changeprice F1 | Total.changeprice Number | Total.creditcardprice Precision | Total.creditcardprice Recall | Total.creditcardprice F1 | Total.creditcardprice Number | Total.emoneyprice Precision | Total.emoneyprice Recall | Total.emoneyprice F1 | Total.emoneyprice Number | Total.menuqty Cnt Precision | Total.menuqty Cnt Recall | Total.menuqty Cnt F1 | Total.menuqty Cnt Number | Total.menutype Cnt Precision | Total.menutype Cnt Recall | Total.menutype Cnt F1 | Total.menutype Cnt Number | Total.total Etc Precision | Total.total Etc Recall | Total.total Etc F1 | Total.total Etc Number | Total.total Price Precision | Total.total Price Recall | Total.total Price F1 | Total.total Price Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:------------------:|:---------------:|:-----------:|:---------------:|:----------------------------:|:-------------------------:|:---------------------:|:-------------------------:|:------------------:|:---------------:|:-----------:|:---------------:|:---------------------------:|:------------------------:|:--------------------:|:------------------------:|:-----------------:|:--------------:|:----------:|:--------------:|:------------------:|:---------------:|:-----------:|:---------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:---------------------:|:------------------:|:--------------:|:------------------:|:------------------------:|:---------------------:|:-----------------:|:---------------------:|:------------------------:|:---------------------:|:-----------------:|:---------------------:|:----------------------------------:|:-------------------------------:|:---------------------------:|:-------------------------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:---------------------------------:|:------------------------------:|:--------------------------:|:------------------------------:|:----------------------------------:|:-------------------------------:|:---------------------------:|:-------------------------------:|:-----------------------------:|:--------------------------:|:----------------------:|:--------------------------:|:-------------------------:|:----------------------:|:------------------:|:----------------------:|:---------------------------:|:------------------------:|:--------------------:|:------------------------:|:-------------------------------:|:----------------------------:|:------------------------:|:----------------------------:|:---------------------------:|:------------------------:|:--------------------:|:------------------------:|:---------------------------:|:------------------------:|:--------------------:|:------------------------:|:----------------------------:|:-------------------------:|:---------------------:|:-------------------------:|:-------------------------:|:----------------------:|:------------------:|:----------------------:|:---------------------------:|:------------------------:|:--------------------:|:------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
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| No log | 2.0 | 250 | 2.5018 | 0.85 | 0.9822 | 0.9113 | 225 | 0.0 | 0.0 | 0.0 | 10 | 0.0 | 0.0 | 0.0 | 3 | 0.0 | 0.0 | 0.0 | 6 | 0.8257 | 1.0 | 0.9045 | 251 | 0.0 | 0.0 | 0.0 | 11 | 0.8746 | 0.9839 | 0.9260 | 248 | 0.0 | 0.0 | 0.0 | 17 | 0.0 | 0.0 | 0.0 | 37 | 0.0 | 0.0 | 0.0 | 20 | 0.9296 | 0.9565 | 0.9429 | 69 | 0.0 | 0.0 | 0.0 | 7 | 0.0 | 0.0 | 0.0 | 13 | 0.0 | 0.0 | 0.0 | 12 | 0.8108 | 0.8696 | 0.8392 | 69 | 0.4719 | 0.8936 | 0.6176 | 47 | 0.7683 | 0.875 | 0.8182 | 72 | 0.8 | 0.8814 | 0.8387 | 59 | 0.0 | 0.0 | 0.0 | 17 | 0.0 | 0.0 | 0.0 | 2 | 0.4138 | 0.4138 | 0.4138 | 29 | 0.0 | 0.0 | 0.0 | 7 | 0.0 | 0.0 | 0.0 | 4 | 0.7323 | 0.9208 | 0.8158 | 101 | 0.7983 | 0.8263 | 0.8121 | 0.8255 |
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| 2.6537 | 4.0 | 500 | 1.3952 | 0.8805 | 0.9822 | 0.9286 | 225 | 0.7273 | 0.8 | 0.7619 | 10 | 0.0 | 0.0 | 0.0 | 3 | 0.0 | 0.0 | 0.0 | 6 | 0.8817 | 0.9801 | 0.9283 | 251 | 1.0 | 1.0 | 1.0 | 11 | 0.8547 | 0.9960 | 0.9199 | 248 | 0.0 | 0.0 | 0.0 | 17 | 0.4444 | 0.1081 | 0.1739 | 37 | 0.0 | 0.0 | 0.0 | 20 | 0.8608 | 0.9855 | 0.9189 | 69 | 0.0 | 0.0 | 0.0 | 7 | 0.0 | 0.0 | 0.0 | 13 | 0.3438 | 0.9167 | 0.5 | 12 | 0.8919 | 0.9565 | 0.9231 | 69 | 0.88 | 0.9362 | 0.9072 | 47 | 1.0 | 0.875 | 0.9333 | 72 | 0.9483 | 0.9322 | 0.9402 | 59 | 0.6522 | 0.8824 | 0.75 | 17 | 0.0 | 0.0 | 0.0 | 2 | 0.8286 | 1.0 | 0.9062 | 29 | 0.0 | 0.0 | 0.0 | 7 | 0.0 | 0.0 | 0.0 | 4 | 0.9684 | 0.9109 | 0.9388 | 101 | 0.8632 | 0.8832 | 0.8731 | 0.8947 |
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| 2.6537 | 6.0 | 750 | 0.7646 | 0.9170 | 0.9822 | 0.9485 | 225 | 0.5556 | 0.5 | 0.5263 | 10 | 0.0 | 0.0 | 0.0 | 3 | 0.0 | 0.0 | 0.0 | 6 | 0.9537 | 0.9841 | 0.9686 | 251 | 1.0 | 1.0 | 1.0 | 11 | 0.9385 | 0.9839 | 0.9606 | 248 | 0.0 | 0.0 | 0.0 | 17 | 0.8 | 0.8649 | 0.8312 | 37 | 1.0 | 0.55 | 0.7097 | 20 | 0.9306 | 0.9710 | 0.9504 | 69 | 0.75 | 0.8571 | 0.8000 | 7 | 0.6667 | 0.7692 | 0.7143 | 13 | 0.8571 | 1.0 | 0.9231 | 12 | 0.9067 | 0.9855 | 0.9444 | 69 | 0.9787 | 0.9787 | 0.9787 | 47 | 1.0 | 0.9167 | 0.9565 | 72 | 0.9516 | 1.0 | 0.9752 | 59 | 0.7619 | 0.9412 | 0.8421 | 17 | 0.0 | 0.0 | 0.0 | 2 | 0.7632 | 1.0 | 0.8657 | 29 | 0.0 | 0.0 | 0.0 | 7 | 0.0 | 0.0 | 0.0 | 4 | 0.97 | 0.9604 | 0.9652 | 101 | 0.9244 | 0.9334 | 0.9289 | 0.9435 |
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| 0.8368 | 8.0 | 1000 | 0.4986 | 0.9567 | 0.9822 | 0.9693 | 225 | 0.8889 | 0.8 | 0.8421 | 10 | 0.0 | 0.0 | 0.0 | 3 | 0.0 | 0.0 | 0.0 | 6 | 0.9764 | 0.9880 | 0.9822 | 251 | 0.7333 | 1.0 | 0.8462 | 11 | 0.9648 | 0.9960 | 0.9802 | 248 | 1.0 | 0.6471 | 0.7857 | 17 | 0.8718 | 0.9189 | 0.8947 | 37 | 1.0 | 0.85 | 0.9189 | 20 | 0.9718 | 1.0 | 0.9857 | 69 | 0.5556 | 0.7143 | 0.6250 | 7 | 0.8889 | 0.6154 | 0.7273 | 13 | 1.0 | 1.0 | 1.0 | 12 | 0.8831 | 0.9855 | 0.9315 | 69 | 1.0 | 0.9787 | 0.9892 | 47 | 1.0 | 0.8889 | 0.9412 | 72 | 0.9831 | 0.9831 | 0.9831 | 59 | 0.5333 | 0.9412 | 0.6809 | 17 | 0.0 | 0.0 | 0.0 | 2 | 0.8056 | 1.0 | 0.8923 | 29 | 0.0 | 0.0 | 0.0 | 7 | 0.0 | 0.0 | 0.0 | 4 | 0.9694 | 0.9406 | 0.9548 | 101 | 0.9420 | 0.9484 | 0.9452 | 0.9520 |
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| 0.8368 | 10.0 | 1250 | 0.3597 | 0.9528 | 0.9867 | 0.9694 | 225 | 0.8889 | 0.8 | 0.8421 | 10 | 0.0 | 0.0 | 0.0 | 3 | 0.0 | 0.0 | 0.0 | 6 | 0.9688 | 0.9880 | 0.9783 | 251 | 0.7333 | 1.0 | 0.8462 | 11 | 0.9462 | 0.9919 | 0.9685 | 248 | 1.0 | 0.5294 | 0.6923 | 17 | 0.825 | 0.8919 | 0.8571 | 37 | 1.0 | 0.65 | 0.7879 | 20 | 0.9718 | 1.0 | 0.9857 | 69 | 1.0 | 1.0 | 1.0 | 7 | 0.8667 | 1.0 | 0.9286 | 13 | 1.0 | 1.0 | 1.0 | 12 | 0.9324 | 1.0 | 0.9650 | 69 | 1.0 | 0.9787 | 0.9892 | 47 | 1.0 | 0.9306 | 0.9640 | 72 | 0.9516 | 1.0 | 0.9752 | 59 | 0.8889 | 0.9412 | 0.9143 | 17 | 0.25 | 0.5 | 0.3333 | 2 | 0.9667 | 1.0 | 0.9831 | 29 | 1.0 | 0.7143 | 0.8333 | 7 | 0.0 | 0.0 | 0.0 | 4 | 0.9898 | 0.9604 | 0.9749 | 101 | 0.9524 | 0.9581 | 0.9552 | 0.9660 |
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| 157 |
+
| 0.3287 | 12.0 | 1500 | 0.3021 | 0.9864 | 0.9644 | 0.9753 | 225 | 0.8889 | 0.8 | 0.8421 | 10 | 0.0 | 0.0 | 0.0 | 3 | 0.0 | 0.0 | 0.0 | 6 | 0.9839 | 0.9761 | 0.98 | 251 | 0.7333 | 1.0 | 0.8462 | 11 | 0.9755 | 0.9637 | 0.9696 | 248 | 0.7727 | 1.0 | 0.8718 | 17 | 0.7556 | 0.9189 | 0.8293 | 37 | 0.7917 | 0.95 | 0.8636 | 20 | 0.9855 | 0.9855 | 0.9855 | 69 | 1.0 | 1.0 | 1.0 | 7 | 0.8667 | 1.0 | 0.9286 | 13 | 1.0 | 1.0 | 1.0 | 12 | 0.8947 | 0.9855 | 0.9379 | 69 | 1.0 | 0.9787 | 0.9892 | 47 | 1.0 | 0.9306 | 0.9640 | 72 | 0.9516 | 1.0 | 0.9752 | 59 | 0.8889 | 0.9412 | 0.9143 | 17 | 0.5 | 1.0 | 0.6667 | 2 | 0.9667 | 1.0 | 0.9831 | 29 | 1.0 | 0.7143 | 0.8333 | 7 | 0.0 | 0.0 | 0.0 | 4 | 0.9802 | 0.9802 | 0.9802 | 101 | 0.9553 | 0.9588 | 0.9570 | 0.9652 |
|
| 158 |
+
| 0.3287 | 14.0 | 1750 | 0.2756 | 0.9825 | 0.9956 | 0.9890 | 225 | 0.8889 | 0.8 | 0.8421 | 10 | 0.0 | 0.0 | 0.0 | 3 | 0.0 | 0.0 | 0.0 | 6 | 0.9650 | 0.9880 | 0.9764 | 251 | 0.9167 | 1.0 | 0.9565 | 11 | 0.9762 | 0.9919 | 0.9840 | 248 | 1.0 | 0.8824 | 0.9375 | 17 | 0.8889 | 0.8649 | 0.8767 | 37 | 0.95 | 0.95 | 0.9500 | 20 | 0.9855 | 0.9855 | 0.9855 | 69 | 0.875 | 1.0 | 0.9333 | 7 | 0.9091 | 0.7692 | 0.8333 | 13 | 1.0 | 1.0 | 1.0 | 12 | 0.9189 | 0.9855 | 0.9510 | 69 | 1.0 | 0.9787 | 0.9892 | 47 | 1.0 | 0.9306 | 0.9640 | 72 | 0.9516 | 1.0 | 0.9752 | 59 | 0.9412 | 0.9412 | 0.9412 | 17 | 0.3333 | 0.5 | 0.4 | 2 | 0.9667 | 1.0 | 0.9831 | 29 | 1.0 | 0.7143 | 0.8333 | 7 | 0.0 | 0.0 | 0.0 | 4 | 0.9612 | 0.9802 | 0.9706 | 101 | 0.9648 | 0.9656 | 0.9652 | 0.9656 |
|
| 159 |
+
| 0.1835 | 16.0 | 2000 | 0.2440 | 0.9955 | 0.9867 | 0.9911 | 225 | 0.8889 | 0.8 | 0.8421 | 10 | 0.0 | 0.0 | 0.0 | 3 | 0.0 | 0.0 | 0.0 | 6 | 0.9688 | 0.9880 | 0.9783 | 251 | 0.9167 | 1.0 | 0.9565 | 11 | 0.9762 | 0.9919 | 0.9840 | 248 | 0.85 | 1.0 | 0.9189 | 17 | 0.8684 | 0.8919 | 0.88 | 37 | 1.0 | 0.95 | 0.9744 | 20 | 0.9853 | 0.9710 | 0.9781 | 69 | 1.0 | 1.0 | 1.0 | 7 | 0.9286 | 1.0 | 0.9630 | 13 | 1.0 | 1.0 | 1.0 | 12 | 0.9444 | 0.9855 | 0.9645 | 69 | 1.0 | 0.9787 | 0.9892 | 47 | 0.9851 | 0.9167 | 0.9496 | 72 | 0.9672 | 1.0 | 0.9833 | 59 | 0.9412 | 0.9412 | 0.9412 | 17 | 0.4 | 1.0 | 0.5714 | 2 | 0.9667 | 1.0 | 0.9831 | 29 | 1.0 | 0.7143 | 0.8333 | 7 | 0.0 | 0.0 | 0.0 | 4 | 0.9712 | 1.0 | 0.9854 | 101 | 0.9679 | 0.9693 | 0.9686 | 0.9720 |
|
| 160 |
+
| 0.1835 | 18.0 | 2250 | 0.2300 | 0.9912 | 0.9956 | 0.9933 | 225 | 0.8 | 0.8 | 0.8000 | 10 | 0.0 | 0.0 | 0.0 | 3 | 0.0 | 0.0 | 0.0 | 6 | 0.9764 | 0.9880 | 0.9822 | 251 | 0.7857 | 1.0 | 0.88 | 11 | 0.9762 | 0.9919 | 0.9840 | 248 | 0.9444 | 1.0 | 0.9714 | 17 | 0.8205 | 0.8649 | 0.8421 | 37 | 0.95 | 0.95 | 0.9500 | 20 | 0.9855 | 0.9855 | 0.9855 | 69 | 0.8571 | 0.8571 | 0.8571 | 7 | 0.9231 | 0.9231 | 0.9231 | 13 | 1.0 | 1.0 | 1.0 | 12 | 0.9577 | 0.9855 | 0.9714 | 69 | 1.0 | 1.0 | 1.0 | 47 | 1.0 | 0.9028 | 0.9489 | 72 | 0.9672 | 1.0 | 0.9833 | 59 | 0.9412 | 0.9412 | 0.9412 | 17 | 0.1667 | 0.5 | 0.25 | 2 | 0.9667 | 1.0 | 0.9831 | 29 | 1.0 | 0.7143 | 0.8333 | 7 | 0.0 | 0.0 | 0.0 | 4 | 0.9709 | 0.9901 | 0.9804 | 101 | 0.9628 | 0.9678 | 0.9653 | 0.9690 |
|
| 161 |
+
| 0.1239 | 20.0 | 2500 | 0.2151 | 1.0 | 0.9867 | 0.9933 | 225 | 0.8889 | 0.8 | 0.8421 | 10 | 0.0 | 0.0 | 0.0 | 3 | 0.0 | 0.0 | 0.0 | 6 | 0.9724 | 0.9841 | 0.9782 | 251 | 0.8462 | 1.0 | 0.9167 | 11 | 0.98 | 0.9879 | 0.9839 | 248 | 0.85 | 1.0 | 0.9189 | 17 | 0.85 | 0.9189 | 0.8831 | 37 | 0.8636 | 0.95 | 0.9048 | 20 | 0.9855 | 0.9855 | 0.9855 | 69 | 0.8571 | 0.8571 | 0.8571 | 7 | 0.9231 | 0.9231 | 0.9231 | 13 | 1.0 | 1.0 | 1.0 | 12 | 0.9444 | 0.9855 | 0.9645 | 69 | 1.0 | 0.9787 | 0.9892 | 47 | 1.0 | 0.9167 | 0.9565 | 72 | 0.9672 | 1.0 | 0.9833 | 59 | 0.9412 | 0.9412 | 0.9412 | 17 | 0.1667 | 0.5 | 0.25 | 2 | 1.0 | 0.9655 | 0.9825 | 29 | 0.8571 | 0.8571 | 0.8571 | 7 | 0.0 | 0.0 | 0.0 | 4 | 0.9709 | 0.9901 | 0.9804 | 101 | 0.9620 | 0.9663 | 0.9642 | 0.9690 |
|
| 162 |
+
| 0.1239 | 22.0 | 2750 | nan | 1.0 | 0.9778 | 0.9888 | 225 | 0.8889 | 0.8 | 0.8421 | 10 | 0.0 | 0.0 | 0.0 | 3 | 0.0 | 0.0 | 0.0 | 6 | 0.9723 | 0.9801 | 0.9762 | 251 | 0.8462 | 1.0 | 0.9167 | 11 | 0.9721 | 0.9839 | 0.9780 | 248 | 0.85 | 1.0 | 0.9189 | 17 | 0.8611 | 0.8378 | 0.8493 | 37 | 0.95 | 0.95 | 0.9500 | 20 | 0.9851 | 0.9565 | 0.9706 | 69 | 0.8333 | 0.7143 | 0.7692 | 7 | 0.9231 | 0.9231 | 0.9231 | 13 | 1.0 | 1.0 | 1.0 | 12 | 0.9710 | 0.9710 | 0.9710 | 69 | 1.0 | 1.0 | 1.0 | 47 | 1.0 | 0.9028 | 0.9489 | 72 | 0.9667 | 0.9831 | 0.9748 | 59 | 1.0 | 0.9412 | 0.9697 | 17 | 0.1667 | 0.5 | 0.25 | 2 | 1.0 | 1.0 | 1.0 | 29 | 1.0 | 0.8571 | 0.9231 | 7 | 0.0 | 0.0 | 0.0 | 4 | 0.9706 | 0.9802 | 0.9754 | 101 | 0.9624 | 0.9573 | 0.9598 | 0.9575 |
|
| 163 |
+
| 0.1008 | 24.0 | 3000 | 0.2207 | 1.0 | 0.9867 | 0.9933 | 225 | 0.8889 | 0.8 | 0.8421 | 10 | 0.0 | 0.0 | 0.0 | 3 | 0.0 | 0.0 | 0.0 | 6 | 0.9764 | 0.9880 | 0.9822 | 251 | 0.8462 | 1.0 | 0.9167 | 11 | 0.9723 | 0.9919 | 0.9820 | 248 | 0.85 | 1.0 | 0.9189 | 17 | 0.8421 | 0.8649 | 0.8533 | 37 | 0.95 | 0.95 | 0.9500 | 20 | 0.9855 | 0.9855 | 0.9855 | 69 | 0.8571 | 0.8571 | 0.8571 | 7 | 0.9231 | 0.9231 | 0.9231 | 13 | 1.0 | 1.0 | 1.0 | 12 | 0.9714 | 0.9855 | 0.9784 | 69 | 1.0 | 1.0 | 1.0 | 47 | 1.0 | 0.9167 | 0.9565 | 72 | 0.9672 | 1.0 | 0.9833 | 59 | 1.0 | 0.9412 | 0.9697 | 17 | 0.1667 | 0.5 | 0.25 | 2 | 0.9667 | 1.0 | 0.9831 | 29 | 1.0 | 0.7143 | 0.8333 | 7 | 0.0 | 0.0 | 0.0 | 4 | 0.9709 | 0.9901 | 0.9804 | 101 | 0.9627 | 0.9671 | 0.9649 | 0.9690 |
|
| 164 |
+
|
| 165 |
+
|
| 166 |
+
### Framework versions
|
| 167 |
+
|
| 168 |
+
- Transformers 4.21.2
|
| 169 |
+
- Pytorch 1.10.0+cu111
|
| 170 |
+
- Datasets 2.4.0
|
| 171 |
+
- Tokenizers 0.12.1
|