File size: 24,350 Bytes
01660b0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 |
---
tags:
- generated_from_trainer
model-index:
- name: layoutlm-donut-own
results: []
---
<!-- 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. -->
# layoutlm-donut-own
This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3438
- Ban: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
- Eader:client: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44}
- Eader:client Tax Id: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44}
- Eader:iban: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44}
- Eader:invoice Date: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44}
- Eader:invoice No: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44}
- Eader:seller: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44}
- Eader:seller Tax Id: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 43}
- Eller: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
- Eller Tax Id: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
- Lient: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
- Lient Tax Id: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
- Nvoice Date: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
- Nvoice No: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
- Otal Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
- Otal Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
- Otal Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
- Tem Desc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}
- Tem Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}
- Tem Net Price: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}
- Tem Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}
- Tem Qty: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}
- Tem Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}
- Tems Row1:item Desc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44}
- Tems Row1:item Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44}
- Tems Row1:item Net Price: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44}
- Tems Row1:item Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 43}
- Tems Row1:item Qty: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 45}
- Tems Row1:item Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 43}
- Tems Row1:seller Tax Id: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
- Tems Row2:item Desc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 39}
- Tems Row2:item Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 39}
- Tems Row2:item Net Price: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 38}
- Tems Row2:item Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 39}
- Tems Row2:item Qty: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 40}
- Tems Row2:item Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 38}
- Tems Row3:item Desc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 32}
- Tems Row3:item Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 32}
- Tems Row3:item Net Price: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 32}
- Tems Row3:item Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 32}
- Tems Row3:item Qty: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 33}
- Tems Row3:item Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 31}
- Tems Row4:item Desc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}
- Tems Row4:item Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}
- Tems Row4:item Net Price: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}
- Tems Row4:item Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26}
- Tems Row4:item Qty: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 27}
- Tems Row4:item Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 25}
- Tems Row5:item Desc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21}
- Tems Row5:item Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21}
- Tems Row5:item Net Price: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21}
- Tems Row5:item Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21}
- Tems Row5:item Qty: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22}
- Tems Row5:item Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 20}
- Tems Row6:item Desc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17}
- Tems Row6:item Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17}
- Tems Row6:item Net Price: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17}
- Tems Row6:item Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17}
- Tems Row6:item Qty: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17}
- Tems Row6:item Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17}
- Tems Row7:item Desc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11}
- Tems Row7:item Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11}
- Tems Row7:item Net Price: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11}
- Tems Row7:item Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11}
- Tems Row7:item Qty: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11}
- Tems Row7:item Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 10}
- Ther: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 609}
- Ummary:total Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44}
- Ummary:total Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44}
- Ummary:total Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44}
- Overall Precision: 0.0
- Overall Recall: 0.0
- Overall F1: 0.0
- Overall Accuracy: 0.5689
## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Ban | Eader:client | Eader:client Tax Id | Eader:iban | Eader:invoice Date | Eader:invoice No | Eader:seller | Eader:seller Tax Id | Eller | Eller Tax Id | Lient | Lient Tax Id | Nvoice Date | Nvoice No | Otal Gross Worth | Otal Net Worth | Otal Vat | Tem Desc | Tem Gross Worth | Tem Net Price | Tem Net Worth | Tem Qty | Tem Vat | Tems Row1:item Desc | Tems Row1:item Gross Worth | Tems Row1:item Net Price | Tems Row1:item Net Worth | Tems Row1:item Qty | Tems Row1:item Vat | Tems Row1:seller Tax Id | Tems Row2:item Desc | Tems Row2:item Gross Worth | Tems Row2:item Net Price | Tems Row2:item Net Worth | Tems Row2:item Qty | Tems Row2:item Vat | Tems Row3:item Desc | Tems Row3:item Gross Worth | Tems Row3:item Net Price | Tems Row3:item Net Worth | Tems Row3:item Qty | Tems Row3:item Vat | Tems Row4:item Desc | Tems Row4:item Gross Worth | Tems Row4:item Net Price | Tems Row4:item Net Worth | Tems Row4:item Qty | Tems Row4:item Vat | Tems Row5:item Desc | Tems Row5:item Gross Worth | Tems Row5:item Net Price | Tems Row5:item Net Worth | Tems Row5:item Qty | Tems Row5:item Vat | Tems Row6:item Desc | Tems Row6:item Gross Worth | Tems Row6:item Net Price | Tems Row6:item Net Worth | Tems Row6:item Qty | Tems Row6:item Vat | Tems Row7:item Desc | Tems Row7:item Gross Worth | Tems Row7:item Net Price | Tems Row7:item Net Worth | Tems Row7:item Qty | Tems Row7:item Vat | Ther | Ummary:total Gross Worth | Ummary:total Net Worth | Ummary:total Vat | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:---------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:-----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 3.6109 | 1.0 | 7 | 2.7573 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 43} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 43} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 45} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 43} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 39} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 39} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 38} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 39} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 40} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 38} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 32} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 32} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 32} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 32} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 33} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 31} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 27} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 25} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 20} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 10} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 609} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | 0.0 | 0.0 | 0.0 | 0.5689 |
| 2.5323 | 2.0 | 14 | 2.3438 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 43} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 43} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 45} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 43} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 39} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 39} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 38} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 39} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 40} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 38} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 32} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 32} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 32} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 32} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 33} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 31} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 27} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 25} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 20} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 10} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 609} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} | 0.0 | 0.0 | 0.0 | 0.5689 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
|