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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: layoutlm-donut-own |
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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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# layoutlm-donut-own |
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This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3438 |
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- Ban: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} |
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- Eader:client: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} |
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- Eader:client Tax Id: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} |
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- Eader:iban: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} |
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- Eader:invoice Date: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} |
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- Eader:invoice No: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} |
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- Eader:seller: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} |
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- Eader:seller Tax Id: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 43} |
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- Eller: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} |
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- Eller Tax Id: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} |
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- Lient: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} |
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- Lient Tax Id: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} |
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- Nvoice Date: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} |
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- Nvoice No: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} |
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- Otal Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} |
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- Otal Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} |
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- Otal Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} |
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- Tem Desc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} |
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- Tem Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} |
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- Tem Net Price: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} |
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- Tem Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} |
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- Tem Qty: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} |
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- Tem Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} |
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- Tems Row1:item Desc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} |
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- Tems Row1:item Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} |
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- Tems Row1:item Net Price: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} |
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- Tems Row1:item Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 43} |
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- Tems Row1:item Qty: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 45} |
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- Tems Row1:item Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 43} |
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- Tems Row1:seller Tax Id: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} |
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- Tems Row2:item Desc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 39} |
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- Tems Row2:item Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 39} |
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- Tems Row2:item Net Price: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 38} |
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- Tems Row2:item Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 39} |
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- Tems Row2:item Qty: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 40} |
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- Tems Row2:item Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 38} |
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- Tems Row3:item Desc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 32} |
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- Tems Row3:item Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 32} |
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- Tems Row3:item Net Price: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 32} |
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- Tems Row3:item Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 32} |
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- Tems Row3:item Qty: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 33} |
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- Tems Row3:item Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 31} |
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- Tems Row4:item Desc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26} |
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- Tems Row4:item Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26} |
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- Tems Row4:item Net Price: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26} |
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- Tems Row4:item Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 26} |
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- Tems Row4:item Qty: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 27} |
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- Tems Row4:item Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 25} |
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- Tems Row5:item Desc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21} |
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- Tems Row5:item Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21} |
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- Tems Row5:item Net Price: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21} |
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- Tems Row5:item Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21} |
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- Tems Row5:item Qty: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22} |
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- Tems Row5:item Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 20} |
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- Tems Row6:item Desc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} |
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- Tems Row6:item Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} |
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- Tems Row6:item Net Price: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} |
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- Tems Row6:item Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} |
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- Tems Row6:item Qty: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} |
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- Tems Row6:item Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} |
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- Tems Row7:item Desc: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11} |
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- Tems Row7:item Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11} |
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- Tems Row7:item Net Price: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11} |
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- Tems Row7:item Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11} |
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- Tems Row7:item Qty: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 11} |
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- Tems Row7:item Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 10} |
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- Ther: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 609} |
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- Ummary:total Gross Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} |
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- Ummary:total Net Worth: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} |
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- Ummary:total Vat: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 44} |
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- Overall Precision: 0.0 |
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- Overall Recall: 0.0 |
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- Overall F1: 0.0 |
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- Overall Accuracy: 0.5689 |
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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: 3e-05 |
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- train_batch_size: 16 |
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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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- num_epochs: 2 |
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### Training results |
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| 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 | |
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| 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 | |
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| 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 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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