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--- |
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library_name: transformers |
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license: cc-by-nc-sa-4.0 |
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base_model: NLPmonster/layoutlmv3-for-receipt-understanding |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: layoutlmv3-for-complete-receipt-understanding |
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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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# layoutlmv3-for-complete-receipt-understanding |
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This model is a fine-tuned version of [NLPmonster/layoutlmv3-for-receipt-understanding](https://huggingface.co/NLPmonster/layoutlmv3-for-receipt-understanding) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4421 |
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- Precision: 0.6502 |
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- Recall: 0.6607 |
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- F1: 0.6554 |
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- Accuracy: 0.8760 |
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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: 5 |
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- eval_batch_size: 5 |
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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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- training_steps: 1000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 1.2604 | 0.4673 | 50 | 0.6573 | 0.5077 | 0.4747 | 0.4906 | 0.7863 | |
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| 0.5256 | 0.9346 | 100 | 0.4824 | 0.5732 | 0.6521 | 0.6101 | 0.8465 | |
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| 0.4529 | 1.4019 | 150 | 0.4461 | 0.5926 | 0.6509 | 0.6204 | 0.8464 | |
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| 0.3767 | 1.8692 | 200 | 0.4265 | 0.5747 | 0.6740 | 0.6204 | 0.8492 | |
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| 0.3403 | 2.3364 | 250 | 0.4557 | 0.5564 | 0.6083 | 0.5812 | 0.8451 | |
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| 0.331 | 2.8037 | 300 | 0.4065 | 0.6384 | 0.6671 | 0.6524 | 0.8669 | |
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| 0.2984 | 3.2710 | 350 | 0.3820 | 0.6411 | 0.6411 | 0.6411 | 0.8729 | |
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| 0.2763 | 3.7383 | 400 | 0.4078 | 0.6104 | 0.6037 | 0.6070 | 0.8576 | |
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| 0.2626 | 4.2056 | 450 | 0.4203 | 0.6268 | 0.6164 | 0.6216 | 0.8589 | |
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| 0.2456 | 4.6729 | 500 | 0.3960 | 0.6240 | 0.6406 | 0.6322 | 0.8686 | |
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| 0.2078 | 5.1402 | 550 | 0.4074 | 0.6401 | 0.6290 | 0.6345 | 0.8709 | |
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| 0.1859 | 5.6075 | 600 | 0.3853 | 0.6511 | 0.6601 | 0.6556 | 0.8733 | |
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| 0.2059 | 6.0748 | 650 | 0.3845 | 0.6539 | 0.6509 | 0.6524 | 0.8772 | |
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| 0.1649 | 6.5421 | 700 | 0.4128 | 0.6298 | 0.6486 | 0.6390 | 0.8706 | |
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| 0.1599 | 7.0093 | 750 | 0.4328 | 0.6302 | 0.6578 | 0.6437 | 0.8644 | |
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| 0.1437 | 7.4766 | 800 | 0.4100 | 0.6510 | 0.6469 | 0.6489 | 0.8727 | |
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| 0.1377 | 7.9439 | 850 | 0.4409 | 0.6317 | 0.6699 | 0.6503 | 0.8711 | |
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| 0.1164 | 8.4112 | 900 | 0.4331 | 0.6301 | 0.6642 | 0.6467 | 0.8717 | |
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| 0.1149 | 8.8785 | 950 | 0.4523 | 0.6466 | 0.6555 | 0.6510 | 0.8712 | |
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| 0.1096 | 9.3458 | 1000 | 0.4421 | 0.6502 | 0.6607 | 0.6554 | 0.8760 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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