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--- |
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license: cc-by-nc-sa-4.0 |
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base_model: microsoft/layoutlmv3-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- ls-generated4 |
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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-invoice-model |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: ls-generated4 |
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type: ls-generated4 |
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config: invoice |
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split: test |
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args: invoice |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.9185733512786003 |
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- name: Recall |
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type: recall |
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value: 0.9375 |
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- name: F1 |
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type: f1 |
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value: 0.9279401767505099 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9536870503597122 |
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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-invoice-model |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the ls-generated4 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3694 |
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- Precision: 0.9186 |
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- Recall: 0.9375 |
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- F1: 0.9279 |
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- Accuracy: 0.9537 |
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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: 2 |
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- eval_batch_size: 2 |
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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: 2000 |
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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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| No log | 0.85 | 100 | 0.7836 | 0.5238 | 0.5982 | 0.5585 | 0.7680 | |
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| No log | 1.69 | 200 | 0.4954 | 0.6888 | 0.7479 | 0.7172 | 0.8422 | |
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| No log | 2.54 | 300 | 0.3483 | 0.7807 | 0.8462 | 0.8121 | 0.9040 | |
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| No log | 3.39 | 400 | 0.3200 | 0.8113 | 0.8654 | 0.8375 | 0.9125 | |
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| 0.5923 | 4.24 | 500 | 0.2775 | 0.8593 | 0.8853 | 0.8721 | 0.9319 | |
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| 0.5923 | 5.08 | 600 | 0.2674 | 0.8700 | 0.9052 | 0.8872 | 0.9377 | |
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| 0.5923 | 5.93 | 700 | 0.2766 | 0.8739 | 0.9135 | 0.8932 | 0.9386 | |
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| 0.5923 | 6.78 | 800 | 0.2641 | 0.8879 | 0.9190 | 0.9031 | 0.9472 | |
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| 0.5923 | 7.63 | 900 | 0.2893 | 0.9094 | 0.9238 | 0.9165 | 0.9447 | |
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| 0.0802 | 8.47 | 1000 | 0.3369 | 0.9145 | 0.9258 | 0.9201 | 0.9465 | |
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| 0.0802 | 9.32 | 1100 | 0.3037 | 0.9043 | 0.9341 | 0.9189 | 0.9505 | |
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| 0.0802 | 10.17 | 1200 | 0.3510 | 0.9032 | 0.9231 | 0.9130 | 0.9472 | |
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| 0.0802 | 11.02 | 1300 | 0.3224 | 0.9138 | 0.9251 | 0.9195 | 0.9501 | |
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| 0.0802 | 11.86 | 1400 | 0.3873 | 0.9133 | 0.9265 | 0.9199 | 0.9456 | |
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| 0.0198 | 12.71 | 1500 | 0.3786 | 0.9120 | 0.9327 | 0.9222 | 0.9492 | |
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| 0.0198 | 13.56 | 1600 | 0.3807 | 0.9050 | 0.9293 | 0.9170 | 0.9469 | |
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| 0.0198 | 14.41 | 1700 | 0.3664 | 0.9088 | 0.9313 | 0.9199 | 0.9510 | |
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| 0.0198 | 15.25 | 1800 | 0.3582 | 0.9152 | 0.9341 | 0.9245 | 0.9521 | |
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| 0.0198 | 16.1 | 1900 | 0.3736 | 0.9198 | 0.9368 | 0.9282 | 0.9528 | |
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| 0.007 | 16.95 | 2000 | 0.3694 | 0.9186 | 0.9375 | 0.9279 | 0.9537 | |
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### Framework versions |
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- Transformers 4.35.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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