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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: microsoft/layoutlmv3-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mp-02/cord |
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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-base-cord2 |
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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: mp-02/cord |
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type: mp-02/cord |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.9466882067851373 |
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- name: Recall |
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type: recall |
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value: 0.9614438063986874 |
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- name: F1 |
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type: f1 |
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value: 0.9540089540089539 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9611161939615737 |
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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-base-cord2 |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the mp-02/cord dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1856 |
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- Precision: 0.9467 |
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- Recall: 0.9614 |
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- F1: 0.9540 |
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- Accuracy: 0.9611 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- training_steps: 3000 |
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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 | 1.0 | 100 | 1.2612 | 0.6788 | 0.7629 | 0.7184 | 0.7685 | |
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| No log | 2.0 | 200 | 0.5621 | 0.8674 | 0.8802 | 0.8738 | 0.8916 | |
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| No log | 3.0 | 300 | 0.3639 | 0.8846 | 0.9114 | 0.8978 | 0.9186 | |
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| No log | 4.0 | 400 | 0.3197 | 0.9153 | 0.9393 | 0.9271 | 0.9410 | |
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| 0.8719 | 5.0 | 500 | 0.2304 | 0.9357 | 0.9549 | 0.9452 | 0.9543 | |
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| 0.8719 | 6.0 | 600 | 0.2069 | 0.9389 | 0.9573 | 0.9480 | 0.9556 | |
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| 0.8719 | 7.0 | 700 | 0.2081 | 0.9459 | 0.9606 | 0.9532 | 0.9593 | |
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| 0.8719 | 8.0 | 800 | 0.1901 | 0.9532 | 0.9688 | 0.9609 | 0.9666 | |
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| 0.8719 | 9.0 | 900 | 0.1559 | 0.9515 | 0.9647 | 0.9580 | 0.9671 | |
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| 0.136 | 10.0 | 1000 | 0.1856 | 0.9467 | 0.9614 | 0.9540 | 0.9611 | |
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| 0.136 | 11.0 | 1100 | 0.2020 | 0.9537 | 0.9631 | 0.9584 | 0.9629 | |
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| 0.136 | 12.0 | 1200 | 0.1908 | 0.9552 | 0.9631 | 0.9592 | 0.9620 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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