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--- |
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base_model: layoutlmv3 |
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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-finetuned-cord |
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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: 0.963984674329502 |
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- name: Recall |
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type: recall |
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value: 0.9767080745341615 |
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- name: F1 |
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type: f1 |
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value: 0.9703046664095644 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9690152801358234 |
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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-finetuned-cord |
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This model is a fine-tuned version of [layoutlmv3](https://huggingface.co/layoutlmv3) on the mp-02/cord dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2087 |
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- Precision: 0.9640 |
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- Recall: 0.9767 |
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- F1: 0.9703 |
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- Accuracy: 0.9690 |
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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: 1e-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: 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 | 1.5625 | 250 | 0.2302 | 0.9594 | 0.9720 | 0.9657 | 0.9656 | |
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| 0.041 | 3.125 | 500 | 0.2176 | 0.9542 | 0.9705 | 0.9623 | 0.9618 | |
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| 0.041 | 4.6875 | 750 | 0.1903 | 0.9573 | 0.9736 | 0.9654 | 0.9682 | |
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| 0.0302 | 6.25 | 1000 | 0.2027 | 0.9602 | 0.9744 | 0.9672 | 0.9660 | |
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| 0.0302 | 7.8125 | 1250 | 0.2174 | 0.9670 | 0.9775 | 0.9722 | 0.9703 | |
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| 0.019 | 9.375 | 1500 | 0.2018 | 0.9640 | 0.9775 | 0.9707 | 0.9711 | |
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| 0.019 | 10.9375 | 1750 | 0.2084 | 0.9677 | 0.9783 | 0.9730 | 0.9694 | |
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| 0.0115 | 12.5 | 2000 | 0.2087 | 0.9640 | 0.9767 | 0.9703 | 0.9690 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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