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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mp-02/funsd |
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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-funsd |
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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/funsd |
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type: mp-02/funsd |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.875725338491296 |
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- name: Recall |
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type: recall |
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value: 0.9055 |
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- name: F1 |
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type: f1 |
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value: 0.8903638151425762 |
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- name: Accuracy |
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type: accuracy |
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value: 0.843706936150666 |
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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-funsd |
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This model is a fine-tuned version of [layoutlmv3](https://huggingface.co/layoutlmv3) on the mp-02/funsd dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6187 |
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- Precision: 0.8757 |
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- Recall: 0.9055 |
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- F1: 0.8904 |
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- Accuracy: 0.8437 |
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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: 4 |
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- eval_batch_size: 16 |
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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: 500 |
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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 | 1.32 | 50 | 0.9063 | 0.7006 | 0.757 | 0.7277 | 0.7607 | |
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| No log | 2.63 | 100 | 0.6387 | 0.7930 | 0.858 | 0.8242 | 0.7967 | |
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| No log | 3.95 | 150 | 0.5691 | 0.8171 | 0.8825 | 0.8486 | 0.8254 | |
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| No log | 5.26 | 200 | 0.5723 | 0.8315 | 0.881 | 0.8555 | 0.8223 | |
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| No log | 6.58 | 250 | 0.5897 | 0.8475 | 0.9 | 0.8729 | 0.8292 | |
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| No log | 7.89 | 300 | 0.6122 | 0.8482 | 0.9025 | 0.8745 | 0.8283 | |
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| No log | 9.21 | 350 | 0.6045 | 0.8505 | 0.899 | 0.8741 | 0.8392 | |
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| No log | 10.53 | 400 | 0.5662 | 0.8708 | 0.9 | 0.8852 | 0.8446 | |
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| No log | 11.84 | 450 | 0.5973 | 0.8739 | 0.9045 | 0.8889 | 0.8437 | |
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| 0.4305 | 13.16 | 500 | 0.6187 | 0.8757 | 0.9055 | 0.8904 | 0.8437 | |
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### Framework versions |
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- Transformers 4.12.5 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.13.2 |
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- Tokenizers 0.10.1 |
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