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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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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-sroie |
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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-finetuned-sroie |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0742 |
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- Precision: 0.9472 |
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- Recall: 0.9668 |
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- F1: 0.9569 |
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- Accuracy: 0.9872 |
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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: 2500 |
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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 | 1.9841 | 250 | 0.0544 | 0.9319 | 0.9592 | 0.9453 | 0.9836 | |
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| 0.0813 | 3.9683 | 500 | 0.0607 | 0.9280 | 0.9683 | 0.9477 | 0.9844 | |
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| 0.0813 | 5.9524 | 750 | 0.0530 | 0.9451 | 0.9589 | 0.9519 | 0.9854 | |
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| 0.023 | 7.9365 | 1000 | 0.0562 | 0.9434 | 0.9643 | 0.9537 | 0.9863 | |
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| 0.023 | 9.9206 | 1250 | 0.0613 | 0.9486 | 0.9614 | 0.9549 | 0.9867 | |
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| 0.0128 | 11.9048 | 1500 | 0.0632 | 0.9510 | 0.9650 | 0.9579 | 0.9875 | |
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| 0.0128 | 13.8889 | 1750 | 0.0705 | 0.9403 | 0.9670 | 0.9535 | 0.9862 | |
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| 0.0073 | 15.8730 | 2000 | 0.0723 | 0.9485 | 0.9643 | 0.9563 | 0.9871 | |
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| 0.0073 | 17.8571 | 2250 | 0.0728 | 0.9505 | 0.9653 | 0.9579 | 0.9875 | |
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| 0.0054 | 19.8413 | 2500 | 0.0742 | 0.9472 | 0.9668 | 0.9569 | 0.9872 | |
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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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