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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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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: test |
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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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# test |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4675 |
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- Precision: 0.8 |
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- Recall: 0.8649 |
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- F1: 0.8312 |
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- Accuracy: 0.8318 |
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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: 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: 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 | 3.85 | 50 | 1.1808 | 0.7013 | 0.7297 | 0.7152 | 0.7196 | |
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| No log | 7.69 | 100 | 0.7117 | 0.7317 | 0.8108 | 0.7692 | 0.8037 | |
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| No log | 11.54 | 150 | 0.5580 | 0.7778 | 0.8514 | 0.8129 | 0.8224 | |
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| No log | 15.38 | 200 | 0.5009 | 0.8228 | 0.8784 | 0.8497 | 0.8411 | |
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| No log | 19.23 | 250 | 0.4659 | 0.8228 | 0.8784 | 0.8497 | 0.8505 | |
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| No log | 23.08 | 300 | 0.4734 | 0.7901 | 0.8649 | 0.8258 | 0.8318 | |
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| No log | 26.92 | 350 | 0.4496 | 0.8205 | 0.8649 | 0.8421 | 0.8318 | |
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| No log | 30.77 | 400 | 0.4619 | 0.8 | 0.8649 | 0.8312 | 0.8318 | |
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| No log | 34.62 | 450 | 0.4560 | 0.8125 | 0.8784 | 0.8442 | 0.8411 | |
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| 0.3885 | 38.46 | 500 | 0.4675 | 0.8 | 0.8649 | 0.8312 | 0.8318 | |
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### Framework versions |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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