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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: 0.4598 |
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- Precision: 0.6190 |
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- Recall: 0.8667 |
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- F1: 0.7222 |
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- Accuracy: 0.9428 |
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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: 1000 |
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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 | 10.0 | 100 | 0.5546 | 0.4510 | 0.7667 | 0.5679 | 0.9016 | |
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| No log | 20.0 | 200 | 0.4975 | 0.5510 | 0.9 | 0.6835 | 0.9441 | |
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| No log | 30.0 | 300 | 0.4426 | 0.5098 | 0.8667 | 0.6420 | 0.9455 | |
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| No log | 40.0 | 400 | 0.5438 | 0.4727 | 0.8667 | 0.6118 | 0.9322 | |
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| 0.2854 | 50.0 | 500 | 0.3669 | 0.6047 | 0.8667 | 0.7123 | 0.9548 | |
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| 0.2854 | 60.0 | 600 | 0.5638 | 0.5778 | 0.8667 | 0.6933 | 0.9348 | |
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| 0.2854 | 70.0 | 700 | 0.3922 | 0.6512 | 0.9333 | 0.7671 | 0.9574 | |
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| 0.2854 | 80.0 | 800 | 0.3999 | 0.6047 | 0.8667 | 0.7123 | 0.9535 | |
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| 0.2854 | 90.0 | 900 | 0.4413 | 0.5814 | 0.8333 | 0.6849 | 0.9428 | |
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| 0.0112 | 100.0 | 1000 | 0.4598 | 0.6190 | 0.8667 | 0.7222 | 0.9428 | |
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### Framework versions |
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- Transformers 4.33.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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