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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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datasets: |
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- format_dataset |
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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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- 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: format_dataset |
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type: format_dataset |
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config: assesment dataset |
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split: test |
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args: assesment dataset |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.8869778869778869 |
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- name: Recall |
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type: recall |
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value: 0.9025 |
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- name: F1 |
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type: f1 |
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value: 0.8946716232961586 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9977016777752241 |
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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 format_dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0089 |
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- Precision: 0.8870 |
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- Recall: 0.9025 |
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- F1: 0.8947 |
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- Accuracy: 0.9977 |
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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 | 0.62 | 100 | 0.0405 | 0.0 | 0.0 | 0.0 | 0.9877 | |
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| No log | 1.25 | 200 | 0.0170 | 0.7538 | 0.735 | 0.7443 | 0.9949 | |
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| No log | 1.88 | 300 | 0.0131 | 0.7261 | 0.875 | 0.7937 | 0.9956 | |
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| No log | 2.5 | 400 | 0.0123 | 0.7692 | 0.85 | 0.8076 | 0.9959 | |
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| 0.0271 | 3.12 | 500 | 0.0105 | 0.8098 | 0.905 | 0.8548 | 0.9968 | |
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| 0.0271 | 3.75 | 600 | 0.0106 | 0.8460 | 0.8925 | 0.8686 | 0.9972 | |
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| 0.0271 | 4.38 | 700 | 0.0086 | 0.8504 | 0.895 | 0.8721 | 0.9973 | |
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| 0.0271 | 5.0 | 800 | 0.0109 | 0.8871 | 0.845 | 0.8656 | 0.9972 | |
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| 0.0271 | 5.62 | 900 | 0.0085 | 0.8883 | 0.895 | 0.8917 | 0.9977 | |
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| 0.0042 | 6.25 | 1000 | 0.0089 | 0.8870 | 0.9025 | 0.8947 | 0.9977 | |
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### Framework versions |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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