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--- |
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license: cc-by-nc-sa-4.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- drug_bill_layoutv3 |
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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-vinv2 |
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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: drug_bill_layoutv3 |
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type: drug_bill_layoutv3 |
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config: Vin_Drug_Bill |
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split: train |
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args: Vin_Drug_Bill |
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metrics: |
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- name: Precision |
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type: precision |
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value: 1.0 |
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- name: Recall |
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type: recall |
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value: 1.0 |
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- name: F1 |
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type: f1 |
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value: 1.0 |
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- name: Accuracy |
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type: accuracy |
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value: 1.0 |
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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-vinv2 |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the drug_bill_layoutv3 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0001 |
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- Precision: 1.0 |
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- Recall: 1.0 |
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- F1: 1.0 |
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- Accuracy: 1.0 |
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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: 3000 |
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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 | 1.33 | 250 | 0.0025 | 0.9994 | 0.9994 | 0.9994 | 0.9998 | |
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| 0.0662 | 2.66 | 500 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0662 | 3.99 | 750 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0111 | 5.32 | 1000 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0111 | 6.65 | 1250 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0126 | 7.98 | 1500 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0126 | 9.31 | 1750 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0032 | 10.64 | 2000 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0032 | 11.97 | 2250 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0011 | 13.3 | 2500 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0011 | 14.63 | 2750 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0002 | 15.96 | 3000 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.2 |
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