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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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- generated |
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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-invoice |
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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: generated |
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type: generated |
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config: sroie |
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split: train |
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args: sroie |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.9959514170040485 |
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- name: Recall |
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type: recall |
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value: 0.9979716024340771 |
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- name: F1 |
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type: f1 |
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value: 0.9969604863221885 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9995786812723826 |
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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-invoice |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the generated dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0028 |
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- Precision: 0.9960 |
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- Recall: 0.9980 |
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- F1: 0.9970 |
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- Accuracy: 0.9996 |
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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: 2000 |
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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 | 2.0 | 100 | 0.0502 | 0.97 | 0.9838 | 0.9768 | 0.9968 | |
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| No log | 4.0 | 200 | 0.0194 | 0.972 | 0.9858 | 0.9789 | 0.9971 | |
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| No log | 6.0 | 300 | 0.0160 | 0.972 | 0.9858 | 0.9789 | 0.9971 | |
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| No log | 8.0 | 400 | 0.0123 | 0.972 | 0.9858 | 0.9789 | 0.9971 | |
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| 0.053 | 10.0 | 500 | 0.0089 | 0.9757 | 0.9757 | 0.9757 | 0.9966 | |
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| 0.053 | 12.0 | 600 | 0.0058 | 0.9959 | 0.9919 | 0.9939 | 0.9992 | |
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| 0.053 | 14.0 | 700 | 0.0046 | 0.9939 | 0.9919 | 0.9929 | 0.9989 | |
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| 0.053 | 16.0 | 800 | 0.0037 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.053 | 18.0 | 900 | 0.0068 | 0.9959 | 0.9878 | 0.9919 | 0.9987 | |
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| 0.0057 | 20.0 | 1000 | 0.0054 | 0.9919 | 0.9959 | 0.9939 | 0.9992 | |
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| 0.0057 | 22.0 | 1100 | 0.0057 | 0.9919 | 0.9959 | 0.9939 | 0.9992 | |
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| 0.0057 | 24.0 | 1200 | 0.0049 | 0.9919 | 0.9959 | 0.9939 | 0.9992 | |
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| 0.0057 | 26.0 | 1300 | 0.0052 | 0.9919 | 0.9959 | 0.9939 | 0.9992 | |
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| 0.0057 | 28.0 | 1400 | 0.0030 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.0022 | 30.0 | 1500 | 0.0028 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.0022 | 32.0 | 1600 | 0.0030 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.0022 | 34.0 | 1700 | 0.0030 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.0022 | 36.0 | 1800 | 0.0037 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.0022 | 38.0 | 1900 | 0.0037 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.0017 | 40.0 | 2000 | 0.0037 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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### Framework versions |
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- Transformers 4.23.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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