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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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- 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: test |
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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: 0.0042 |
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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 | 0.1164 | 0.902 | 0.9148 | 0.9084 | 0.9897 | |
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| No log | 4.0 | 200 | 0.0262 | 0.972 | 0.9858 | 0.9789 | 0.9971 | |
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| No log | 6.0 | 300 | 0.0157 | 0.972 | 0.9858 | 0.9789 | 0.9971 | |
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| No log | 8.0 | 400 | 0.0097 | 0.9877 | 0.9797 | 0.9837 | 0.9979 | |
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| 0.1294 | 10.0 | 500 | 0.0065 | 0.9939 | 0.9959 | 0.9949 | 0.9994 | |
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| 0.1294 | 12.0 | 600 | 0.0042 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.1294 | 14.0 | 700 | 0.0048 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.1294 | 16.0 | 800 | 0.0047 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.1294 | 18.0 | 900 | 0.0045 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.0051 | 20.0 | 1000 | 0.0042 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.0051 | 22.0 | 1100 | 0.0041 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.0051 | 24.0 | 1200 | 0.0041 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.0051 | 26.0 | 1300 | 0.0040 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.0051 | 28.0 | 1400 | 0.0040 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.0024 | 30.0 | 1500 | 0.0040 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.0024 | 32.0 | 1600 | 0.0040 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.0024 | 34.0 | 1700 | 0.0039 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.0024 | 36.0 | 1800 | 0.0039 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.0024 | 38.0 | 1900 | 0.0039 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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| 0.0018 | 40.0 | 2000 | 0.0039 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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