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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: 0.010438413361169102 |
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- name: Recall |
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type: recall |
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value: 0.02028397565922921 |
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- name: F1 |
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type: f1 |
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value: 0.013783597518952447 |
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- name: Accuracy |
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type: accuracy |
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value: 0.6785338108278913 |
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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: 2.1320 |
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- Precision: 0.0104 |
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- Recall: 0.0203 |
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- F1: 0.0138 |
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- Accuracy: 0.6785 |
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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: 1 |
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- eval_batch_size: 1 |
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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: 5 |
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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 | 0.01 | 1 | 2.3858 | 0.0114 | 0.0649 | 0.0194 | 0.1904 | |
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| No log | 0.02 | 2 | 2.2795 | 0.0108 | 0.0527 | 0.0180 | 0.3240 | |
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| No log | 0.03 | 3 | 2.2072 | 0.0131 | 0.0446 | 0.0203 | 0.5155 | |
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| No log | 0.04 | 4 | 2.1575 | 0.0103 | 0.0243 | 0.0145 | 0.6345 | |
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| No log | 0.05 | 5 | 2.1320 | 0.0104 | 0.0203 | 0.0138 | 0.6785 | |
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### Framework versions |
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- Transformers 4.35.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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