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--- |
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library_name: transformers |
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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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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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--- |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0558 |
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- Precision: 0.9435 |
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- Recall: 0.9612 |
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- F1: 0.9523 |
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- Accuracy: 0.9858 |
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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 | 0.3195 | 100 | 0.0961 | 0.9121 | 0.9134 | 0.9128 | 0.9752 | |
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| No log | 0.6390 | 200 | 0.0772 | 0.9120 | 0.9396 | 0.9256 | 0.9780 | |
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| No log | 0.9585 | 300 | 0.0707 | 0.9272 | 0.9509 | 0.9389 | 0.9822 | |
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| No log | 1.2780 | 400 | 0.0638 | 0.9202 | 0.9602 | 0.9398 | 0.9819 | |
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| 0.1131 | 1.5974 | 500 | 0.0631 | 0.9270 | 0.9582 | 0.9423 | 0.9829 | |
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| 0.1131 | 1.9169 | 600 | 0.0561 | 0.9331 | 0.9615 | 0.9471 | 0.9843 | |
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| 0.1131 | 2.2364 | 700 | 0.0651 | 0.9141 | 0.9720 | 0.9421 | 0.9824 | |
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| 0.1131 | 2.5559 | 800 | 0.0537 | 0.9515 | 0.9556 | 0.9535 | 0.9862 | |
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| 0.1131 | 2.8754 | 900 | 0.0556 | 0.9467 | 0.9582 | 0.9524 | 0.9860 | |
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| 0.0379 | 3.1949 | 1000 | 0.0558 | 0.9435 | 0.9612 | 0.9523 | 0.9858 | |
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### Framework versions |
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- Transformers 4.46.0.dev0 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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