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layoutlmv3-finetuned-invoice-2

Token Classification
Transformers
PyTorch
layoutlmv3
Generated from Trainer
Inference Endpoints
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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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+ 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-2
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+ results: []
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+ ---
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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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+
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+ # layoutlmv3-finetuned-invoice-2
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+
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+ This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1396
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+ - Precision: 0.7576
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+ - Recall: 0.8929
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+ - F1: 0.8197
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+ - Accuracy: 0.9742
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 4.35 | 100 | 0.4241 | 0.0 | 0.0 | 0.0 | 0.9135 |
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+ | No log | 8.7 | 200 | 0.2990 | 0.2353 | 0.1429 | 0.1778 | 0.9239 |
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+ | No log | 13.04 | 300 | 0.3107 | 0.5263 | 0.3571 | 0.4255 | 0.9458 |
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+ | No log | 17.39 | 400 | 0.1345 | 0.6970 | 0.8214 | 0.7541 | 0.9742 |
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+ | 0.2872 | 21.74 | 500 | 0.1396 | 0.7576 | 0.8929 | 0.8197 | 0.9742 |
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+ | 0.2872 | 26.09 | 600 | 0.1673 | 0.8519 | 0.8214 | 0.8364 | 0.9690 |
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+ | 0.2872 | 30.43 | 700 | 0.1784 | 0.8519 | 0.8214 | 0.8364 | 0.9690 |
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+ | 0.2872 | 34.78 | 800 | 0.1401 | 0.7742 | 0.8571 | 0.8136 | 0.9729 |
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+ | 0.2872 | 39.13 | 900 | 0.1480 | 0.7273 | 0.8571 | 0.7869 | 0.9716 |
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+ | 0.0443 | 43.48 | 1000 | 0.1739 | 0.6970 | 0.8214 | 0.7541 | 0.9703 |
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+ | 0.0443 | 47.83 | 1100 | 0.1786 | 0.7097 | 0.7857 | 0.7458 | 0.9690 |
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+ | 0.0443 | 52.17 | 1200 | 0.1832 | 0.6970 | 0.8214 | 0.7541 | 0.9690 |
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+ | 0.0443 | 56.52 | 1300 | 0.1861 | 0.6389 | 0.8214 | 0.7187 | 0.9690 |
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+ | 0.0443 | 60.87 | 1400 | 0.2155 | 0.6667 | 0.7143 | 0.6897 | 0.9639 |
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+ | 0.0198 | 65.22 | 1500 | 0.2087 | 0.6667 | 0.7143 | 0.6897 | 0.9652 |
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+ | 0.0198 | 69.57 | 1600 | 0.1680 | 0.6970 | 0.8214 | 0.7541 | 0.9703 |
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+ | 0.0198 | 73.91 | 1700 | 0.1664 | 0.6970 | 0.8214 | 0.7541 | 0.9703 |
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+ | 0.0198 | 78.26 | 1800 | 0.1795 | 0.6970 | 0.8214 | 0.7541 | 0.9703 |
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+ | 0.0198 | 82.61 | 1900 | 0.1807 | 0.6970 | 0.8214 | 0.7541 | 0.9703 |
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+ | 0.0151 | 86.96 | 2000 | 0.1825 | 0.6970 | 0.8214 | 0.7541 | 0.9703 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.27.4
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+ - Pytorch 2.0.0+cu117
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+ - Datasets 2.11.0
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+ - Tokenizers 0.13.3