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---
library_name: transformers
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-invoice_ConControl_v1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# layoutlmv3-finetuned-invoice_ConControl_v1
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1550
- Precision: 0.8826
- Recall: 0.7390
- F1: 0.8044
- Accuracy: 0.9788
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 300
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 8 | 0.5664 | 0.0 | 0.0 | 0.0 | 0.9383 |
| No log | 2.0 | 16 | 0.3789 | 0.0 | 0.0 | 0.0 | 0.9383 |
| No log | 3.0 | 24 | 0.3673 | 0.0 | 0.0 | 0.0 | 0.9383 |
| No log | 4.0 | 32 | 0.3596 | 0.0 | 0.0 | 0.0 | 0.9383 |
| No log | 5.0 | 40 | 0.3381 | 0.0 | 0.0 | 0.0 | 0.9383 |
| No log | 6.0 | 48 | 0.2985 | 0.0 | 0.0 | 0.0 | 0.9383 |
| No log | 7.0 | 56 | 0.2590 | 0.5833 | 0.0949 | 0.1633 | 0.9456 |
| No log | 8.0 | 64 | 0.2310 | 0.6629 | 0.3932 | 0.4936 | 0.9585 |
| No log | 9.0 | 72 | 0.2125 | 0.5837 | 0.5085 | 0.5435 | 0.9639 |
| No log | 10.0 | 80 | 0.2003 | 0.6130 | 0.5424 | 0.5755 | 0.9672 |
| No log | 11.0 | 88 | 0.1858 | 0.6667 | 0.5831 | 0.6221 | 0.9696 |
| No log | 12.0 | 96 | 0.1734 | 0.7188 | 0.6237 | 0.6679 | 0.9731 |
| No log | 13.0 | 104 | 0.1719 | 0.7510 | 0.6542 | 0.6993 | 0.9739 |
| No log | 14.0 | 112 | 0.1677 | 0.8048 | 0.6847 | 0.7399 | 0.9756 |
| No log | 15.0 | 120 | 0.1616 | 0.8008 | 0.6949 | 0.7441 | 0.9754 |
| No log | 16.0 | 128 | 0.1587 | 0.8038 | 0.7085 | 0.7532 | 0.9757 |
| No log | 17.0 | 136 | 0.1528 | 0.8275 | 0.7153 | 0.7673 | 0.9783 |
| No log | 18.0 | 144 | 0.1591 | 0.8554 | 0.7220 | 0.7831 | 0.9779 |
| No log | 19.0 | 152 | 0.1449 | 0.868 | 0.7356 | 0.7963 | 0.9791 |
| No log | 20.0 | 160 | 0.1568 | 0.8611 | 0.7356 | 0.7934 | 0.9786 |
| No log | 21.0 | 168 | 0.1509 | 0.8645 | 0.7356 | 0.7949 | 0.9788 |
| No log | 22.0 | 176 | 0.1465 | 0.8715 | 0.7356 | 0.7978 | 0.9786 |
| No log | 23.0 | 184 | 0.1446 | 0.8577 | 0.7356 | 0.7920 | 0.9783 |
| No log | 24.0 | 192 | 0.1469 | 0.8645 | 0.7356 | 0.7949 | 0.9788 |
| No log | 25.0 | 200 | 0.1513 | 0.8685 | 0.7390 | 0.7985 | 0.9788 |
| No log | 26.0 | 208 | 0.1554 | 0.8617 | 0.7390 | 0.7956 | 0.9788 |
| No log | 27.0 | 216 | 0.1511 | 0.8651 | 0.7390 | 0.7971 | 0.9786 |
| No log | 28.0 | 224 | 0.1566 | 0.872 | 0.7390 | 0.8 | 0.9788 |
| No log | 29.0 | 232 | 0.1544 | 0.8685 | 0.7390 | 0.7985 | 0.9788 |
| No log | 30.0 | 240 | 0.1510 | 0.8622 | 0.7424 | 0.7978 | 0.9791 |
| No log | 31.0 | 248 | 0.1589 | 0.8755 | 0.7390 | 0.8015 | 0.9788 |
| No log | 32.0 | 256 | 0.1550 | 0.8826 | 0.7390 | 0.8044 | 0.9788 |
| No log | 33.0 | 264 | 0.1498 | 0.8656 | 0.7424 | 0.7993 | 0.9791 |
| No log | 34.0 | 272 | 0.1539 | 0.8725 | 0.7424 | 0.8022 | 0.9793 |
| No log | 35.0 | 280 | 0.1542 | 0.8690 | 0.7424 | 0.8007 | 0.9793 |
| No log | 36.0 | 288 | 0.1538 | 0.8690 | 0.7424 | 0.8007 | 0.9793 |
| No log | 37.0 | 296 | 0.1543 | 0.8725 | 0.7424 | 0.8022 | 0.9793 |
| No log | 37.5 | 300 | 0.1543 | 0.8725 | 0.7424 | 0.8022 | 0.9793 |
### Framework versions
- Transformers 4.50.0
- Pytorch 2.6.0+cu118
- Datasets 3.4.1
- Tokenizers 0.21.1
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