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---
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-funsd2
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-funsd2
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6633
- Precision: 0.9027
- Recall: 0.9090
- F1: 0.9058
- Accuracy: 0.8500
## 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: 5e-05
- train_batch_size: 14
- eval_batch_size: 14
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 120
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 0.9091 | 10 | 0.9825 | 0.5685 | 0.6133 | 0.5901 | 0.6804 |
| No log | 1.8182 | 20 | 0.6492 | 0.7647 | 0.8215 | 0.7921 | 0.7781 |
| No log | 2.7273 | 30 | 0.5079 | 0.8037 | 0.8635 | 0.8326 | 0.8370 |
| No log | 3.6364 | 40 | 0.5371 | 0.8600 | 0.8924 | 0.8759 | 0.8428 |
| No log | 4.5455 | 50 | 0.5696 | 0.8753 | 0.8968 | 0.8859 | 0.8348 |
| No log | 5.4545 | 60 | 0.6309 | 0.8733 | 0.8863 | 0.8797 | 0.8272 |
| No log | 6.3636 | 70 | 0.6272 | 0.8878 | 0.9003 | 0.8940 | 0.8494 |
| No log | 7.2727 | 80 | 0.6168 | 0.9025 | 0.9151 | 0.9088 | 0.8688 |
| No log | 8.1818 | 90 | 0.6458 | 0.9094 | 0.9134 | 0.9114 | 0.8588 |
| No log | 9.0909 | 100 | 0.6830 | 0.8985 | 0.9064 | 0.9024 | 0.8490 |
| No log | 10.0 | 110 | 0.6325 | 0.9086 | 0.9221 | 0.9153 | 0.8502 |
| No log | 10.9091 | 120 | 0.6633 | 0.9027 | 0.9090 | 0.9058 | 0.8500 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
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