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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-sroie
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-sroie
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: 0.0742
- Precision: 0.9472
- Recall: 0.9668
- F1: 0.9569
- Accuracy: 0.9872
## 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: 1e-05
- train_batch_size: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.9841 | 250 | 0.0544 | 0.9319 | 0.9592 | 0.9453 | 0.9836 |
| 0.0813 | 3.9683 | 500 | 0.0607 | 0.9280 | 0.9683 | 0.9477 | 0.9844 |
| 0.0813 | 5.9524 | 750 | 0.0530 | 0.9451 | 0.9589 | 0.9519 | 0.9854 |
| 0.023 | 7.9365 | 1000 | 0.0562 | 0.9434 | 0.9643 | 0.9537 | 0.9863 |
| 0.023 | 9.9206 | 1250 | 0.0613 | 0.9486 | 0.9614 | 0.9549 | 0.9867 |
| 0.0128 | 11.9048 | 1500 | 0.0632 | 0.9510 | 0.9650 | 0.9579 | 0.9875 |
| 0.0128 | 13.8889 | 1750 | 0.0705 | 0.9403 | 0.9670 | 0.9535 | 0.9862 |
| 0.0073 | 15.8730 | 2000 | 0.0723 | 0.9485 | 0.9643 | 0.9563 | 0.9871 |
| 0.0073 | 17.8571 | 2250 | 0.0728 | 0.9505 | 0.9653 | 0.9579 | 0.9875 |
| 0.0054 | 19.8413 | 2500 | 0.0742 | 0.9472 | 0.9668 | 0.9569 | 0.9872 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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