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---
library_name: transformers
base_model: layoutlmv3
tags:
- generated_from_trainer
datasets:
- mp-02/sroie
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-sroie
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: mp-02/sroie
type: mp-02/sroie
metrics:
- name: Precision
type: precision
value: 0.9232981783317353
- name: Recall
type: recall
value: 0.9578912466843501
- name: F1
type: f1
value: 0.9402766476810415
- name: Accuracy
type: accuracy
value: 0.981485280541594
---
<!-- 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 [layoutlmv3](https://huggingface.co/layoutlmv3) on the mp-02/sroie dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0651
- Precision: 0.9233
- Recall: 0.9579
- F1: 0.9403
- Accuracy: 0.9815
## 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-06
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 2.3810 | 250 | 0.0957 | 0.9075 | 0.9304 | 0.9188 | 0.9752 |
| 0.1943 | 4.7619 | 500 | 0.0699 | 0.9260 | 0.9456 | 0.9357 | 0.9805 |
| 0.1943 | 7.1429 | 750 | 0.0657 | 0.9291 | 0.9513 | 0.9400 | 0.9817 |
| 0.0485 | 9.5238 | 1000 | 0.0651 | 0.9233 | 0.9579 | 0.9403 | 0.9815 |
| 0.0485 | 11.9048 | 1250 | 0.0661 | 0.9155 | 0.9625 | 0.9384 | 0.9808 |
| 0.0397 | 14.2857 | 1500 | 0.0660 | 0.9161 | 0.9632 | 0.9391 | 0.9810 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
|