---
library_name: transformers
base_model: layoutlmv3
tags:
- generated_from_trainer
datasets:
- mp-02/sroie
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-base-sroie
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: mp-02/sroie
      type: mp-02/sroie
    metrics:
    - name: Precision
      type: precision
      value: 0.9469573706475757
    - name: Recall
      type: recall
      value: 0.9648541114058355
    - name: F1
      type: f1
      value: 0.9558219740515684
    - name: Accuracy
      type: accuracy
      value: 0.9863575751359114
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# layoutlmv3-base-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: 0.0526
- Precision: 0.9470
- Recall: 0.9649
- F1: 0.9558
- Accuracy: 0.9864

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 3000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 2.5   | 100  | 0.0806          | 0.9001    | 0.9377 | 0.9185 | 0.9759   |
| No log        | 5.0   | 200  | 0.0541          | 0.9392    | 0.9576 | 0.9483 | 0.9840   |
| No log        | 7.5   | 300  | 0.0515          | 0.9368    | 0.9629 | 0.9496 | 0.9844   |
| No log        | 10.0  | 400  | 0.0515          | 0.9450    | 0.9622 | 0.9535 | 0.9856   |
| 0.0717        | 12.5  | 500  | 0.0526          | 0.9470    | 0.9649 | 0.9558 | 0.9864   |
| 0.0717        | 15.0  | 600  | 0.0558          | 0.9353    | 0.9685 | 0.9516 | 0.9849   |
| 0.0717        | 17.5  | 700  | 0.0668          | 0.9408    | 0.9635 | 0.9520 | 0.9852   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1