---
library_name: transformers
base_model: layoutlmv3
tags:
- generated_from_trainer
datasets:
- not-lain/sroie
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-sroie
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: not-lain/sroie
      type: not-lain/sroie
    metrics:
    - name: Precision
      type: precision
      value: 0.9515865227347072
    - name: Recall
      type: recall
      value: 0.9645225464190982
    - name: F1
      type: f1
      value: 0.9580108677753993
    - name: Accuracy
      type: accuracy
      value: 0.9870755974971792
---

<!-- 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 not-lain/sroie dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0596
- Precision: 0.9516
- Recall: 0.9645
- F1: 0.9580
- Accuracy: 0.9871

## 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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.5873  | 100  | 0.0548          | 0.9415    | 0.9453 | 0.9434 | 0.9830   |
| No log        | 3.1746  | 200  | 0.0531          | 0.9377    | 0.9625 | 0.9499 | 0.9847   |
| No log        | 4.7619  | 300  | 0.0550          | 0.9414    | 0.9595 | 0.9504 | 0.9851   |
| No log        | 6.3492  | 400  | 0.0560          | 0.9500    | 0.9645 | 0.9572 | 0.9868   |
| 0.0464        | 7.9365  | 500  | 0.0596          | 0.9516    | 0.9645 | 0.9580 | 0.9871   |
| 0.0464        | 9.5238  | 600  | 0.0630          | 0.9502    | 0.9622 | 0.9562 | 0.9865   |
| 0.0464        | 11.1111 | 700  | 0.0707          | 0.9489    | 0.9658 | 0.9573 | 0.9868   |
| 0.0464        | 12.6984 | 800  | 0.0726          | 0.9515    | 0.9629 | 0.9572 | 0.9868   |
| 0.0464        | 14.2857 | 900  | 0.0765          | 0.9510    | 0.9652 | 0.9580 | 0.9871   |
| 0.0048        | 15.8730 | 1000 | 0.0773          | 0.9500    | 0.9645 | 0.9572 | 0.9868   |


### Framework versions

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