---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
datasets:
- sroie
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: nexon_jan_2023
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: sroie
      type: sroie
      config: discharge
      split: test
      args: discharge
    metrics:
    - name: Precision
      type: precision
      value: 0.975609756097561
    - name: Recall
      type: recall
      value: 0.9302325581395349
    - name: F1
      type: f1
      value: 0.9523809523809524
    - name: Accuracy
      type: accuracy
      value: 0.9971428571428571
---

<!-- 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. -->

# nexon_jan_2023

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the sroie dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0380
- Precision: 0.9756
- Recall: 0.9302
- F1: 0.9524
- Accuracy: 0.9971

## 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: 2
- eval_batch_size: 2
- 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        | 16.67  | 100  | 0.1998          | 0.6286    | 0.5116 | 0.5641 | 0.9571   |
| No log        | 33.33  | 200  | 0.0616          | 0.9756    | 0.9302 | 0.9524 | 0.9971   |
| No log        | 50.0   | 300  | 0.0439          | 0.9756    | 0.9302 | 0.9524 | 0.9971   |
| No log        | 66.67  | 400  | 0.0404          | 0.9756    | 0.9302 | 0.9524 | 0.9971   |
| 0.1151        | 83.33  | 500  | 0.0389          | 0.9756    | 0.9302 | 0.9524 | 0.9971   |
| 0.1151        | 100.0  | 600  | 0.0380          | 0.9756    | 0.9302 | 0.9524 | 0.9971   |
| 0.1151        | 116.67 | 700  | 0.0378          | 0.9756    | 0.9302 | 0.9524 | 0.9971   |
| 0.1151        | 133.33 | 800  | 0.0379          | 0.9756    | 0.9302 | 0.9524 | 0.9971   |
| 0.1151        | 150.0  | 900  | 0.0378          | 0.9756    | 0.9302 | 0.9524 | 0.9971   |
| 0.009         | 166.67 | 1000 | 0.0378          | 0.9756    | 0.9302 | 0.9524 | 0.9971   |
| 0.009         | 183.33 | 1100 | 0.0378          | 0.9756    | 0.9302 | 0.9524 | 0.9971   |
| 0.009         | 200.0  | 1200 | 0.0379          | 0.9756    | 0.9302 | 0.9524 | 0.9971   |
| 0.009         | 216.67 | 1300 | 0.0379          | 0.9756    | 0.9302 | 0.9524 | 0.9971   |
| 0.009         | 233.33 | 1400 | 0.0379          | 0.9756    | 0.9302 | 0.9524 | 0.9971   |
| 0.0064        | 250.0  | 1500 | 0.0380          | 0.9756    | 0.9302 | 0.9524 | 0.9971   |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.2.2
- Tokenizers 0.13.2