---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: test
  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. -->

# test

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4598
- Precision: 0.6190
- Recall: 0.8667
- F1: 0.7222
- Accuracy: 0.9428

## 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: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 10.0  | 100  | 0.5546          | 0.4510    | 0.7667 | 0.5679 | 0.9016   |
| No log        | 20.0  | 200  | 0.4975          | 0.5510    | 0.9    | 0.6835 | 0.9441   |
| No log        | 30.0  | 300  | 0.4426          | 0.5098    | 0.8667 | 0.6420 | 0.9455   |
| No log        | 40.0  | 400  | 0.5438          | 0.4727    | 0.8667 | 0.6118 | 0.9322   |
| 0.2854        | 50.0  | 500  | 0.3669          | 0.6047    | 0.8667 | 0.7123 | 0.9548   |
| 0.2854        | 60.0  | 600  | 0.5638          | 0.5778    | 0.8667 | 0.6933 | 0.9348   |
| 0.2854        | 70.0  | 700  | 0.3922          | 0.6512    | 0.9333 | 0.7671 | 0.9574   |
| 0.2854        | 80.0  | 800  | 0.3999          | 0.6047    | 0.8667 | 0.7123 | 0.9535   |
| 0.2854        | 90.0  | 900  | 0.4413          | 0.5814    | 0.8333 | 0.6849 | 0.9428   |
| 0.0112        | 100.0 | 1000 | 0.4598          | 0.6190    | 0.8667 | 0.7222 | 0.9428   |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3