---
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: 0.2843
- Precision: 0.4118
- Recall: 0.8235
- F1: 0.5490
- Accuracy: 0.9485

## 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        | 8.33  | 100  | 0.6271          | 0.1864    | 0.6471 | 0.2895 | 0.8757   |
| No log        | 16.67 | 200  | 0.1736          | 0.52      | 0.7647 | 0.6190 | 0.9734   |
| No log        | 25.0  | 300  | 0.1302          | 0.5714    | 0.9412 | 0.7111 | 0.9734   |
| No log        | 33.33 | 400  | 0.2835          | 0.5333    | 0.9412 | 0.6809 | 0.9556   |
| 0.287         | 41.67 | 500  | 0.0924          | 0.4828    | 0.8235 | 0.6087 | 0.9805   |
| 0.287         | 50.0  | 600  | 0.2594          | 0.4412    | 0.8824 | 0.5882 | 0.9485   |
| 0.287         | 58.33 | 700  | 0.3172          | 0.4412    | 0.8824 | 0.5882 | 0.9467   |
| 0.287         | 66.67 | 800  | 0.2447          | 0.4545    | 0.8824 | 0.6    | 0.9520   |
| 0.287         | 75.0  | 900  | 0.2941          | 0.4118    | 0.8235 | 0.5490 | 0.9485   |
| 0.013         | 83.33 | 1000 | 0.2843          | 0.4118    | 0.8235 | 0.5490 | 0.9485   |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3