---
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: 0.2763
- Precision: 0.5109
- Recall: 0.6026
- F1: 0.5529
- Accuracy: 0.9222

## 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  | 0.6800          | 0.3371    | 0.3846 | 0.3593 | 0.7682   |
| No log        | 16.67 | 200  | 0.3088          | 0.5204    | 0.6538 | 0.5795 | 0.9156   |
| No log        | 25.0  | 300  | 0.2142          | 0.5326    | 0.6282 | 0.5765 | 0.9305   |
| No log        | 33.33 | 400  | 0.2301          | 0.5795    | 0.6538 | 0.6145 | 0.9288   |
| 0.4115        | 41.67 | 500  | 0.2426          | 0.5618    | 0.6410 | 0.5988 | 0.9272   |
| 0.4115        | 50.0  | 600  | 0.4171          | 0.6190    | 0.6667 | 0.6420 | 0.8924   |
| 0.4115        | 58.33 | 700  | 0.2265          | 0.5393    | 0.6154 | 0.5749 | 0.9371   |
| 0.4115        | 66.67 | 800  | 0.2869          | 0.5506    | 0.6282 | 0.5868 | 0.9156   |
| 0.4115        | 75.0  | 900  | 0.2633          | 0.5568    | 0.6282 | 0.5904 | 0.9272   |
| 0.0231        | 83.33 | 1000 | 0.2763          | 0.5109    | 0.6026 | 0.5529 | 0.9222   |


### Framework versions

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