---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv2-base-uncased
tags:
- generated_from_trainer
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/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.0749

## 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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 5.3171        | 0.2212  | 50   | 4.6375          |
| 4.4008        | 0.4425  | 100  | 4.0771          |
| 4.0457        | 0.6637  | 150  | 3.8669          |
| 3.8671        | 0.8850  | 200  | 3.6725          |
| 3.4191        | 1.1062  | 250  | 3.7154          |
| 3.181         | 1.3274  | 300  | 3.2224          |
| 3.1471        | 1.5487  | 350  | 3.1611          |
| 2.8849        | 1.7699  | 400  | 2.9149          |
| 2.6279        | 1.9912  | 450  | 2.7628          |
| 2.1833        | 2.2124  | 500  | 2.6845          |
| 1.9236        | 2.4336  | 550  | 2.5157          |
| 1.9385        | 2.6549  | 600  | 2.3477          |
| 1.8375        | 2.8761  | 650  | 2.5764          |
| 1.5994        | 3.0973  | 700  | 2.5796          |
| 1.4455        | 3.3186  | 750  | 2.4148          |
| 1.4008        | 3.5398  | 800  | 2.3462          |
| 1.4988        | 3.7611  | 850  | 2.0116          |
| 1.3286        | 3.9823  | 900  | 2.4790          |
| 1.0156        | 4.2035  | 950  | 2.6341          |
| 1.0546        | 4.4248  | 1000 | 2.9160          |
| 0.9135        | 4.6460  | 1050 | 3.3701          |
| 1.0544        | 4.8673  | 1100 | 2.3959          |
| 0.8423        | 5.0885  | 1150 | 2.8365          |
| 0.8101        | 5.3097  | 1200 | 2.7091          |
| 0.6854        | 5.5310  | 1250 | 3.1581          |
| 0.7012        | 5.7522  | 1300 | 3.2229          |
| 0.7611        | 5.9735  | 1350 | 2.8766          |
| 0.5144        | 6.1947  | 1400 | 3.1662          |
| 0.6242        | 6.4159  | 1450 | 3.4253          |
| 0.619         | 6.6372  | 1500 | 3.4169          |
| 0.4874        | 6.8584  | 1550 | 3.6466          |
| 0.4547        | 7.0796  | 1600 | 3.2960          |
| 0.4377        | 7.3009  | 1650 | 3.6329          |
| 0.3454        | 7.5221  | 1700 | 3.7038          |
| 0.6575        | 7.7434  | 1750 | 3.6313          |
| 0.3357        | 7.9646  | 1800 | 3.9394          |
| 0.2812        | 8.1858  | 1850 | 3.7570          |
| 0.278         | 8.4071  | 1900 | 3.9145          |
| 0.3365        | 8.6283  | 1950 | 3.7289          |
| 0.4358        | 8.8496  | 2000 | 3.3832          |
| 0.2653        | 9.0708  | 2050 | 3.6875          |
| 0.2302        | 9.2920  | 2100 | 3.8430          |
| 0.1409        | 9.5133  | 2150 | 4.0128          |
| 0.3695        | 9.7345  | 2200 | 3.5634          |
| 0.2317        | 9.9558  | 2250 | 4.5010          |
| 0.3039        | 10.1770 | 2300 | 4.3949          |
| 0.2396        | 10.3982 | 2350 | 4.1234          |
| 0.2696        | 10.6195 | 2400 | 3.9876          |
| 0.2627        | 10.8407 | 2450 | 4.0118          |
| 0.2415        | 11.0619 | 2500 | 4.0133          |
| 0.062         | 11.2832 | 2550 | 4.1836          |
| 0.2313        | 11.5044 | 2600 | 4.2826          |
| 0.1002        | 11.7257 | 2650 | 4.4694          |
| 0.0836        | 11.9469 | 2700 | 4.6534          |
| 0.1351        | 12.1681 | 2750 | 4.3303          |
| 0.0415        | 12.3894 | 2800 | 4.4617          |
| 0.1199        | 12.6106 | 2850 | 4.5453          |
| 0.106         | 12.8319 | 2900 | 4.5849          |
| 0.1003        | 13.0531 | 2950 | 4.7043          |
| 0.0116        | 13.2743 | 3000 | 4.8034          |
| 0.0372        | 13.4956 | 3050 | 4.8729          |
| 0.0587        | 13.7168 | 3100 | 4.7357          |
| 0.1131        | 13.9381 | 3150 | 4.2960          |
| 0.0582        | 14.1593 | 3200 | 4.2865          |
| 0.0746        | 14.3805 | 3250 | 4.5552          |
| 0.1061        | 14.6018 | 3300 | 4.5042          |
| 0.108         | 14.8230 | 3350 | 4.5374          |
| 0.0118        | 15.0442 | 3400 | 4.7829          |
| 0.0579        | 15.2655 | 3450 | 4.8695          |
| 0.0358        | 15.4867 | 3500 | 4.9450          |
| 0.0772        | 15.7080 | 3550 | 4.9850          |
| 0.0838        | 15.9292 | 3600 | 4.9220          |
| 0.0478        | 16.1504 | 3650 | 4.8603          |
| 0.1258        | 16.3717 | 3700 | 5.0143          |
| 0.0192        | 16.5929 | 3750 | 5.0035          |
| 0.0856        | 16.8142 | 3800 | 5.0450          |
| 0.0079        | 17.0354 | 3850 | 5.0792          |
| 0.0075        | 17.2566 | 3900 | 5.0261          |
| 0.0647        | 17.4779 | 3950 | 5.0301          |
| 0.0296        | 17.6991 | 4000 | 4.9634          |
| 0.0044        | 17.9204 | 4050 | 4.9916          |
| 0.0117        | 18.1416 | 4100 | 4.9851          |
| 0.0047        | 18.3628 | 4150 | 4.9993          |
| 0.0034        | 18.5841 | 4200 | 5.0673          |
| 0.0466        | 18.8053 | 4250 | 5.0642          |
| 0.0362        | 19.0265 | 4300 | 5.0544          |
| 0.0145        | 19.2478 | 4350 | 5.0634          |
| 0.0125        | 19.4690 | 4400 | 5.0688          |
| 0.0063        | 19.6903 | 4450 | 5.0728          |
| 0.0231        | 19.9115 | 4500 | 5.0749          |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.4.0+cpu
- Datasets 2.20.0
- Tokenizers 0.19.1