---
library_name: transformers
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv2-base-uncased
tags:
- generated_from_trainer
model-index:
- name: test-model
  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-model

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: 5.7326

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.5222        | 0.2212  | 50   | 3.3167          |
| 0.3741        | 0.4425  | 100  | 3.5175          |
| 0.5087        | 0.6637  | 150  | 3.8062          |
| 0.7125        | 0.8850  | 200  | 4.1227          |
| 0.4148        | 1.1062  | 250  | 4.1049          |
| 0.3261        | 1.3274  | 300  | 3.8527          |
| 0.3721        | 1.5487  | 350  | 4.1329          |
| 0.3444        | 1.7699  | 400  | 4.0143          |
| 0.7134        | 1.9912  | 450  | 3.9609          |
| 0.2702        | 2.2124  | 500  | 4.3720          |
| 0.4396        | 2.4336  | 550  | 4.0561          |
| 0.4176        | 2.6549  | 600  | 3.8587          |
| 0.3063        | 2.8761  | 650  | 3.7568          |
| 0.2262        | 3.0973  | 700  | 4.1540          |
| 0.2206        | 3.3186  | 750  | 4.4668          |
| 0.3822        | 3.5398  | 800  | 4.1496          |
| 0.2665        | 3.7611  | 850  | 4.0747          |
| 0.3072        | 3.9823  | 900  | 4.8918          |
| 0.2284        | 4.2035  | 950  | 4.1878          |
| 0.1628        | 4.4248  | 1000 | 4.7544          |
| 0.1525        | 4.6460  | 1050 | 4.5190          |
| 0.2555        | 4.8673  | 1100 | 4.3845          |
| 0.3933        | 5.0885  | 1150 | 4.0418          |
| 0.0484        | 5.3097  | 1200 | 4.6753          |
| 0.3433        | 5.5310  | 1250 | 4.1875          |
| 0.2453        | 5.7522  | 1300 | 4.1922          |
| 0.0677        | 5.9735  | 1350 | 4.7340          |
| 0.1835        | 6.1947  | 1400 | 4.6262          |
| 0.2394        | 6.4159  | 1450 | 4.4393          |
| 0.1599        | 6.6372  | 1500 | 5.3708          |
| 0.2705        | 6.8584  | 1550 | 3.9829          |
| 0.2067        | 7.0796  | 1600 | 4.3178          |
| 0.2859        | 7.3009  | 1650 | 3.7816          |
| 0.1232        | 7.5221  | 1700 | 4.1798          |
| 0.1811        | 7.7434  | 1750 | 4.3196          |
| 0.1274        | 7.9646  | 1800 | 4.6113          |
| 0.1361        | 8.1858  | 1850 | 4.2228          |
| 0.1533        | 8.4071  | 1900 | 3.8230          |
| 0.1179        | 8.6283  | 1950 | 4.0259          |
| 0.1265        | 8.8496  | 2000 | 4.8971          |
| 0.2258        | 9.0708  | 2050 | 4.7136          |
| 0.0998        | 9.2920  | 2100 | 4.8828          |
| 0.1154        | 9.5133  | 2150 | 4.2313          |
| 0.1426        | 9.7345  | 2200 | 3.8275          |
| 0.0924        | 9.9558  | 2250 | 4.2277          |
| 0.0889        | 10.1770 | 2300 | 4.0426          |
| 0.0495        | 10.3982 | 2350 | 4.2849          |
| 0.0538        | 10.6195 | 2400 | 4.6157          |
| 0.0318        | 10.8407 | 2450 | 5.0160          |
| 0.0957        | 11.0619 | 2500 | 5.1147          |
| 0.0417        | 11.2832 | 2550 | 4.8833          |
| 0.0244        | 11.5044 | 2600 | 5.1067          |
| 0.0799        | 11.7257 | 2650 | 4.8877          |
| 0.0365        | 11.9469 | 2700 | 5.0193          |
| 0.0901        | 12.1681 | 2750 | 4.7789          |
| 0.0088        | 12.3894 | 2800 | 4.7324          |
| 0.0498        | 12.6106 | 2850 | 4.6903          |
| 0.0809        | 12.8319 | 2900 | 4.4701          |
| 0.035         | 13.0531 | 2950 | 4.6233          |
| 0.0486        | 13.2743 | 3000 | 4.8579          |
| 0.0231        | 13.4956 | 3050 | 4.9399          |
| 0.0677        | 13.7168 | 3100 | 4.8829          |
| 0.028         | 13.9381 | 3150 | 5.1337          |
| 0.0243        | 14.1593 | 3200 | 5.3634          |
| 0.0248        | 14.3805 | 3250 | 5.4940          |
| 0.0422        | 14.6018 | 3300 | 5.6946          |
| 0.0654        | 14.8230 | 3350 | 5.3121          |
| 0.0134        | 15.0442 | 3400 | 5.3630          |
| 0.0405        | 15.2655 | 3450 | 5.3444          |
| 0.0213        | 15.4867 | 3500 | 5.3298          |
| 0.0125        | 15.7080 | 3550 | 5.3672          |
| 0.0623        | 15.9292 | 3600 | 5.3024          |
| 0.0032        | 16.1504 | 3650 | 5.2147          |
| 0.0149        | 16.3717 | 3700 | 5.3809          |
| 0.0248        | 16.5929 | 3750 | 5.4913          |
| 0.03          | 16.8142 | 3800 | 5.3860          |
| 0.0007        | 17.0354 | 3850 | 5.3717          |
| 0.0032        | 17.2566 | 3900 | 5.5140          |
| 0.0029        | 17.4779 | 3950 | 5.4480          |
| 0.0055        | 17.6991 | 4000 | 5.4522          |
| 0.0349        | 17.9204 | 4050 | 5.5724          |
| 0.0007        | 18.1416 | 4100 | 5.6047          |
| 0.0006        | 18.3628 | 4150 | 5.6135          |
| 0.0007        | 18.5841 | 4200 | 5.6239          |
| 0.0077        | 18.8053 | 4250 | 5.6692          |
| 0.009         | 19.0265 | 4300 | 5.6640          |
| 0.009         | 19.2478 | 4350 | 5.6822          |
| 0.0007        | 19.4690 | 4400 | 5.7342          |
| 0.0073        | 19.6903 | 4450 | 5.7320          |
| 0.015         | 19.9115 | 4500 | 5.7326          |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3