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

# layoutlmv2-base-uncased_finetuned_docvqa

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: 5.5645

## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 5.3224        | 0.2212  | 50   | 4.5586          |
| 4.5246        | 0.4425  | 100  | 4.1173          |
| 4.1619        | 0.6637  | 150  | 3.8601          |
| 3.7534        | 0.8850  | 200  | 3.6319          |
| 3.6105        | 1.1062  | 250  | 3.7778          |
| 3.3319        | 1.3274  | 300  | 3.1775          |
| 3.0645        | 1.5487  | 350  | 2.8592          |
| 2.8209        | 1.7699  | 400  | 2.7744          |
| 2.7174        | 1.9912  | 450  | 2.7408          |
| 2.0437        | 2.2124  | 500  | 2.7848          |
| 2.0063        | 2.4336  | 550  | 2.9319          |
| 1.9314        | 2.6549  | 600  | 2.3084          |
| 1.7939        | 2.8761  | 650  | 2.4124          |
| 1.7613        | 3.0973  | 700  | 2.5776          |
| 1.3099        | 3.3186  | 750  | 2.2375          |
| 1.4457        | 3.5398  | 800  | 2.7229          |
| 1.4964        | 3.7611  | 850  | 2.5109          |
| 1.428         | 3.9823  | 900  | 2.4552          |
| 0.9892        | 4.2035  | 950  | 3.2111          |
| 1.0568        | 4.4248  | 1000 | 2.3875          |
| 0.8754        | 4.6460  | 1050 | 2.8059          |
| 0.8201        | 4.8673  | 1100 | 2.5949          |
| 1.0239        | 5.0885  | 1150 | 2.8688          |
| 0.7348        | 5.3097  | 1200 | 2.8210          |
| 0.7866        | 5.5310  | 1250 | 2.4231          |
| 0.5954        | 5.7522  | 1300 | 2.8619          |
| 0.7299        | 5.9735  | 1350 | 2.8536          |
| 0.5132        | 6.1947  | 1400 | 2.6224          |
| 0.7035        | 6.4159  | 1450 | 3.2108          |
| 0.5626        | 6.6372  | 1500 | 2.8695          |
| 0.431         | 6.8584  | 1550 | 3.3508          |
| 0.4354        | 7.0796  | 1600 | 3.4196          |
| 0.3896        | 7.3009  | 1650 | 3.1219          |
| 0.4899        | 7.5221  | 1700 | 3.0649          |
| 0.5703        | 7.7434  | 1750 | 3.0621          |
| 0.435         | 7.9646  | 1800 | 3.3686          |
| 0.3251        | 8.1858  | 1850 | 3.2093          |
| 0.2464        | 8.4071  | 1900 | 3.9491          |
| 0.4524        | 8.6283  | 1950 | 3.4324          |
| 0.5715        | 8.8496  | 2000 | 3.5811          |
| 0.3552        | 9.0708  | 2050 | 3.9434          |
| 0.1147        | 9.2920  | 2100 | 4.5776          |
| 0.2613        | 9.5133  | 2150 | 4.0439          |
| 0.5679        | 9.7345  | 2200 | 3.4187          |
| 0.3372        | 9.9558  | 2250 | 3.3868          |
| 0.3143        | 10.1770 | 2300 | 4.2051          |
| 0.1989        | 10.3982 | 2350 | 3.7925          |
| 0.1859        | 10.6195 | 2400 | 4.1932          |
| 0.3882        | 10.8407 | 2450 | 4.1672          |
| 0.1824        | 11.0619 | 2500 | 4.3516          |
| 0.106         | 11.2832 | 2550 | 4.5112          |
| 0.2096        | 11.5044 | 2600 | 4.3784          |
| 0.1035        | 11.7257 | 2650 | 4.3866          |
| 0.2113        | 11.9469 | 2700 | 4.1279          |
| 0.2263        | 12.1681 | 2750 | 4.2749          |
| 0.1014        | 12.3894 | 2800 | 4.5176          |
| 0.1555        | 12.6106 | 2850 | 3.9479          |
| 0.1732        | 12.8319 | 2900 | 4.2414          |
| 0.1484        | 13.0531 | 2950 | 4.0296          |
| 0.1051        | 13.2743 | 3000 | 4.5086          |
| 0.1282        | 13.4956 | 3050 | 4.6194          |
| 0.1471        | 13.7168 | 3100 | 4.6707          |
| 0.1888        | 13.9381 | 3150 | 4.3906          |
| 0.0723        | 14.1593 | 3200 | 4.9790          |
| 0.0302        | 14.3805 | 3250 | 5.0363          |
| 0.1599        | 14.6018 | 3300 | 4.8371          |
| 0.1179        | 14.8230 | 3350 | 4.3327          |
| 0.1128        | 15.0442 | 3400 | 5.0618          |
| 0.0493        | 15.2655 | 3450 | 5.2469          |
| 0.0341        | 15.4867 | 3500 | 5.3640          |
| 0.0545        | 15.7080 | 3550 | 5.0736          |
| 0.0883        | 15.9292 | 3600 | 5.1372          |
| 0.0461        | 16.1504 | 3650 | 5.0354          |
| 0.0244        | 16.3717 | 3700 | 5.4353          |
| 0.0541        | 16.5929 | 3750 | 5.3114          |
| 0.0164        | 16.8142 | 3800 | 5.4107          |
| 0.0336        | 17.0354 | 3850 | 5.4258          |
| 0.0483        | 17.2566 | 3900 | 5.3555          |
| 0.0994        | 17.4779 | 3950 | 5.2090          |
| 0.0351        | 17.6991 | 4000 | 5.3768          |
| 0.0065        | 17.9204 | 4050 | 5.5076          |
| 0.0053        | 18.1416 | 4100 | 5.4823          |
| 0.0043        | 18.3628 | 4150 | 5.4850          |
| 0.0452        | 18.5841 | 4200 | 5.4849          |
| 0.0086        | 18.8053 | 4250 | 5.5881          |
| 0.0322        | 19.0265 | 4300 | 5.5167          |
| 0.0135        | 19.2478 | 4350 | 5.5502          |
| 0.0229        | 19.4690 | 4400 | 5.5385          |
| 0.042         | 19.6903 | 4450 | 5.5602          |
| 0.0404        | 19.9115 | 4500 | 5.5645          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1