---
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: 4.6126

## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 5.2641        | 0.2212  | 50   | 4.8696          |
| 4.6026        | 0.4425  | 100  | 4.2722          |
| 4.3484        | 0.6637  | 150  | 4.0328          |
| 3.879         | 0.8850  | 200  | 3.6907          |
| 3.5541        | 1.1062  | 250  | 3.3437          |
| 3.3072        | 1.3274  | 300  | 3.1499          |
| 3.1514        | 1.5487  | 350  | 2.9365          |
| 2.9353        | 1.7699  | 400  | 2.7036          |
| 2.4954        | 1.9912  | 450  | 2.7155          |
| 1.9393        | 2.2124  | 500  | 2.8356          |
| 1.8631        | 2.4336  | 550  | 2.4434          |
| 1.9553        | 2.6549  | 600  | 2.5365          |
| 2.0108        | 2.8761  | 650  | 2.5717          |
| 1.8383        | 3.0973  | 700  | 2.5751          |
| 1.3356        | 3.3186  | 750  | 2.5472          |
| 1.3101        | 3.5398  | 800  | 2.6720          |
| 1.3699        | 3.7611  | 850  | 2.4359          |
| 1.421         | 3.9823  | 900  | 2.9012          |
| 1.1819        | 4.2035  | 950  | 2.9297          |
| 0.9407        | 4.4248  | 1000 | 2.7371          |
| 1.0575        | 4.6460  | 1050 | 2.3495          |
| 0.9061        | 4.8673  | 1100 | 2.5941          |
| 0.8149        | 5.0885  | 1150 | 2.7071          |
| 0.7002        | 5.3097  | 1200 | 3.2910          |
| 1.009         | 5.5310  | 1250 | 2.7820          |
| 0.6106        | 5.7522  | 1300 | 2.9551          |
| 0.7998        | 5.9735  | 1350 | 3.0283          |
| 0.5198        | 6.1947  | 1400 | 3.0532          |
| 0.5274        | 6.4159  | 1450 | 3.3331          |
| 0.4868        | 6.6372  | 1500 | 3.0930          |
| 0.4724        | 6.8584  | 1550 | 3.3668          |
| 0.6184        | 7.0796  | 1600 | 3.1645          |
| 0.4337        | 7.3009  | 1650 | 3.3045          |
| 0.4681        | 7.5221  | 1700 | 3.3785          |
| 0.3815        | 7.7434  | 1750 | 3.6287          |
| 0.4704        | 7.9646  | 1800 | 3.6386          |
| 0.2866        | 8.1858  | 1850 | 3.8093          |
| 0.4064        | 8.4071  | 1900 | 3.6475          |
| 0.4187        | 8.6283  | 1950 | 3.4646          |
| 0.4037        | 8.8496  | 2000 | 3.8256          |
| 0.3989        | 9.0708  | 2050 | 3.7898          |
| 0.1772        | 9.2920  | 2100 | 3.9931          |
| 0.2577        | 9.5133  | 2150 | 3.7201          |
| 0.3283        | 9.7345  | 2200 | 3.7783          |
| 0.416         | 9.9558  | 2250 | 3.7312          |
| 0.1935        | 10.1770 | 2300 | 3.8151          |
| 0.1934        | 10.3982 | 2350 | 3.6563          |
| 0.2502        | 10.6195 | 2400 | 3.9194          |
| 0.3274        | 10.8407 | 2450 | 3.6391          |
| 0.0669        | 11.0619 | 2500 | 3.9782          |
| 0.144         | 11.2832 | 2550 | 3.9159          |
| 0.1992        | 11.5044 | 2600 | 4.2785          |
| 0.1433        | 11.7257 | 2650 | 4.3765          |
| 0.204         | 11.9469 | 2700 | 4.1064          |
| 0.094         | 12.1681 | 2750 | 4.0756          |
| 0.0549        | 12.3894 | 2800 | 4.3475          |
| 0.1252        | 12.6106 | 2850 | 4.3339          |
| 0.2964        | 12.8319 | 2900 | 4.0766          |
| 0.0759        | 13.0531 | 2950 | 4.0707          |
| 0.019         | 13.2743 | 3000 | 4.2173          |
| 0.1115        | 13.4956 | 3050 | 4.2590          |
| 0.0624        | 13.7168 | 3100 | 4.1736          |
| 0.1996        | 13.9381 | 3150 | 4.2134          |
| 0.1371        | 14.1593 | 3200 | 4.3083          |
| 0.0826        | 14.3805 | 3250 | 4.3719          |
| 0.0729        | 14.6018 | 3300 | 4.3055          |
| 0.0893        | 14.8230 | 3350 | 4.2607          |
| 0.0209        | 15.0442 | 3400 | 4.3385          |
| 0.0463        | 15.2655 | 3450 | 4.5433          |
| 0.0498        | 15.4867 | 3500 | 4.4161          |
| 0.0544        | 15.7080 | 3550 | 4.5817          |
| 0.1237        | 15.9292 | 3600 | 4.3659          |
| 0.0696        | 16.1504 | 3650 | 4.1952          |
| 0.0654        | 16.3717 | 3700 | 4.2650          |
| 0.1063        | 16.5929 | 3750 | 4.1685          |
| 0.0564        | 16.8142 | 3800 | 4.2705          |
| 0.0212        | 17.0354 | 3850 | 4.3499          |
| 0.0131        | 17.2566 | 3900 | 4.3843          |
| 0.0044        | 17.4779 | 3950 | 4.4541          |
| 0.0719        | 17.6991 | 4000 | 4.4613          |
| 0.0271        | 17.9204 | 4050 | 4.5354          |
| 0.0073        | 18.1416 | 4100 | 4.6207          |
| 0.0037        | 18.3628 | 4150 | 4.6541          |
| 0.0171        | 18.5841 | 4200 | 4.6636          |
| 0.0345        | 18.8053 | 4250 | 4.6466          |
| 0.103         | 19.0265 | 4300 | 4.5768          |
| 0.0232        | 19.2478 | 4350 | 4.6006          |
| 0.0162        | 19.4690 | 4400 | 4.6079          |
| 0.0261        | 19.6903 | 4450 | 4.6057          |
| 0.0083        | 19.9115 | 4500 | 4.6126          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1