---
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: 5.2363

## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 4.0408        | 0.2212  | 50   | 4.0001          |
| 4.1144        | 0.4425  | 100  | 3.7920          |
| 3.8854        | 0.6637  | 150  | 3.6503          |
| 3.6048        | 0.8850  | 200  | 3.3228          |
| 3.1846        | 1.1062  | 250  | 3.6110          |
| 2.917         | 1.3274  | 300  | 2.9913          |
| 2.8848        | 1.5487  | 350  | 2.7110          |
| 2.5842        | 1.7699  | 400  | 2.4111          |
| 2.1162        | 1.9912  | 450  | 2.4839          |
| 1.8347        | 2.2124  | 500  | 2.7160          |
| 1.786         | 2.4336  | 550  | 2.5238          |
| 1.8828        | 2.6549  | 600  | 2.4274          |
| 1.8181        | 2.8761  | 650  | 2.5544          |
| 1.5656        | 3.0973  | 700  | 2.4362          |
| 1.4265        | 3.3186  | 750  | 2.9550          |
| 1.4967        | 3.5398  | 800  | 3.2754          |
| 1.2732        | 3.7611  | 850  | 3.0296          |
| 1.3162        | 3.9823  | 900  | 2.6941          |
| 1.0837        | 4.2035  | 950  | 2.9119          |
| 1.1094        | 4.4248  | 1000 | 3.0181          |
| 1.1846        | 4.6460  | 1050 | 2.6419          |
| 1.5768        | 4.8673  | 1100 | 4.0184          |
| 1.4084        | 5.0885  | 1150 | 3.1371          |
| 0.9783        | 5.3097  | 1200 | 2.9210          |
| 0.984         | 5.5310  | 1250 | 3.0042          |
| 0.7546        | 5.7522  | 1300 | 3.1277          |
| 0.799         | 5.9735  | 1350 | 3.0501          |
| 0.6629        | 6.1947  | 1400 | 3.2626          |
| 0.8973        | 6.4159  | 1450 | 3.2922          |
| 0.6816        | 6.6372  | 1500 | 3.0462          |
| 0.539         | 6.8584  | 1550 | 3.1018          |
| 0.6871        | 7.0796  | 1600 | 3.1925          |
| 0.4569        | 7.3009  | 1650 | 3.2120          |
| 0.6451        | 7.5221  | 1700 | 2.9812          |
| 0.5579        | 7.7434  | 1750 | 3.3052          |
| 0.4851        | 7.9646  | 1800 | 4.1491          |
| 0.5851        | 8.1858  | 1850 | 3.5338          |
| 0.4344        | 8.4071  | 1900 | 3.4542          |
| 0.5021        | 8.6283  | 1950 | 3.2402          |
| 0.4699        | 8.8496  | 2000 | 3.3066          |
| 0.4668        | 9.0708  | 2050 | 3.6041          |
| 0.2258        | 9.2920  | 2100 | 3.6862          |
| 0.4708        | 9.5133  | 2150 | 3.7622          |
| 0.3933        | 9.7345  | 2200 | 3.7370          |
| 0.3858        | 9.9558  | 2250 | 3.3631          |
| 0.3359        | 10.1770 | 2300 | 3.6203          |
| 0.2365        | 10.3982 | 2350 | 3.7388          |
| 0.3147        | 10.6195 | 2400 | 3.8653          |
| 0.3401        | 10.8407 | 2450 | 4.0243          |
| 0.1644        | 11.0619 | 2500 | 4.1857          |
| 0.142         | 11.2832 | 2550 | 4.3611          |
| 0.266         | 11.5044 | 2600 | 4.2761          |
| 0.1592        | 11.7257 | 2650 | 4.3012          |
| 0.1126        | 11.9469 | 2700 | 4.3518          |
| 0.1409        | 12.1681 | 2750 | 4.4466          |
| 0.0731        | 12.3894 | 2800 | 4.3459          |
| 0.1243        | 12.6106 | 2850 | 4.3446          |
| 0.2672        | 12.8319 | 2900 | 4.3548          |
| 0.228         | 13.0531 | 2950 | 4.1020          |
| 0.0622        | 13.2743 | 3000 | 4.4363          |
| 0.1287        | 13.4956 | 3050 | 4.5345          |
| 0.1974        | 13.7168 | 3100 | 4.6727          |
| 0.2213        | 13.9381 | 3150 | 4.3807          |
| 0.1551        | 14.1593 | 3200 | 4.4805          |
| 0.1295        | 14.3805 | 3250 | 4.7027          |
| 0.0664        | 14.6018 | 3300 | 4.7583          |
| 0.1159        | 14.8230 | 3350 | 4.3252          |
| 0.02          | 15.0442 | 3400 | 4.6594          |
| 0.0438        | 15.2655 | 3450 | 4.8679          |
| 0.0495        | 15.4867 | 3500 | 5.1235          |
| 0.1143        | 15.7080 | 3550 | 5.1614          |
| 0.1405        | 15.9292 | 3600 | 5.1302          |
| 0.0351        | 16.1504 | 3650 | 5.0780          |
| 0.1258        | 16.3717 | 3700 | 5.1000          |
| 0.0387        | 16.5929 | 3750 | 5.0849          |
| 0.0809        | 16.8142 | 3800 | 4.9809          |
| 0.0955        | 17.0354 | 3850 | 5.0030          |
| 0.0347        | 17.2566 | 3900 | 5.0040          |
| 0.0716        | 17.4779 | 3950 | 4.9608          |
| 0.0417        | 17.6991 | 4000 | 5.0922          |
| 0.1394        | 17.9204 | 4050 | 5.1081          |
| 0.0612        | 18.1416 | 4100 | 5.1859          |
| 0.0057        | 18.3628 | 4150 | 5.2126          |
| 0.0965        | 18.5841 | 4200 | 5.1589          |
| 0.0131        | 18.8053 | 4250 | 5.1224          |
| 0.0922        | 19.0265 | 4300 | 5.1521          |
| 0.0353        | 19.2478 | 4350 | 5.1961          |
| 0.0351        | 19.4690 | 4400 | 5.2249          |
| 0.0161        | 19.6903 | 4450 | 5.2304          |
| 0.0095        | 19.9115 | 4500 | 5.2363          |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1