---
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: 4.4147

## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 5.2445        | 0.2212  | 50   | 4.5117          |
| 4.4073        | 0.4425  | 100  | 4.2219          |
| 4.1282        | 0.6637  | 150  | 3.8024          |
| 3.8337        | 0.8850  | 200  | 3.6136          |
| 3.5425        | 1.1062  | 250  | 3.4874          |
| 3.3022        | 1.3274  | 300  | 3.1532          |
| 3.2627        | 1.5487  | 350  | 3.0497          |
| 2.9534        | 1.7699  | 400  | 3.0351          |
| 2.7062        | 1.9912  | 450  | 3.0241          |
| 2.3171        | 2.2124  | 500  | 2.6357          |
| 2.0499        | 2.4336  | 550  | 2.3957          |
| 1.9222        | 2.6549  | 600  | 2.4198          |
| 1.8248        | 2.8761  | 650  | 2.5430          |
| 1.5168        | 3.0973  | 700  | 4.2506          |
| 1.4417        | 3.3186  | 750  | 2.3309          |
| 1.3993        | 3.5398  | 800  | 2.3422          |
| 1.3945        | 3.7611  | 850  | 2.0276          |
| 1.138         | 3.9823  | 900  | 2.3541          |
| 1.2168        | 4.2035  | 950  | 2.8071          |
| 1.1358        | 4.4248  | 1000 | 2.6772          |
| 1.0205        | 4.6460  | 1050 | 2.7978          |
| 0.9784        | 4.8673  | 1100 | 3.3150          |
| 1.001         | 5.0885  | 1150 | 2.5239          |
| 0.8487        | 5.3097  | 1200 | 2.9815          |
| 1.0126        | 5.5310  | 1250 | 3.2436          |
| 0.6363        | 5.7522  | 1300 | 3.2784          |
| 0.9224        | 5.9735  | 1350 | 3.4480          |
| 0.6946        | 6.1947  | 1400 | 3.1487          |
| 0.6052        | 6.4159  | 1450 | 3.4397          |
| 0.5203        | 6.6372  | 1500 | 2.9999          |
| 0.6589        | 6.8584  | 1550 | 3.2889          |
| 0.6399        | 7.0796  | 1600 | 3.1920          |
| 0.4313        | 7.3009  | 1650 | 2.9790          |
| 0.3867        | 7.5221  | 1700 | 3.4399          |
| 0.5132        | 7.7434  | 1750 | 3.0626          |
| 0.4955        | 7.9646  | 1800 | 3.2692          |
| 0.3658        | 8.1858  | 1850 | 3.4662          |
| 0.2021        | 8.4071  | 1900 | 3.7119          |
| 0.394         | 8.6283  | 1950 | 3.5633          |
| 0.4442        | 8.8496  | 2000 | 3.7246          |
| 0.3807        | 9.0708  | 2050 | 3.5174          |
| 0.2692        | 9.2920  | 2100 | 3.8268          |
| 0.3595        | 9.5133  | 2150 | 3.6366          |
| 0.3495        | 9.7345  | 2200 | 3.5126          |
| 0.3814        | 9.9558  | 2250 | 3.4845          |
| 0.2319        | 10.1770 | 2300 | 3.5154          |
| 0.1587        | 10.3982 | 2350 | 3.9049          |
| 0.2771        | 10.6195 | 2400 | 3.9095          |
| 0.2156        | 10.8407 | 2450 | 3.9481          |
| 0.1906        | 11.0619 | 2500 | 3.9076          |
| 0.2064        | 11.2832 | 2550 | 3.9890          |
| 0.1756        | 11.5044 | 2600 | 3.8731          |
| 0.1934        | 11.7257 | 2650 | 3.8914          |
| 0.1177        | 11.9469 | 2700 | 4.0169          |
| 0.2135        | 12.1681 | 2750 | 3.6795          |
| 0.1198        | 12.3894 | 2800 | 3.9709          |
| 0.1219        | 12.6106 | 2850 | 3.7425          |
| 0.1073        | 12.8319 | 2900 | 4.2397          |
| 0.1428        | 13.0531 | 2950 | 3.9107          |
| 0.0728        | 13.2743 | 3000 | 4.2249          |
| 0.0516        | 13.4956 | 3050 | 3.9716          |
| 0.1044        | 13.7168 | 3100 | 4.2036          |
| 0.2026        | 13.9381 | 3150 | 3.8552          |
| 0.1182        | 14.1593 | 3200 | 4.0365          |
| 0.0368        | 14.3805 | 3250 | 4.3629          |
| 0.0331        | 14.6018 | 3300 | 4.4697          |
| 0.1629        | 14.8230 | 3350 | 3.9966          |
| 0.0619        | 15.0442 | 3400 | 4.1223          |
| 0.0167        | 15.2655 | 3450 | 4.2150          |
| 0.0602        | 15.4867 | 3500 | 4.1427          |
| 0.1045        | 15.7080 | 3550 | 3.9883          |
| 0.0629        | 15.9292 | 3600 | 4.1485          |
| 0.0492        | 16.1504 | 3650 | 3.9531          |
| 0.0657        | 16.3717 | 3700 | 4.2826          |
| 0.0354        | 16.5929 | 3750 | 4.1867          |
| 0.0327        | 16.8142 | 3800 | 4.1699          |
| 0.0045        | 17.0354 | 3850 | 4.1904          |
| 0.0139        | 17.2566 | 3900 | 4.2937          |
| 0.0373        | 17.4779 | 3950 | 4.1179          |
| 0.039         | 17.6991 | 4000 | 4.1837          |
| 0.0717        | 17.9204 | 4050 | 4.2483          |
| 0.0316        | 18.1416 | 4100 | 4.2423          |
| 0.0041        | 18.3628 | 4150 | 4.2651          |
| 0.0268        | 18.5841 | 4200 | 4.3379          |
| 0.0156        | 18.8053 | 4250 | 4.3978          |
| 0.0265        | 19.0265 | 4300 | 4.3942          |
| 0.0461        | 19.2478 | 4350 | 4.4056          |
| 0.0195        | 19.4690 | 4400 | 4.4082          |
| 0.0105        | 19.6903 | 4450 | 4.4160          |
| 0.0387        | 19.9115 | 4500 | 4.4147          |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1