---
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: 4.9512

## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 5.2951        | 0.2212  | 50   | 4.7074          |
| 4.5271        | 0.4425  | 100  | 4.1032          |
| 4.1303        | 0.6637  | 150  | 3.9369          |
| 3.8633        | 0.8850  | 200  | 3.5651          |
| 3.4747        | 1.1062  | 250  | 3.6489          |
| 3.4294        | 1.3274  | 300  | 3.1484          |
| 3.1319        | 1.5487  | 350  | 2.9161          |
| 2.8258        | 1.7699  | 400  | 2.8137          |
| 2.6171        | 1.9912  | 450  | 2.9083          |
| 2.4222        | 2.2124  | 500  | 3.0206          |
| 2.1271        | 2.4336  | 550  | 2.6056          |
| 1.9083        | 2.6549  | 600  | 2.3721          |
| 1.9685        | 2.8761  | 650  | 2.3992          |
| 1.6307        | 3.0973  | 700  | 2.7301          |
| 1.4481        | 3.3186  | 750  | 2.3406          |
| 1.4984        | 3.5398  | 800  | 2.6880          |
| 1.7125        | 3.7611  | 850  | 2.4609          |
| 1.3863        | 3.9823  | 900  | 2.3533          |
| 1.2462        | 4.2035  | 950  | 2.5440          |
| 1.0761        | 4.4248  | 1000 | 2.7272          |
| 1.1144        | 4.6460  | 1050 | 1.9797          |
| 0.9787        | 4.8673  | 1100 | 2.4466          |
| 0.8171        | 5.0885  | 1150 | 2.9085          |
| 0.8736        | 5.3097  | 1200 | 2.9959          |
| 0.9349        | 5.5310  | 1250 | 2.3175          |
| 0.7439        | 5.7522  | 1300 | 3.0023          |
| 0.7007        | 5.9735  | 1350 | 3.1554          |
| 0.4858        | 6.1947  | 1400 | 3.3196          |
| 0.7693        | 6.4159  | 1450 | 3.3589          |
| 0.4525        | 6.6372  | 1500 | 3.1226          |
| 0.442         | 6.8584  | 1550 | 3.5817          |
| 0.5321        | 7.0796  | 1600 | 3.4303          |
| 0.4044        | 7.3009  | 1650 | 3.5700          |
| 0.3062        | 7.5221  | 1700 | 4.0335          |
| 0.5116        | 7.7434  | 1750 | 3.6335          |
| 0.3481        | 7.9646  | 1800 | 3.5987          |
| 0.2781        | 8.1858  | 1850 | 4.0488          |
| 0.3054        | 8.4071  | 1900 | 3.4694          |
| 0.3572        | 8.6283  | 1950 | 3.7605          |
| 0.3524        | 8.8496  | 2000 | 3.9977          |
| 0.3551        | 9.0708  | 2050 | 3.7106          |
| 0.1455        | 9.2920  | 2100 | 3.8854          |
| 0.3655        | 9.5133  | 2150 | 3.6476          |
| 0.348         | 9.7345  | 2200 | 3.5709          |
| 0.299         | 9.9558  | 2250 | 3.6914          |
| 0.1781        | 10.1770 | 2300 | 3.7616          |
| 0.1812        | 10.3982 | 2350 | 3.7328          |
| 0.3197        | 10.6195 | 2400 | 4.3628          |
| 0.2139        | 10.8407 | 2450 | 4.3765          |
| 0.0266        | 11.0619 | 2500 | 4.6882          |
| 0.0659        | 11.2832 | 2550 | 4.5060          |
| 0.2312        | 11.5044 | 2600 | 4.1473          |
| 0.1366        | 11.7257 | 2650 | 4.2983          |
| 0.2264        | 11.9469 | 2700 | 4.2400          |
| 0.165         | 12.1681 | 2750 | 4.0799          |
| 0.0443        | 12.3894 | 2800 | 4.2081          |
| 0.178         | 12.6106 | 2850 | 4.0656          |
| 0.2517        | 12.8319 | 2900 | 4.2621          |
| 0.1208        | 13.0531 | 2950 | 4.6150          |
| 0.0767        | 13.2743 | 3000 | 4.6056          |
| 0.0789        | 13.4956 | 3050 | 4.2637          |
| 0.0492        | 13.7168 | 3100 | 4.3896          |
| 0.1782        | 13.9381 | 3150 | 4.3427          |
| 0.0968        | 14.1593 | 3200 | 4.5666          |
| 0.0287        | 14.3805 | 3250 | 4.6159          |
| 0.0516        | 14.6018 | 3300 | 4.4566          |
| 0.1008        | 14.8230 | 3350 | 4.5481          |
| 0.052         | 15.0442 | 3400 | 4.6010          |
| 0.0334        | 15.2655 | 3450 | 4.6442          |
| 0.027         | 15.4867 | 3500 | 4.7174          |
| 0.0791        | 15.7080 | 3550 | 4.5374          |
| 0.147         | 15.9292 | 3600 | 4.6980          |
| 0.1186        | 16.1504 | 3650 | 4.5936          |
| 0.0373        | 16.3717 | 3700 | 4.6215          |
| 0.0445        | 16.5929 | 3750 | 4.4737          |
| 0.0325        | 16.8142 | 3800 | 4.6176          |
| 0.0842        | 17.0354 | 3850 | 4.7082          |
| 0.0097        | 17.2566 | 3900 | 4.7821          |
| 0.0707        | 17.4779 | 3950 | 4.7606          |
| 0.0583        | 17.6991 | 4000 | 4.8275          |
| 0.0222        | 17.9204 | 4050 | 4.8638          |
| 0.0413        | 18.1416 | 4100 | 4.8912          |
| 0.0097        | 18.3628 | 4150 | 4.9439          |
| 0.0075        | 18.5841 | 4200 | 4.9960          |
| 0.0735        | 18.8053 | 4250 | 4.9482          |
| 0.0821        | 19.0265 | 4300 | 5.0201          |
| 0.0254        | 19.2478 | 4350 | 4.9772          |
| 0.1105        | 19.4690 | 4400 | 4.9629          |
| 0.0649        | 19.6903 | 4450 | 4.9474          |
| 0.025         | 19.9115 | 4500 | 4.9512          |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.0
- Datasets 3.0.1
- Tokenizers 0.20.1