---
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: 4.7623

## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 5.2477        | 0.2212  | 50   | 4.4955          |
| 4.4322        | 0.4425  | 100  | 4.0859          |
| 4.2098        | 0.6637  | 150  | 3.8177          |
| 3.8664        | 0.8850  | 200  | 3.5806          |
| 3.5251        | 1.1062  | 250  | 3.5032          |
| 3.1732        | 1.3274  | 300  | 3.2472          |
| 3.0841        | 1.5487  | 350  | 3.0947          |
| 2.8536        | 1.7699  | 400  | 2.7800          |
| 2.4276        | 1.9912  | 450  | 2.7769          |
| 2.06          | 2.2124  | 500  | 2.6578          |
| 1.8173        | 2.4336  | 550  | 2.6715          |
| 2.1107        | 2.6549  | 600  | 2.5620          |
| 2.1352        | 2.8761  | 650  | 2.3209          |
| 1.5368        | 3.0973  | 700  | 2.2305          |
| 1.3107        | 3.3186  | 750  | 2.6482          |
| 1.4519        | 3.5398  | 800  | 2.3794          |
| 1.2756        | 3.7611  | 850  | 2.3672          |
| 1.2282        | 3.9823  | 900  | 2.2342          |
| 1.0882        | 4.2035  | 950  | 2.7453          |
| 0.9957        | 4.4248  | 1000 | 2.7899          |
| 1.0055        | 4.6460  | 1050 | 2.7979          |
| 0.9377        | 4.8673  | 1100 | 2.5045          |
| 1.0285        | 5.0885  | 1150 | 2.4579          |
| 0.6299        | 5.3097  | 1200 | 2.7204          |
| 0.8789        | 5.5310  | 1250 | 2.6098          |
| 0.5642        | 5.7522  | 1300 | 2.7831          |
| 0.6949        | 5.9735  | 1350 | 3.0893          |
| 0.4063        | 6.1947  | 1400 | 2.8284          |
| 0.5117        | 6.4159  | 1450 | 3.0634          |
| 0.4416        | 6.6372  | 1500 | 3.3999          |
| 0.4999        | 6.8584  | 1550 | 3.2898          |
| 0.5086        | 7.0796  | 1600 | 3.4221          |
| 0.3996        | 7.3009  | 1650 | 3.0418          |
| 0.235         | 7.5221  | 1700 | 3.3613          |
| 0.4907        | 7.7434  | 1750 | 3.1062          |
| 0.3033        | 7.9646  | 1800 | 4.0306          |
| 0.3901        | 8.1858  | 1850 | 3.8258          |
| 0.3625        | 8.4071  | 1900 | 3.2560          |
| 0.3074        | 8.6283  | 1950 | 3.6874          |
| 0.3582        | 8.8496  | 2000 | 3.2337          |
| 0.2091        | 9.0708  | 2050 | 3.2660          |
| 0.2416        | 9.2920  | 2100 | 3.4408          |
| 0.1241        | 9.5133  | 2150 | 3.6883          |
| 0.2945        | 9.7345  | 2200 | 3.5552          |
| 0.2575        | 9.9558  | 2250 | 3.3925          |
| 0.258         | 10.1770 | 2300 | 3.8662          |
| 0.1662        | 10.3982 | 2350 | 3.6742          |
| 0.1491        | 10.6195 | 2400 | 4.3579          |
| 0.2379        | 10.8407 | 2450 | 4.1496          |
| 0.0899        | 11.0619 | 2500 | 4.2631          |
| 0.026         | 11.2832 | 2550 | 4.3676          |
| 0.1356        | 11.5044 | 2600 | 4.1160          |
| 0.0734        | 11.7257 | 2650 | 3.8254          |
| 0.2507        | 11.9469 | 2700 | 3.9717          |
| 0.1241        | 12.1681 | 2750 | 3.7671          |
| 0.0207        | 12.3894 | 2800 | 3.9668          |
| 0.0662        | 12.6106 | 2850 | 4.0811          |
| 0.1262        | 12.8319 | 2900 | 3.9894          |
| 0.0483        | 13.0531 | 2950 | 4.0627          |
| 0.0889        | 13.2743 | 3000 | 4.1365          |
| 0.0311        | 13.4956 | 3050 | 4.1390          |
| 0.0992        | 13.7168 | 3100 | 4.0020          |
| 0.1021        | 13.9381 | 3150 | 3.8962          |
| 0.109         | 14.1593 | 3200 | 4.2122          |
| 0.0164        | 14.3805 | 3250 | 4.3584          |
| 0.0663        | 14.6018 | 3300 | 4.1452          |
| 0.0702        | 14.8230 | 3350 | 4.2793          |
| 0.0435        | 15.0442 | 3400 | 4.3782          |
| 0.0504        | 15.2655 | 3450 | 4.3851          |
| 0.0185        | 15.4867 | 3500 | 4.6016          |
| 0.0795        | 15.7080 | 3550 | 4.5381          |
| 0.049         | 15.9292 | 3600 | 4.2093          |
| 0.0608        | 16.1504 | 3650 | 4.3391          |
| 0.0953        | 16.3717 | 3700 | 4.2657          |
| 0.0603        | 16.5929 | 3750 | 4.4624          |
| 0.0312        | 16.8142 | 3800 | 4.3063          |
| 0.0038        | 17.0354 | 3850 | 4.4603          |
| 0.0271        | 17.2566 | 3900 | 4.4354          |
| 0.0094        | 17.4779 | 3950 | 4.6563          |
| 0.019         | 17.6991 | 4000 | 4.7925          |
| 0.045         | 17.9204 | 4050 | 4.6123          |
| 0.0112        | 18.1416 | 4100 | 4.6376          |
| 0.0348        | 18.3628 | 4150 | 4.6756          |
| 0.0216        | 18.5841 | 4200 | 4.7026          |
| 0.009         | 18.8053 | 4250 | 4.7217          |
| 0.0356        | 19.0265 | 4300 | 4.7260          |
| 0.0479        | 19.2478 | 4350 | 4.7143          |
| 0.0114        | 19.4690 | 4400 | 4.7547          |
| 0.0069        | 19.6903 | 4450 | 4.7605          |
| 0.0053        | 19.9115 | 4500 | 4.7623          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1