transformers tensorboard safetensors layoutlmv2 document-question-answering generated_from_trainer base_model:microsoft/layoutlmv2-base-uncased license:cc-by-nc-sa-4.0 endpoints_compatible region:us
---
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: 4.6788

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 5.3193        | 0.22  | 50   | 4.5453          |
| 4.5115        | 0.44  | 100  | 4.1632          |
| 4.1316        | 0.66  | 150  | 3.8496          |
| 3.7911        | 0.88  | 200  | 3.7418          |
| 3.5175        | 1.11  | 250  | 3.9454          |
| 3.2171        | 1.33  | 300  | 3.0430          |
| 3.0377        | 1.55  | 350  | 3.1317          |
| 3.1081        | 1.77  | 400  | 2.8709          |
| 2.6219        | 1.99  | 450  | 2.9745          |
| 2.2922        | 2.21  | 500  | 3.0184          |
| 2.2245        | 2.43  | 550  | 2.6649          |
| 2.0918        | 2.65  | 600  | 2.3156          |
| 2.0339        | 2.88  | 650  | 2.4970          |
| 1.7088        | 3.1   | 700  | 2.2817          |
| 1.4584        | 3.32  | 750  | 2.3237          |
| 1.4296        | 3.54  | 800  | 2.1868          |
| 1.4413        | 3.76  | 850  | 2.2775          |
| 1.4055        | 3.98  | 900  | 2.6660          |
| 1.0251        | 4.2   | 950  | 2.6155          |
| 1.1251        | 4.42  | 1000 | 2.9841          |
| 1.059         | 4.65  | 1050 | 2.7376          |
| 1.0179        | 4.87  | 1100 | 3.7345          |
| 1.1128        | 5.09  | 1150 | 2.6704          |
| 0.8461        | 5.31  | 1200 | 3.0422          |
| 0.86          | 5.53  | 1250 | 3.2093          |
| 0.9124        | 5.75  | 1300 | 3.2782          |
| 0.8687        | 5.97  | 1350 | 3.1477          |
| 0.7039        | 6.19  | 1400 | 2.6896          |
| 0.8908        | 6.42  | 1450 | 3.0843          |
| 0.7408        | 6.64  | 1500 | 2.9585          |
| 0.6026        | 6.86  | 1550 | 3.3629          |
| 0.4852        | 7.08  | 1600 | 3.1505          |
| 0.5496        | 7.3   | 1650 | 3.6285          |
| 0.5578        | 7.52  | 1700 | 3.3481          |
| 0.5897        | 7.74  | 1750 | 3.3201          |
| 0.4487        | 7.96  | 1800 | 3.1462          |
| 0.2182        | 8.19  | 1850 | 3.7251          |
| 0.3524        | 8.41  | 1900 | 3.5870          |
| 0.4516        | 8.63  | 1950 | 3.6300          |
| 0.5658        | 8.85  | 2000 | 3.1085          |
| 0.4877        | 9.07  | 2050 | 3.5353          |
| 0.2226        | 9.29  | 2100 | 3.6744          |
| 0.2544        | 9.51  | 2150 | 4.1244          |
| 0.6194        | 9.73  | 2200 | 3.4775          |
| 0.3759        | 9.96  | 2250 | 3.7031          |
| 0.2718        | 10.18 | 2300 | 3.6076          |
| 0.1322        | 10.4  | 2350 | 3.6885          |
| 0.2596        | 10.62 | 2400 | 3.9328          |
| 0.1675        | 10.84 | 2450 | 4.1439          |
| 0.158         | 11.06 | 2500 | 4.4306          |
| 0.1462        | 11.28 | 2550 | 4.3744          |
| 0.2187        | 11.5  | 2600 | 4.4111          |
| 0.264         | 11.73 | 2650 | 3.9780          |
| 0.1997        | 11.95 | 2700 | 4.2383          |
| 0.1369        | 12.17 | 2750 | 4.1329          |
| 0.1204        | 12.39 | 2800 | 4.2738          |
| 0.2001        | 12.61 | 2850 | 4.0106          |
| 0.2132        | 12.83 | 2900 | 4.1816          |
| 0.1472        | 13.05 | 2950 | 4.4600          |
| 0.0603        | 13.27 | 3000 | 4.0050          |
| 0.0911        | 13.5  | 3050 | 4.1838          |
| 0.1016        | 13.72 | 3100 | 4.4429          |
| 0.0887        | 13.94 | 3150 | 4.1510          |
| 0.0495        | 14.16 | 3200 | 4.2938          |
| 0.0677        | 14.38 | 3250 | 4.6133          |
| 0.1263        | 14.6  | 3300 | 4.4634          |
| 0.1953        | 14.82 | 3350 | 3.9348          |
| 0.0212        | 15.04 | 3400 | 4.1726          |
| 0.0082        | 15.27 | 3450 | 4.3512          |
| 0.0432        | 15.49 | 3500 | 4.2992          |
| 0.0975        | 15.71 | 3550 | 4.2274          |
| 0.0933        | 15.93 | 3600 | 4.4028          |
| 0.024         | 16.15 | 3650 | 4.4662          |
| 0.0964        | 16.37 | 3700 | 4.3964          |
| 0.0487        | 16.59 | 3750 | 4.4827          |
| 0.0147        | 16.81 | 3800 | 4.5577          |
| 0.0951        | 17.04 | 3850 | 4.5640          |
| 0.0508        | 17.26 | 3900 | 4.4473          |
| 0.1163        | 17.48 | 3950 | 4.4565          |
| 0.0151        | 17.7  | 4000 | 4.5511          |
| 0.0569        | 17.92 | 4050 | 4.5298          |
| 0.0639        | 18.14 | 4100 | 4.5417          |
| 0.0155        | 18.36 | 4150 | 4.6398          |
| 0.0107        | 18.58 | 4200 | 4.7664          |
| 0.0044        | 18.81 | 4250 | 4.8119          |
| 0.0906        | 19.03 | 4300 | 4.7168          |
| 0.0533        | 19.25 | 4350 | 4.7032          |
| 0.0496        | 19.47 | 4400 | 4.6918          |
| 0.0938        | 19.69 | 4450 | 4.6824          |
| 0.0483        | 19.91 | 4500 | 4.6788          |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1
- Datasets 2.17.1
- Tokenizers 0.15.2
