---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv2-base-uncased
tags:
- generated_from_trainer
model-index:
- name: layout2
  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. -->

# layout2

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: 4.9306

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 5.3459        | 0.22  | 50   | 4.5773          |
| 4.4535        | 0.44  | 100  | 4.3372          |
| 4.0847        | 0.66  | 150  | 3.7812          |
| 3.8993        | 0.88  | 200  | 3.5418          |
| 3.5723        | 1.11  | 250  | 3.4054          |
| 3.1247        | 1.33  | 300  | 3.1567          |
| 3.1067        | 1.55  | 350  | 2.8839          |
| 2.9002        | 1.77  | 400  | 2.9007          |
| 2.7197        | 1.99  | 450  | 3.1319          |
| 2.0518        | 2.21  | 500  | 2.8704          |
| 1.9376        | 2.43  | 550  | 2.5644          |
| 1.9025        | 2.65  | 600  | 2.5909          |
| 2.1491        | 2.88  | 650  | 2.2353          |
| 1.5984        | 3.1   | 700  | 2.2114          |
| 1.4801        | 3.32  | 750  | 2.5351          |
| 1.2501        | 3.54  | 800  | 2.2936          |
| 1.2647        | 3.76  | 850  | 2.2360          |
| 1.1896        | 3.98  | 900  | 2.3516          |
| 0.8484        | 4.2   | 950  | 2.9913          |
| 0.8924        | 4.42  | 1000 | 2.6146          |
| 0.8342        | 4.65  | 1050 | 3.0150          |
| 1.0721        | 4.87  | 1100 | 2.8298          |
| 0.6878        | 5.09  | 1150 | 2.9925          |
| 0.6807        | 5.31  | 1200 | 2.9388          |
| 0.6139        | 5.53  | 1250 | 3.0299          |
| 0.7792        | 5.75  | 1300 | 2.4786          |
| 0.6837        | 5.97  | 1350 | 3.0713          |
| 0.4388        | 6.19  | 1400 | 3.2049          |
| 0.5377        | 6.42  | 1450 | 3.1746          |
| 0.6028        | 6.64  | 1500 | 3.1708          |
| 0.6295        | 6.86  | 1550 | 3.4203          |
| 0.5441        | 7.08  | 1600 | 3.3876          |
| 0.4105        | 7.3   | 1650 | 3.4065          |
| 0.3848        | 7.52  | 1700 | 3.4103          |
| 0.507         | 7.74  | 1750 | 3.2958          |
| 0.3741        | 7.96  | 1800 | 3.9773          |
| 0.297         | 8.19  | 1850 | 4.1055          |
| 0.4131        | 8.41  | 1900 | 3.7588          |
| 0.3332        | 8.63  | 1950 | 3.6752          |
| 0.2608        | 8.85  | 2000 | 4.2848          |
| 0.2652        | 9.07  | 2050 | 3.6098          |
| 0.1967        | 9.29  | 2100 | 3.7971          |
| 0.3771        | 9.51  | 2150 | 3.6206          |
| 0.1677        | 9.73  | 2200 | 4.3747          |
| 0.1711        | 9.96  | 2250 | 4.2229          |
| 0.0949        | 10.18 | 2300 | 4.5390          |
| 0.1804        | 10.4  | 2350 | 4.3297          |
| 0.1313        | 10.62 | 2400 | 4.3467          |
| 0.2292        | 10.84 | 2450 | 4.4368          |
| 0.1342        | 11.06 | 2500 | 4.2101          |
| 0.1411        | 11.28 | 2550 | 4.2723          |
| 0.0907        | 11.5  | 2600 | 4.3821          |
| 0.1656        | 11.73 | 2650 | 4.3373          |
| 0.0757        | 11.95 | 2700 | 4.3297          |
| 0.1571        | 12.17 | 2750 | 4.1193          |
| 0.1015        | 12.39 | 2800 | 4.2492          |
| 0.0785        | 12.61 | 2850 | 4.3998          |
| 0.1003        | 12.83 | 2900 | 4.3994          |
| 0.0884        | 13.05 | 2950 | 4.4914          |
| 0.0261        | 13.27 | 3000 | 4.5869          |
| 0.1138        | 13.5  | 3050 | 4.4546          |
| 0.1481        | 13.72 | 3100 | 4.6197          |
| 0.0814        | 13.94 | 3150 | 4.4034          |
| 0.0079        | 14.16 | 3200 | 4.7623          |
| 0.0641        | 14.38 | 3250 | 4.5933          |
| 0.0499        | 14.6  | 3300 | 4.6543          |
| 0.1052        | 14.82 | 3350 | 4.2287          |
| 0.0775        | 15.04 | 3400 | 4.3898          |
| 0.0561        | 15.27 | 3450 | 4.5852          |
| 0.0443        | 15.49 | 3500 | 4.6139          |
| 0.006         | 15.71 | 3550 | 4.7572          |
| 0.1517        | 15.93 | 3600 | 4.5492          |
| 0.0473        | 16.15 | 3650 | 4.6196          |
| 0.0534        | 16.37 | 3700 | 4.5726          |
| 0.0069        | 16.59 | 3750 | 4.7234          |
| 0.0515        | 16.81 | 3800 | 4.7475          |
| 0.0187        | 17.04 | 3850 | 4.7945          |
| 0.0616        | 17.26 | 3900 | 4.7330          |
| 0.0385        | 17.48 | 3950 | 4.6939          |
| 0.0377        | 17.7  | 4000 | 4.7966          |
| 0.0039        | 17.92 | 4050 | 4.7507          |
| 0.027         | 18.14 | 4100 | 4.7653          |
| 0.0193        | 18.36 | 4150 | 4.7589          |
| 0.0318        | 18.58 | 4200 | 4.8174          |
| 0.0094        | 18.81 | 4250 | 4.8776          |
| 0.035         | 19.03 | 4300 | 4.9437          |
| 0.0118        | 19.25 | 4350 | 4.9520          |
| 0.0036        | 19.47 | 4400 | 4.9428          |
| 0.0082        | 19.69 | 4450 | 4.9414          |
| 0.004         | 19.91 | 4500 | 4.9306          |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.0+cu118
- Datasets 2.17.1
- Tokenizers 0.13.2