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

# tmp

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: 5.1124

## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 5.2734        | 0.2212  | 50   | 4.4270          |
| 4.3976        | 0.4425  | 100  | 4.0382          |
| 4.0042        | 0.6637  | 150  | 3.8146          |
| 3.7912        | 0.8850  | 200  | 3.5961          |
| 3.4488        | 1.1062  | 250  | 3.7510          |
| 3.1503        | 1.3274  | 300  | 3.1755          |
| 3.1023        | 1.5487  | 350  | 2.8744          |
| 2.7424        | 1.7699  | 400  | 2.7684          |
| 2.3707        | 1.9912  | 450  | 2.7751          |
| 2.0726        | 2.2124  | 500  | 2.8069          |
| 1.7808        | 2.4336  | 550  | 2.4706          |
| 1.9086        | 2.6549  | 600  | 2.3128          |
| 1.8711        | 2.8761  | 650  | 2.2711          |
| 1.5378        | 3.0973  | 700  | 2.7780          |
| 1.4234        | 3.3186  | 750  | 2.3195          |
| 1.3624        | 3.5398  | 800  | 2.8083          |
| 1.5029        | 3.7611  | 850  | 2.3164          |
| 1.4002        | 3.9823  | 900  | 2.2043          |
| 0.993         | 4.2035  | 950  | 2.3923          |
| 1.1307        | 4.4248  | 1000 | 2.6620          |
| 1.0207        | 4.6460  | 1050 | 3.0029          |
| 0.9392        | 4.8673  | 1100 | 2.7303          |
| 0.8404        | 5.0885  | 1150 | 2.9590          |
| 0.7301        | 5.3097  | 1200 | 3.0281          |
| 0.723         | 5.5310  | 1250 | 2.8981          |
| 0.5396        | 5.7522  | 1300 | 3.2900          |
| 0.8811        | 5.9735  | 1350 | 2.8048          |
| 0.5488        | 6.1947  | 1400 | 3.0010          |
| 0.5603        | 6.4159  | 1450 | 3.3632          |
| 0.6611        | 6.6372  | 1500 | 3.1133          |
| 0.589         | 6.8584  | 1550 | 2.9019          |
| 0.5597        | 7.0796  | 1600 | 3.5935          |
| 0.2414        | 7.3009  | 1650 | 3.6715          |
| 0.5152        | 7.5221  | 1700 | 3.3859          |
| 0.3482        | 7.7434  | 1750 | 3.4798          |
| 0.4217        | 7.9646  | 1800 | 3.6040          |
| 0.3183        | 8.1858  | 1850 | 3.9913          |
| 0.1838        | 8.4071  | 1900 | 4.0946          |
| 0.2845        | 8.6283  | 1950 | 3.8923          |
| 0.3402        | 8.8496  | 2000 | 3.6999          |
| 0.3264        | 9.0708  | 2050 | 3.7774          |
| 0.205         | 9.2920  | 2100 | 3.9310          |
| 0.2841        | 9.5133  | 2150 | 4.1358          |
| 0.4066        | 9.7345  | 2200 | 3.8157          |
| 0.2587        | 9.9558  | 2250 | 3.8218          |
| 0.3097        | 10.1770 | 2300 | 3.3976          |
| 0.1278        | 10.3982 | 2350 | 3.8840          |
| 0.2826        | 10.6195 | 2400 | 4.1218          |
| 0.3355        | 10.8407 | 2450 | 4.1840          |
| 0.0822        | 11.0619 | 2500 | 4.3269          |
| 0.0617        | 11.2832 | 2550 | 4.2505          |
| 0.2015        | 11.5044 | 2600 | 4.3315          |
| 0.1249        | 11.7257 | 2650 | 4.3413          |
| 0.118         | 11.9469 | 2700 | 4.4579          |
| 0.1772        | 12.1681 | 2750 | 4.2534          |
| 0.0556        | 12.3894 | 2800 | 4.4677          |
| 0.1161        | 12.6106 | 2850 | 4.3609          |
| 0.13          | 12.8319 | 2900 | 4.2524          |
| 0.1565        | 13.0531 | 2950 | 4.1582          |
| 0.1165        | 13.2743 | 3000 | 4.5896          |
| 0.0341        | 13.4956 | 3050 | 4.7110          |
| 0.0532        | 13.7168 | 3100 | 4.6562          |
| 0.1283        | 13.9381 | 3150 | 4.8117          |
| 0.0744        | 14.1593 | 3200 | 4.6408          |
| 0.0289        | 14.3805 | 3250 | 4.8391          |
| 0.0293        | 14.6018 | 3300 | 4.9042          |
| 0.1226        | 14.8230 | 3350 | 4.8181          |
| 0.0453        | 15.0442 | 3400 | 4.8071          |
| 0.0229        | 15.2655 | 3450 | 4.8802          |
| 0.0077        | 15.4867 | 3500 | 4.8759          |
| 0.0439        | 15.7080 | 3550 | 4.9694          |
| 0.0754        | 15.9292 | 3600 | 4.9196          |
| 0.0608        | 16.1504 | 3650 | 4.7920          |
| 0.0292        | 16.3717 | 3700 | 4.9271          |
| 0.0059        | 16.5929 | 3750 | 4.9988          |
| 0.0286        | 16.8142 | 3800 | 4.9258          |
| 0.0047        | 17.0354 | 3850 | 4.9470          |
| 0.0231        | 17.2566 | 3900 | 4.9583          |
| 0.0254        | 17.4779 | 3950 | 4.9438          |
| 0.023         | 17.6991 | 4000 | 4.9529          |
| 0.016         | 17.9204 | 4050 | 5.0210          |
| 0.0039        | 18.1416 | 4100 | 5.0263          |
| 0.0039        | 18.3628 | 4150 | 5.0436          |
| 0.0103        | 18.5841 | 4200 | 5.0655          |
| 0.0084        | 18.8053 | 4250 | 5.0971          |
| 0.0681        | 19.0265 | 4300 | 5.0795          |
| 0.0157        | 19.2478 | 4350 | 5.0929          |
| 0.0039        | 19.4690 | 4400 | 5.1009          |
| 0.0089        | 19.6903 | 4450 | 5.1096          |
| 0.0086        | 19.9115 | 4500 | 5.1124          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1