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# layoutlmv2-base-uncased_finetuned_docvqa

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.6973

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 5.3322        | 0.22  | 50   | 4.6214          |
| 4.4006        | 0.44  | 100  | 4.1705          |
| 3.9967        | 0.66  | 150  | 3.8115          |
| 3.8349        | 0.88  | 200  | 3.5599          |
| 3.4185        | 1.11  | 250  | 3.2811          |
| 3.1129        | 1.33  | 300  | 3.3014          |
| 2.9186        | 1.55  | 350  | 3.2583          |
| 2.8937        | 1.77  | 400  | 2.6806          |
| 2.5872        | 1.99  | 450  | 2.4617          |
| 1.934         | 2.21  | 500  | 2.4098          |
| 1.9086        | 2.43  | 550  | 2.3926          |
| 1.7456        | 2.65  | 600  | 2.4048          |
| 1.6092        | 2.88  | 650  | 2.2064          |
| 1.5114        | 3.1   | 700  | 2.3882          |
| 1.3176        | 3.32  | 750  | 2.2211          |
| 1.2236        | 3.54  | 800  | 3.5792          |
| 1.4123        | 3.76  | 850  | 2.0391          |
| 1.2434        | 3.98  | 900  | 2.3563          |
| 0.8727        | 4.2   | 950  | 2.6344          |
| 0.9026        | 4.42  | 1000 | 3.1071          |
| 1.0698        | 4.65  | 1050 | 3.1795          |
| 0.9226        | 4.87  | 1100 | 3.0897          |
| 1.0639        | 5.09  | 1150 | 3.2822          |
| 0.7568        | 5.31  | 1200 | 3.0442          |
| 0.8192        | 5.53  | 1250 | 2.8516          |
| 0.5137        | 5.75  | 1300 | 3.1520          |
| 0.7053        | 5.97  | 1350 | 2.7512          |
| 0.4587        | 6.19  | 1400 | 2.8772          |
| 0.4965        | 6.42  | 1450 | 3.1186          |
| 0.4079        | 6.64  | 1500 | 3.0887          |
| 0.6135        | 6.86  | 1550 | 3.0537          |
| 0.7518        | 7.08  | 1600 | 3.2562          |
| 0.336         | 7.3   | 1650 | 3.3709          |
| 0.618         | 7.52  | 1700 | 2.5948          |
| 0.3473        | 7.74  | 1750 | 3.1784          |
| 0.3811        | 7.96  | 1800 | 3.3420          |
| 0.2749        | 8.19  | 1850 | 3.5958          |
| 0.2916        | 8.41  | 1900 | 3.7811          |
| 0.2634        | 8.63  | 1950 | 3.8935          |
| 0.4594        | 8.85  | 2000 | 3.4889          |
| 0.2957        | 9.07  | 2050 | 3.5717          |
| 0.1503        | 9.29  | 2100 | 3.8861          |
| 0.2986        | 9.51  | 2150 | 3.8007          |
| 0.3732        | 9.73  | 2200 | 3.5632          |
| 0.282         | 9.96  | 2250 | 3.1815          |
| 0.1781        | 10.18 | 2300 | 3.8386          |
| 0.1678        | 10.4  | 2350 | 3.9624          |
| 0.1813        | 10.62 | 2400 | 4.1113          |
| 0.3601        | 10.84 | 2450 | 3.9760          |
| 0.2374        | 11.06 | 2500 | 3.8321          |
| 0.1251        | 11.28 | 2550 | 4.0945          |
| 0.0741        | 11.5  | 2600 | 4.1810          |
| 0.2846        | 11.73 | 2650 | 3.9240          |
| 0.1964        | 11.95 | 2700 | 3.7833          |
| 0.1413        | 12.17 | 2750 | 3.9830          |
| 0.0696        | 12.39 | 2800 | 4.4270          |
| 0.1401        | 12.61 | 2850 | 4.6113          |
| 0.1267        | 12.83 | 2900 | 4.3713          |
| 0.0689        | 13.05 | 2950 | 4.4582          |
| 0.1636        | 13.27 | 3000 | 4.6710          |
| 0.1935        | 13.5  | 3050 | 4.2833          |
| 0.0936        | 13.72 | 3100 | 4.5357          |
| 0.1001        | 13.94 | 3150 | 4.2660          |
| 0.0509        | 14.16 | 3200 | 4.3863          |
| 0.0193        | 14.38 | 3250 | 4.5554          |
| 0.031         | 14.6  | 3300 | 4.4455          |
| 0.0163        | 14.82 | 3350 | 4.4985          |
| 0.1558        | 15.04 | 3400 | 4.5935          |
| 0.0707        | 15.27 | 3450 | 4.4791          |
| 0.0089        | 15.49 | 3500 | 4.6358          |
| 0.0881        | 15.71 | 3550 | 4.5644          |
| 0.1348        | 15.93 | 3600 | 4.5336          |
| 0.0176        | 16.15 | 3650 | 4.5465          |
| 0.0679        | 16.37 | 3700 | 4.4872          |
| 0.0138        | 16.59 | 3750 | 4.3819          |
| 0.0211        | 16.81 | 3800 | 4.5024          |
| 0.0506        | 17.04 | 3850 | 4.4761          |
| 0.0051        | 17.26 | 3900 | 4.5898          |
| 0.075         | 17.48 | 3950 | 4.5427          |
| 0.0089        | 17.7  | 4000 | 4.6244          |
| 0.0298        | 17.92 | 4050 | 4.6440          |
| 0.0034        | 18.14 | 4100 | 4.6486          |
| 0.0594        | 18.36 | 4150 | 4.6438          |
| 0.0179        | 18.58 | 4200 | 4.6552          |
| 0.0081        | 18.81 | 4250 | 4.6508          |
| 0.0046        | 19.03 | 4300 | 4.6808          |
| 0.0618        | 19.25 | 4350 | 4.6856          |
| 0.0033        | 19.47 | 4400 | 4.6763          |
| 0.0062        | 19.69 | 4450 | 4.6892          |
| 0.0404        | 19.91 | 4500 | 4.6973          |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.10.0+cu113
- Datasets 2.13.2
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "model-index": [{"name": "layoutlmv2-base-uncased_finetuned_docvqa", "results": []}]}
transformers pytorch tensorboard layoutlmv2 document-question-answering generated_from_trainer endpoints_compatible region:us