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metadata
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: []

layoutlmv2-base-uncased_finetuned_docvqa

This model is a fine-tuned version of microsoft/layoutlmv2-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 3.8273

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: 8
  • 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
2.0156 0.44 50 2.4679
1.8368 0.88 100 2.2079
1.5567 1.33 150 2.3312
1.3487 1.77 200 2.8410
1.2254 2.21 250 2.6996
1.1201 2.65 300 2.2915
0.8816 3.1 350 2.3419
0.7885 3.54 400 2.6410
0.7532 3.98 450 2.7539
0.5822 4.42 500 2.7213
0.5801 4.87 550 2.7429
0.5043 5.31 600 2.8523
0.4545 5.75 650 2.8666
0.4029 6.19 700 3.4559
0.3568 6.64 750 3.1760
0.3962 7.08 800 3.0625
0.2381 7.52 850 3.3868
0.2492 7.96 900 3.7453
0.3813 8.41 950 3.2516
0.2477 8.85 1000 3.4677
0.1834 9.29 1050 3.2748
0.2067 9.73 1100 3.7590
0.2062 10.18 1150 3.5956
0.1337 10.62 1200 3.8232
0.1785 11.06 1250 3.5264
0.0906 11.5 1300 3.6157
0.1649 11.95 1350 3.4667
0.1306 12.39 1400 3.7029
0.0529 12.83 1450 3.6307
0.0628 13.27 1500 3.5905
0.1015 13.72 1550 3.4659
0.0693 14.16 1600 3.7713
0.1111 14.6 1650 3.7680
0.0414 15.04 1700 3.8956
0.0256 15.49 1750 3.9021
0.0737 15.93 1800 3.9392
0.0577 16.37 1850 3.8129
0.0744 16.81 1900 3.8356
0.0698 17.26 1950 3.8406
0.0173 17.7 2000 3.8611
0.0667 18.14 2050 3.7995
0.0482 18.58 2100 3.8132
0.0458 19.03 2150 3.8335
0.0415 19.47 2200 3.8475
0.0236 19.91 2250 3.8273

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1