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TestDocumentQuestionAnswering

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PyTorch
layoutlmv2
Generated from Trainer
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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: 5.3353

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
0.153 0.22 50 5.3909
0.2793 0.44 100 5.0150
0.2634 0.66 150 4.6620
0.5192 0.88 200 4.7826
0.3096 1.11 250 4.9532
0.2638 1.33 300 5.2584
0.4727 1.55 350 4.0943
0.2763 1.77 400 4.8408
1.0425 1.99 450 5.0344
0.4477 2.21 500 4.9084
0.3266 2.43 550 5.0996
0.3085 2.65 600 4.4858
0.4648 2.88 650 4.0630
0.1845 3.1 700 5.3969
0.1616 3.32 750 4.8225
0.1752 3.54 800 5.2945
0.1877 3.76 850 5.2358
0.3172 3.98 900 5.2205
0.1627 4.2 950 4.9991
0.2548 4.42 1000 4.6917
0.1566 4.65 1050 5.1266
0.2616 4.87 1100 4.3241
0.1199 5.09 1150 4.9821
0.1372 5.31 1200 5.0838
0.1198 5.53 1250 5.0156
0.0558 5.75 1300 4.8638
0.1331 5.97 1350 4.9492
0.0689 6.19 1400 4.6926
0.0912 6.42 1450 4.5153
0.0495 6.64 1500 4.6969
0.0853 6.86 1550 4.7690
0.1072 7.08 1600 4.6783
0.034 7.3 1650 4.7351
0.2999 7.52 1700 4.5185
0.0763 7.74 1750 4.5825
0.0799 7.96 1800 4.7218
0.0343 8.19 1850 5.1508
0.0396 8.41 1900 5.4893
0.033 8.63 1950 5.5167
0.0295 8.85 2000 5.6252
0.2303 9.07 2050 4.7031
0.088 9.29 2100 4.7323
0.0666 9.51 2150 4.8688
0.0597 9.73 2200 5.6007
0.0615 9.96 2250 5.5403
0.1003 10.18 2300 5.3198
0.0457 10.4 2350 5.4828
0.0391 10.62 2400 5.5312
0.0325 10.84 2450 5.7410
0.0147 11.06 2500 5.8749
0.1013 11.28 2550 5.6522
0.001 11.5 2600 5.7776
0.0002 11.73 2650 5.8431
0.03 11.95 2700 5.9751
0.0452 12.17 2750 5.6928
0.0002 12.39 2800 5.6264
0.0109 12.61 2850 5.2688
0.0801 12.83 2900 5.2780
0.0216 13.05 2950 5.3691
0.0002 13.27 3000 5.5237
0.0092 13.5 3050 5.3662
0.0124 13.72 3100 5.4474
0.0515 13.94 3150 5.3623
0.0032 14.16 3200 5.4168
0.0051 14.38 3250 5.2897
0.0002 14.6 3300 5.3205
0.014 14.82 3350 5.2114
0.0004 15.04 3400 5.2342
0.0104 15.27 3450 5.2562
0.0107 15.49 3500 5.1112
0.0002 15.71 3550 5.1515
0.0002 15.93 3600 5.2054
0.0002 16.15 3650 5.1968
0.0003 16.37 3700 5.3196
0.0246 16.59 3750 5.3111
0.0054 16.81 3800 5.3335
0.0001 17.04 3850 5.3488
0.0243 17.26 3900 5.2597
0.0217 17.48 3950 5.2834
0.0002 17.7 4000 5.2947
0.0002 17.92 4050 5.3131
0.0001 18.14 4100 5.3240
0.0016 18.36 4150 5.3129
0.0133 18.58 4200 5.3241
0.0002 18.81 4250 5.3382
0.0159 19.03 4300 5.3764
0.003 19.25 4350 5.3776
0.0516 19.47 4400 5.3389
0.016 19.69 4450 5.3275
0.0105 19.91 4500 5.3353

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cpu
  • Datasets 2.14.5
  • Tokenizers 0.13.3