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: 5.5645

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
5.3224 0.2212 50 4.5586
4.5246 0.4425 100 4.1173
4.1619 0.6637 150 3.8601
3.7534 0.8850 200 3.6319
3.6105 1.1062 250 3.7778
3.3319 1.3274 300 3.1775
3.0645 1.5487 350 2.8592
2.8209 1.7699 400 2.7744
2.7174 1.9912 450 2.7408
2.0437 2.2124 500 2.7848
2.0063 2.4336 550 2.9319
1.9314 2.6549 600 2.3084
1.7939 2.8761 650 2.4124
1.7613 3.0973 700 2.5776
1.3099 3.3186 750 2.2375
1.4457 3.5398 800 2.7229
1.4964 3.7611 850 2.5109
1.428 3.9823 900 2.4552
0.9892 4.2035 950 3.2111
1.0568 4.4248 1000 2.3875
0.8754 4.6460 1050 2.8059
0.8201 4.8673 1100 2.5949
1.0239 5.0885 1150 2.8688
0.7348 5.3097 1200 2.8210
0.7866 5.5310 1250 2.4231
0.5954 5.7522 1300 2.8619
0.7299 5.9735 1350 2.8536
0.5132 6.1947 1400 2.6224
0.7035 6.4159 1450 3.2108
0.5626 6.6372 1500 2.8695
0.431 6.8584 1550 3.3508
0.4354 7.0796 1600 3.4196
0.3896 7.3009 1650 3.1219
0.4899 7.5221 1700 3.0649
0.5703 7.7434 1750 3.0621
0.435 7.9646 1800 3.3686
0.3251 8.1858 1850 3.2093
0.2464 8.4071 1900 3.9491
0.4524 8.6283 1950 3.4324
0.5715 8.8496 2000 3.5811
0.3552 9.0708 2050 3.9434
0.1147 9.2920 2100 4.5776
0.2613 9.5133 2150 4.0439
0.5679 9.7345 2200 3.4187
0.3372 9.9558 2250 3.3868
0.3143 10.1770 2300 4.2051
0.1989 10.3982 2350 3.7925
0.1859 10.6195 2400 4.1932
0.3882 10.8407 2450 4.1672
0.1824 11.0619 2500 4.3516
0.106 11.2832 2550 4.5112
0.2096 11.5044 2600 4.3784
0.1035 11.7257 2650 4.3866
0.2113 11.9469 2700 4.1279
0.2263 12.1681 2750 4.2749
0.1014 12.3894 2800 4.5176
0.1555 12.6106 2850 3.9479
0.1732 12.8319 2900 4.2414
0.1484 13.0531 2950 4.0296
0.1051 13.2743 3000 4.5086
0.1282 13.4956 3050 4.6194
0.1471 13.7168 3100 4.6707
0.1888 13.9381 3150 4.3906
0.0723 14.1593 3200 4.9790
0.0302 14.3805 3250 5.0363
0.1599 14.6018 3300 4.8371
0.1179 14.8230 3350 4.3327
0.1128 15.0442 3400 5.0618
0.0493 15.2655 3450 5.2469
0.0341 15.4867 3500 5.3640
0.0545 15.7080 3550 5.0736
0.0883 15.9292 3600 5.1372
0.0461 16.1504 3650 5.0354
0.0244 16.3717 3700 5.4353
0.0541 16.5929 3750 5.3114
0.0164 16.8142 3800 5.4107
0.0336 17.0354 3850 5.4258
0.0483 17.2566 3900 5.3555
0.0994 17.4779 3950 5.2090
0.0351 17.6991 4000 5.3768
0.0065 17.9204 4050 5.5076
0.0053 18.1416 4100 5.4823
0.0043 18.3628 4150 5.4850
0.0452 18.5841 4200 5.4849
0.0086 18.8053 4250 5.5881
0.0322 19.0265 4300 5.5167
0.0135 19.2478 4350 5.5502
0.0229 19.4690 4400 5.5385
0.042 19.6903 4450 5.5602
0.0404 19.9115 4500 5.5645

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.5.0+cu121
  • Datasets 3.1.0
  • Tokenizers 0.19.1
Downloads last month
16
Safetensors
Model size
200M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for gozdenergiz/layoutlmv2-base-uncased_finetuned_docvqa

Finetuned
(67)
this model