layout2_large / README.md
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metadata
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv2-large-uncased
tags:
  - generated_from_trainer
model-index:
  - name: layout2_large
    results: []

layout2_large

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

  • Loss: 5.2238

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
3.6695 0.22 50 2.4612
2.3221 0.44 100 1.9209
2.1651 0.66 150 1.7838
1.7644 0.88 200 1.9484
1.8272 1.11 250 1.7739
1.2938 1.33 300 1.7310
1.477 1.55 350 1.7254
1.4623 1.77 400 1.4813
1.2976 1.99 450 1.8113
0.8746 2.21 500 2.0039
0.8223 2.43 550 2.5449
1.0367 2.65 600 2.3888
1.0897 2.88 650 1.8641
0.6269 3.1 700 3.3845
0.7064 3.32 750 3.5282
0.8204 3.54 800 2.2839
0.9558 3.76 850 3.1004
0.8255 3.98 900 2.5468
0.778 4.2 950 4.6735
0.8192 4.42 1000 3.7428
0.798 4.65 1050 3.7837
0.5329 4.87 1100 3.2764
0.7568 5.09 1150 3.5623
0.5929 5.31 1200 3.1992
0.4427 5.53 1250 4.6837
0.7004 5.75 1300 2.6854
0.4315 5.97 1350 3.0840
0.2394 6.19 1400 4.3777
0.4605 6.42 1450 4.0313
0.4959 6.64 1500 3.3943
0.618 6.86 1550 3.4803
0.254 7.08 1600 4.0659
0.2255 7.3 1650 3.5000
0.3048 7.52 1700 4.0518
0.5369 7.74 1750 3.9500
0.3641 7.96 1800 3.7982
0.1725 8.19 1850 3.8756
0.3369 8.41 1900 4.1205
0.3522 8.63 1950 4.3853
0.4681 8.85 2000 3.2152
0.0857 9.07 2050 4.1299
0.36 9.29 2100 3.5658
0.3325 9.51 2150 3.8848
0.1645 9.73 2200 3.8714
0.2046 9.96 2250 3.9900
0.1267 10.18 2300 4.6510
0.2284 10.4 2350 4.1686
0.173 10.62 2400 4.0575
0.219 10.84 2450 4.2034
0.1107 11.06 2500 4.5646
0.0916 11.28 2550 4.9722
0.1358 11.5 2600 5.0297
0.0681 11.73 2650 5.2933
0.0447 11.95 2700 5.4102
0.0655 12.17 2750 5.8173
0.0694 12.39 2800 6.3645
0.1717 12.61 2850 5.4551
0.0197 12.83 2900 5.3129
0.0319 13.05 2950 5.2423
0.0 13.27 3000 5.3664
0.124 13.5 3050 5.2445
0.0025 13.72 3100 5.5092
0.1243 13.94 3150 5.3060
0.071 14.16 3200 5.3991
0.0301 14.38 3250 5.2129
0.0059 14.6 3300 5.3309
0.1027 14.82 3350 4.6790
0.0001 15.04 3400 5.4300
0.0 15.27 3450 5.4420
0.0046 15.49 3500 5.7107
0.0488 15.71 3550 5.3521
0.0797 15.93 3600 4.9206
0.06 16.15 3650 4.6152
0.0295 16.37 3700 4.6441
0.0126 16.59 3750 4.8442
0.0 16.81 3800 4.8838
0.0004 17.04 3850 5.0888
0.0 17.26 3900 5.1360
0.0003 17.48 3950 5.4019
0.0583 17.7 4000 5.0542
0.0 17.92 4050 4.9908
0.0001 18.14 4100 5.1099
0.0194 18.36 4150 5.1146
0.0002 18.58 4200 5.2076
0.0 18.81 4250 5.3454
0.0249 19.03 4300 5.3082
0.0329 19.25 4350 5.2274
0.0 19.47 4400 5.2129
0.0 19.69 4450 5.2155
0.0009 19.91 4500 5.2238

Framework versions

  • Transformers 4.32.0
  • Pytorch 2.0.0+cu118
  • Datasets 2.17.1
  • Tokenizers 0.13.2