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--- |
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library_name: transformers |
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license: cc-by-nc-sa-4.0 |
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base_model: microsoft/layoutlmv2-base-uncased |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: layoutlmv2-base-uncased_finetuned_docvqa |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# layoutlmv2-base-uncased_finetuned_docvqa |
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This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.5637 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-------:|:----:|:---------------:| |
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| 5.2825 | 0.2212 | 50 | 4.5028 | |
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| 4.4224 | 0.4425 | 100 | 4.0697 | |
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| 4.1296 | 0.6637 | 150 | 3.9535 | |
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| 3.8325 | 0.8850 | 200 | 3.5453 | |
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| 3.4315 | 1.1062 | 250 | 3.8942 | |
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| 3.2797 | 1.3274 | 300 | 3.2322 | |
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| 3.0041 | 1.5487 | 350 | 2.9298 | |
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| 2.7424 | 1.7699 | 400 | 2.6607 | |
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| 2.3969 | 1.9912 | 450 | 2.6309 | |
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| 2.0661 | 2.2124 | 500 | 2.7708 | |
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| 1.9442 | 2.4336 | 550 | 2.6028 | |
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| 1.8616 | 2.6549 | 600 | 2.2959 | |
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| 1.9612 | 2.8761 | 650 | 2.1755 | |
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| 1.5795 | 3.0973 | 700 | 2.3348 | |
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| 1.3558 | 3.3186 | 750 | 2.3090 | |
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| 1.4052 | 3.5398 | 800 | 2.5506 | |
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| 1.4666 | 3.7611 | 850 | 2.4862 | |
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| 1.3408 | 3.9823 | 900 | 2.4843 | |
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| 1.1343 | 4.2035 | 950 | 2.5429 | |
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| 1.0681 | 4.4248 | 1000 | 2.6741 | |
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| 1.2315 | 4.6460 | 1050 | 3.5725 | |
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| 1.3005 | 4.8673 | 1100 | 2.5506 | |
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| 0.9839 | 5.0885 | 1150 | 2.5715 | |
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| 0.8055 | 5.3097 | 1200 | 3.1745 | |
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| 1.0878 | 5.5310 | 1250 | 3.6689 | |
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| 0.7227 | 5.7522 | 1300 | 3.4183 | |
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| 0.7872 | 5.9735 | 1350 | 2.9087 | |
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| 0.5348 | 6.1947 | 1400 | 2.9912 | |
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| 0.8189 | 6.4159 | 1450 | 2.7346 | |
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| 0.5305 | 6.6372 | 1500 | 2.8126 | |
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| 0.5597 | 6.8584 | 1550 | 3.2278 | |
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| 0.7229 | 7.0796 | 1600 | 2.8248 | |
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| 0.4531 | 7.3009 | 1650 | 3.2564 | |
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| 0.5035 | 7.5221 | 1700 | 3.0984 | |
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| 0.4971 | 7.7434 | 1750 | 3.0667 | |
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| 0.5544 | 7.9646 | 1800 | 2.8519 | |
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| 0.2919 | 8.1858 | 1850 | 3.9333 | |
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| 0.405 | 8.4071 | 1900 | 3.5871 | |
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| 0.3391 | 8.6283 | 1950 | 3.5935 | |
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| 0.5292 | 8.8496 | 2000 | 3.4899 | |
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| 0.471 | 9.0708 | 2050 | 3.5509 | |
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| 0.2564 | 9.2920 | 2100 | 3.9214 | |
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| 0.4863 | 9.5133 | 2150 | 3.6614 | |
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| 0.315 | 9.7345 | 2200 | 3.9714 | |
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| 0.4728 | 9.9558 | 2250 | 3.5600 | |
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| 0.2982 | 10.1770 | 2300 | 3.6403 | |
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| 0.1714 | 10.3982 | 2350 | 3.6444 | |
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| 0.205 | 10.6195 | 2400 | 4.3221 | |
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| 0.3756 | 10.8407 | 2450 | 4.0914 | |
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| 0.1874 | 11.0619 | 2500 | 3.8238 | |
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| 0.0965 | 11.2832 | 2550 | 4.0389 | |
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| 0.2563 | 11.5044 | 2600 | 4.1470 | |
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| 0.2176 | 11.7257 | 2650 | 3.8725 | |
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| 0.147 | 11.9469 | 2700 | 4.0304 | |
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| 0.2113 | 12.1681 | 2750 | 3.7899 | |
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| 0.1281 | 12.3894 | 2800 | 4.1518 | |
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| 0.1377 | 12.6106 | 2850 | 4.1490 | |
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| 0.2311 | 12.8319 | 2900 | 4.0664 | |
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| 0.2286 | 13.0531 | 2950 | 3.8024 | |
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| 0.1179 | 13.2743 | 3000 | 3.9863 | |
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| 0.1248 | 13.4956 | 3050 | 3.9647 | |
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| 0.1693 | 13.7168 | 3100 | 3.6965 | |
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| 0.0876 | 13.9381 | 3150 | 4.1747 | |
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| 0.12 | 14.1593 | 3200 | 4.2850 | |
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| 0.0899 | 14.3805 | 3250 | 4.2602 | |
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| 0.1521 | 14.6018 | 3300 | 4.0035 | |
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| 0.1186 | 14.8230 | 3350 | 4.0200 | |
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| 0.0194 | 15.0442 | 3400 | 4.2270 | |
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| 0.0629 | 15.2655 | 3450 | 4.3293 | |
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| 0.0155 | 15.4867 | 3500 | 4.2434 | |
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| 0.1116 | 15.7080 | 3550 | 4.2031 | |
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| 0.0691 | 15.9292 | 3600 | 4.4198 | |
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| 0.0235 | 16.1504 | 3650 | 4.4143 | |
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| 0.0857 | 16.3717 | 3700 | 4.2814 | |
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| 0.0114 | 16.5929 | 3750 | 4.2801 | |
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| 0.0176 | 16.8142 | 3800 | 4.4927 | |
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| 0.0978 | 17.0354 | 3850 | 4.5054 | |
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| 0.0122 | 17.2566 | 3900 | 4.5038 | |
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| 0.009 | 17.4779 | 3950 | 4.5913 | |
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| 0.0476 | 17.6991 | 4000 | 4.6732 | |
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| 0.0985 | 17.9204 | 4050 | 4.5039 | |
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| 0.0051 | 18.1416 | 4100 | 4.5284 | |
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| 0.0696 | 18.3628 | 4150 | 4.5731 | |
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| 0.0238 | 18.5841 | 4200 | 4.5257 | |
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| 0.0068 | 18.8053 | 4250 | 4.5459 | |
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| 0.0276 | 19.0265 | 4300 | 4.5551 | |
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| 0.0296 | 19.2478 | 4350 | 4.5593 | |
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| 0.0068 | 19.4690 | 4400 | 4.5723 | |
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| 0.1252 | 19.6903 | 4450 | 4.5622 | |
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| 0.0051 | 19.9115 | 4500 | 4.5637 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.5.0+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.19.1 |
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