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layoutlmv2-base-uncased_finetuned_docvqa

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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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+
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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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+
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+ # layoutlmv2-base-uncased_finetuned_docvqa
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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