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layoutlmv2-base-uncased_finetuned_docvqa

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layoutlmv2
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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: 4.6448
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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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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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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+ | 5.2021 | 0.2212 | 50 | 4.6324 |
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+ | 4.5313 | 0.4425 | 100 | 4.1367 |
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+ | 4.1524 | 0.6637 | 150 | 3.8836 |
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+ | 3.9207 | 0.8850 | 200 | 3.6920 |
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+ | 3.5517 | 1.1062 | 250 | 3.8563 |
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+ | 3.295 | 1.3274 | 300 | 3.2045 |
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+ | 3.0938 | 1.5487 | 350 | 3.1921 |
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+ | 2.9264 | 1.7699 | 400 | 2.8674 |
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+ | 2.5353 | 1.9912 | 450 | 2.8867 |
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+ | 2.1442 | 2.2124 | 500 | 2.7470 |
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+ | 1.8984 | 2.4336 | 550 | 2.4924 |
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+ | 1.886 | 2.6549 | 600 | 2.6026 |
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+ | 1.9277 | 2.8761 | 650 | 2.6891 |
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+ | 1.6546 | 3.0973 | 700 | 2.4442 |
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+ | 1.4824 | 3.3186 | 750 | 2.8104 |
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+ | 1.3533 | 3.5398 | 800 | 2.6744 |
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+ | 1.5249 | 3.7611 | 850 | 2.1151 |
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+ | 1.3263 | 3.9823 | 900 | 2.5105 |
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+ | 0.9831 | 4.2035 | 950 | 2.8372 |
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+ | 0.9544 | 4.4248 | 1000 | 2.2467 |
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+ | 1.0167 | 4.6460 | 1050 | 3.0175 |
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+ | 0.9889 | 4.8673 | 1100 | 2.6414 |
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+ | 0.7828 | 5.0885 | 1150 | 2.8631 |
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+ | 0.7675 | 5.3097 | 1200 | 2.8171 |
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+ | 0.7695 | 5.5310 | 1250 | 3.0892 |
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+ | 0.5891 | 5.7522 | 1300 | 3.1601 |
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+ | 0.8397 | 5.9735 | 1350 | 3.0463 |
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+ | 0.6106 | 6.1947 | 1400 | 3.3519 |
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+ | 0.7397 | 6.4159 | 1450 | 3.4455 |
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+ | 0.5613 | 6.6372 | 1500 | 3.1579 |
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+ | 0.5931 | 6.8584 | 1550 | 3.3272 |
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+ | 0.6042 | 7.0796 | 1600 | 3.0458 |
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+ | 0.3754 | 7.3009 | 1650 | 3.3260 |
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+ | 0.349 | 7.5221 | 1700 | 3.3049 |
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+ | 0.5256 | 7.7434 | 1750 | 3.4301 |
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+ | 0.4256 | 7.9646 | 1800 | 3.4376 |
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+ | 0.333 | 8.1858 | 1850 | 3.4952 |
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+ | 0.2256 | 8.4071 | 1900 | 3.7613 |
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+ | 0.3261 | 8.6283 | 1950 | 3.3898 |
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+ | 0.6199 | 8.8496 | 2000 | 3.3443 |
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+ | 0.4307 | 9.0708 | 2050 | 3.1757 |
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+ | 0.1569 | 9.2920 | 2100 | 3.7978 |
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+ | 0.4755 | 9.5133 | 2150 | 3.5794 |
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+ | 0.2493 | 9.7345 | 2200 | 3.5829 |
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+ | 0.2686 | 9.9558 | 2250 | 3.5064 |
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+ | 0.3662 | 10.1770 | 2300 | 3.2991 |
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+ | 0.2353 | 10.3982 | 2350 | 3.4224 |
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+ | 0.0991 | 10.6195 | 2400 | 4.2513 |
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+ | 0.407 | 10.8407 | 2450 | 3.5800 |
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+ | 0.1471 | 11.0619 | 2500 | 3.6337 |
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+ | 0.1352 | 11.2832 | 2550 | 3.9379 |
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+ | 0.2922 | 11.5044 | 2600 | 3.8454 |
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+ | 0.1113 | 11.7257 | 2650 | 4.1881 |
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+ | 0.1325 | 11.9469 | 2700 | 4.0861 |
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+ | 0.1598 | 12.1681 | 2750 | 4.1164 |
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+ | 0.0822 | 12.3894 | 2800 | 4.0703 |
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+ | 0.1181 | 12.6106 | 2850 | 3.9423 |
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+ | 0.2272 | 12.8319 | 2900 | 4.1349 |
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+ | 0.1706 | 13.0531 | 2950 | 4.0460 |
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+ | 0.1051 | 13.2743 | 3000 | 4.1329 |
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+ | 0.0349 | 13.4956 | 3050 | 4.2074 |
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+ | 0.2101 | 13.7168 | 3100 | 4.0685 |
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+ | 0.1001 | 13.9381 | 3150 | 4.3431 |
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+ | 0.1109 | 14.1593 | 3200 | 4.3210 |
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+ | 0.0264 | 14.3805 | 3250 | 4.5687 |
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+ | 0.1321 | 14.6018 | 3300 | 4.4580 |
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+ | 0.0979 | 14.8230 | 3350 | 4.5390 |
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+ | 0.0905 | 15.0442 | 3400 | 4.4641 |
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+ | 0.0706 | 15.2655 | 3450 | 4.5589 |
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+ | 0.0386 | 15.4867 | 3500 | 4.4396 |
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+ | 0.0411 | 15.7080 | 3550 | 4.4250 |
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+ | 0.0349 | 15.9292 | 3600 | 4.5973 |
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+ | 0.1208 | 16.1504 | 3650 | 4.5193 |
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+ | 0.0248 | 16.3717 | 3700 | 4.5689 |
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+ | 0.0175 | 16.5929 | 3750 | 4.6381 |
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+ | 0.0266 | 16.8142 | 3800 | 4.6431 |
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+ | 0.0236 | 17.0354 | 3850 | 4.6552 |
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+ | 0.0075 | 17.2566 | 3900 | 4.6977 |
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+ | 0.0514 | 17.4779 | 3950 | 4.6455 |
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+ | 0.0252 | 17.6991 | 4000 | 4.6360 |
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+ | 0.0507 | 17.9204 | 4050 | 4.6566 |
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+ | 0.0273 | 18.1416 | 4100 | 4.5838 |
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+ | 0.0612 | 18.3628 | 4150 | 4.5459 |
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+ | 0.0168 | 18.5841 | 4200 | 4.5979 |
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+ | 0.0384 | 18.8053 | 4250 | 4.6035 |
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+ | 0.0445 | 19.0265 | 4300 | 4.5904 |
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+ | 0.0403 | 19.2478 | 4350 | 4.6543 |
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+ | 0.0095 | 19.4690 | 4400 | 4.6552 |
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+ | 0.0212 | 19.6903 | 4450 | 4.6426 |
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+ | 0.0037 | 19.9115 | 4500 | 4.6448 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.3
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3