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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_on_1200 |
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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_on_1200 |
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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: 4.6669 |
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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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| 5.26 | 0.2212 | 50 | 4.5357 | |
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| 4.3552 | 0.4425 | 100 | 4.0284 | |
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| 4.0237 | 0.6637 | 150 | 3.7961 | |
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| 3.7428 | 0.8850 | 200 | 3.5727 | |
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| 3.6213 | 1.1062 | 250 | 3.7866 | |
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| 3.2334 | 1.3274 | 300 | 3.1121 | |
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| 3.0382 | 1.5487 | 350 | 2.9537 | |
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| 2.8353 | 1.7699 | 400 | 2.8318 | |
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| 2.4759 | 1.9912 | 450 | 2.6736 | |
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| 1.9881 | 2.2124 | 500 | 3.0365 | |
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| 1.9279 | 2.4336 | 550 | 2.4144 | |
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| 1.9336 | 2.6549 | 600 | 2.1754 | |
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| 1.772 | 2.8761 | 650 | 2.1086 | |
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| 1.5504 | 3.0973 | 700 | 2.7056 | |
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| 1.4621 | 3.3186 | 750 | 2.8930 | |
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| 1.4227 | 3.5398 | 800 | 2.4620 | |
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| 1.3924 | 3.7611 | 850 | 2.1275 | |
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| 1.3063 | 3.9823 | 900 | 2.2443 | |
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| 1.0697 | 4.2035 | 950 | 2.6747 | |
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| 0.9476 | 4.4248 | 1000 | 2.7229 | |
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| 1.0868 | 4.6460 | 1050 | 2.9257 | |
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| 0.8726 | 4.8673 | 1100 | 2.7007 | |
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| 0.9436 | 5.0885 | 1150 | 2.8765 | |
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| 0.7219 | 5.3097 | 1200 | 2.5301 | |
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| 0.6919 | 5.5310 | 1250 | 2.9763 | |
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| 0.491 | 5.7522 | 1300 | 3.1198 | |
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| 0.5382 | 5.9735 | 1350 | 3.0883 | |
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| 0.462 | 6.1947 | 1400 | 3.2955 | |
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| 0.6533 | 6.4159 | 1450 | 3.3370 | |
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| 0.6477 | 6.6372 | 1500 | 3.3794 | |
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| 0.4849 | 6.8584 | 1550 | 3.3798 | |
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| 0.4881 | 7.0796 | 1600 | 3.2085 | |
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| 0.3952 | 7.3009 | 1650 | 3.2885 | |
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| 0.161 | 7.5221 | 1700 | 3.6201 | |
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| 0.6895 | 7.7434 | 1750 | 3.4253 | |
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| 0.4638 | 7.9646 | 1800 | 3.4787 | |
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| 0.2186 | 8.1858 | 1850 | 3.7668 | |
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| 0.2531 | 8.4071 | 1900 | 3.7723 | |
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| 0.3971 | 8.6283 | 1950 | 3.7131 | |
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| 0.5665 | 8.8496 | 2000 | 3.5627 | |
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| 0.3377 | 9.0708 | 2050 | 3.1885 | |
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| 0.208 | 9.2920 | 2100 | 3.3734 | |
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| 0.1775 | 9.5133 | 2150 | 4.0609 | |
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| 0.3295 | 9.7345 | 2200 | 3.7039 | |
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| 0.2627 | 9.9558 | 2250 | 3.6028 | |
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| 0.1988 | 10.1770 | 2300 | 3.6288 | |
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| 0.1772 | 10.3982 | 2350 | 3.5394 | |
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| 0.0719 | 10.6195 | 2400 | 4.2068 | |
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| 0.1629 | 10.8407 | 2450 | 4.2701 | |
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| 0.1921 | 11.0619 | 2500 | 4.0440 | |
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| 0.164 | 11.2832 | 2550 | 3.9099 | |
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| 0.1281 | 11.5044 | 2600 | 3.7753 | |
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| 0.0586 | 11.7257 | 2650 | 3.9491 | |
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| 0.1436 | 11.9469 | 2700 | 4.2734 | |
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| 0.0405 | 12.1681 | 2750 | 4.4347 | |
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| 0.0664 | 12.3894 | 2800 | 4.2338 | |
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| 0.0864 | 12.6106 | 2850 | 3.8694 | |
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| 0.103 | 12.8319 | 2900 | 3.9883 | |
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| 0.0456 | 13.0531 | 2950 | 4.5064 | |
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| 0.05 | 13.2743 | 3000 | 4.1434 | |
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| 0.0436 | 13.4956 | 3050 | 4.3928 | |
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| 0.0798 | 13.7168 | 3100 | 4.5576 | |
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| 0.0919 | 13.9381 | 3150 | 4.4114 | |
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| 0.0988 | 14.1593 | 3200 | 4.4998 | |
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| 0.0332 | 14.3805 | 3250 | 4.3948 | |
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| 0.0326 | 14.6018 | 3300 | 4.3823 | |
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| 0.0434 | 14.8230 | 3350 | 4.2468 | |
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| 0.0926 | 15.0442 | 3400 | 4.3909 | |
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| 0.027 | 15.2655 | 3450 | 4.5539 | |
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| 0.047 | 15.4867 | 3500 | 4.5799 | |
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| 0.0189 | 15.7080 | 3550 | 4.3943 | |
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| 0.0096 | 15.9292 | 3600 | 4.4218 | |
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| 0.0467 | 16.1504 | 3650 | 4.6181 | |
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| 0.0144 | 16.3717 | 3700 | 4.5609 | |
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| 0.0339 | 16.5929 | 3750 | 4.5994 | |
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| 0.074 | 16.8142 | 3800 | 4.5598 | |
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| 0.018 | 17.0354 | 3850 | 4.5528 | |
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| 0.0043 | 17.2566 | 3900 | 4.6133 | |
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| 0.0179 | 17.4779 | 3950 | 4.5414 | |
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| 0.039 | 17.6991 | 4000 | 4.4690 | |
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| 0.0134 | 17.9204 | 4050 | 4.4789 | |
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| 0.0094 | 18.1416 | 4100 | 4.5317 | |
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| 0.004 | 18.3628 | 4150 | 4.5711 | |
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| 0.0064 | 18.5841 | 4200 | 4.6237 | |
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| 0.0505 | 18.8053 | 4250 | 4.6148 | |
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| 0.0312 | 19.0265 | 4300 | 4.6302 | |
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| 0.0127 | 19.2478 | 4350 | 4.6577 | |
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| 0.0169 | 19.4690 | 4400 | 4.6685 | |
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| 0.0192 | 19.6903 | 4450 | 4.6626 | |
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| 0.0232 | 19.9115 | 4500 | 4.6669 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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