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--- |
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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: 4.6788 |
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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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| 5.3193 | 0.22 | 50 | 4.5453 | |
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| 4.5115 | 0.44 | 100 | 4.1632 | |
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| 4.1316 | 0.66 | 150 | 3.8496 | |
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| 3.7911 | 0.88 | 200 | 3.7418 | |
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| 3.5175 | 1.11 | 250 | 3.9454 | |
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| 3.2171 | 1.33 | 300 | 3.0430 | |
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| 3.0377 | 1.55 | 350 | 3.1317 | |
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| 3.1081 | 1.77 | 400 | 2.8709 | |
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| 2.6219 | 1.99 | 450 | 2.9745 | |
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| 2.2922 | 2.21 | 500 | 3.0184 | |
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| 2.2245 | 2.43 | 550 | 2.6649 | |
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| 2.0918 | 2.65 | 600 | 2.3156 | |
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| 2.0339 | 2.88 | 650 | 2.4970 | |
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| 1.7088 | 3.1 | 700 | 2.2817 | |
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| 1.4584 | 3.32 | 750 | 2.3237 | |
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| 1.4296 | 3.54 | 800 | 2.1868 | |
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| 1.4413 | 3.76 | 850 | 2.2775 | |
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| 1.4055 | 3.98 | 900 | 2.6660 | |
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| 1.0251 | 4.2 | 950 | 2.6155 | |
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| 1.1251 | 4.42 | 1000 | 2.9841 | |
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| 1.059 | 4.65 | 1050 | 2.7376 | |
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| 1.0179 | 4.87 | 1100 | 3.7345 | |
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| 1.1128 | 5.09 | 1150 | 2.6704 | |
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| 0.8461 | 5.31 | 1200 | 3.0422 | |
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| 0.86 | 5.53 | 1250 | 3.2093 | |
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| 0.9124 | 5.75 | 1300 | 3.2782 | |
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| 0.8687 | 5.97 | 1350 | 3.1477 | |
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| 0.7039 | 6.19 | 1400 | 2.6896 | |
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| 0.8908 | 6.42 | 1450 | 3.0843 | |
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| 0.7408 | 6.64 | 1500 | 2.9585 | |
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| 0.6026 | 6.86 | 1550 | 3.3629 | |
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| 0.4852 | 7.08 | 1600 | 3.1505 | |
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| 0.5496 | 7.3 | 1650 | 3.6285 | |
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| 0.5578 | 7.52 | 1700 | 3.3481 | |
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| 0.5897 | 7.74 | 1750 | 3.3201 | |
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| 0.4487 | 7.96 | 1800 | 3.1462 | |
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| 0.2182 | 8.19 | 1850 | 3.7251 | |
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| 0.3524 | 8.41 | 1900 | 3.5870 | |
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| 0.4516 | 8.63 | 1950 | 3.6300 | |
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| 0.5658 | 8.85 | 2000 | 3.1085 | |
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| 0.4877 | 9.07 | 2050 | 3.5353 | |
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| 0.2226 | 9.29 | 2100 | 3.6744 | |
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| 0.2544 | 9.51 | 2150 | 4.1244 | |
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| 0.6194 | 9.73 | 2200 | 3.4775 | |
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| 0.3759 | 9.96 | 2250 | 3.7031 | |
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| 0.2718 | 10.18 | 2300 | 3.6076 | |
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| 0.1322 | 10.4 | 2350 | 3.6885 | |
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| 0.2596 | 10.62 | 2400 | 3.9328 | |
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| 0.1675 | 10.84 | 2450 | 4.1439 | |
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| 0.158 | 11.06 | 2500 | 4.4306 | |
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| 0.1462 | 11.28 | 2550 | 4.3744 | |
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| 0.2187 | 11.5 | 2600 | 4.4111 | |
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| 0.264 | 11.73 | 2650 | 3.9780 | |
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| 0.1997 | 11.95 | 2700 | 4.2383 | |
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| 0.1369 | 12.17 | 2750 | 4.1329 | |
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| 0.1204 | 12.39 | 2800 | 4.2738 | |
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| 0.2001 | 12.61 | 2850 | 4.0106 | |
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| 0.2132 | 12.83 | 2900 | 4.1816 | |
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| 0.1472 | 13.05 | 2950 | 4.4600 | |
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| 0.0603 | 13.27 | 3000 | 4.0050 | |
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| 0.0911 | 13.5 | 3050 | 4.1838 | |
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| 0.1016 | 13.72 | 3100 | 4.4429 | |
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| 0.0887 | 13.94 | 3150 | 4.1510 | |
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| 0.0495 | 14.16 | 3200 | 4.2938 | |
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| 0.0677 | 14.38 | 3250 | 4.6133 | |
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| 0.1263 | 14.6 | 3300 | 4.4634 | |
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| 0.1953 | 14.82 | 3350 | 3.9348 | |
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| 0.0212 | 15.04 | 3400 | 4.1726 | |
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| 0.0082 | 15.27 | 3450 | 4.3512 | |
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| 0.0432 | 15.49 | 3500 | 4.2992 | |
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| 0.0975 | 15.71 | 3550 | 4.2274 | |
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| 0.0933 | 15.93 | 3600 | 4.4028 | |
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| 0.024 | 16.15 | 3650 | 4.4662 | |
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| 0.0964 | 16.37 | 3700 | 4.3964 | |
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| 0.0487 | 16.59 | 3750 | 4.4827 | |
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| 0.0147 | 16.81 | 3800 | 4.5577 | |
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| 0.0951 | 17.04 | 3850 | 4.5640 | |
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| 0.0508 | 17.26 | 3900 | 4.4473 | |
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| 0.1163 | 17.48 | 3950 | 4.4565 | |
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| 0.0151 | 17.7 | 4000 | 4.5511 | |
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| 0.0569 | 17.92 | 4050 | 4.5298 | |
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| 0.0639 | 18.14 | 4100 | 4.5417 | |
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| 0.0155 | 18.36 | 4150 | 4.6398 | |
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| 0.0107 | 18.58 | 4200 | 4.7664 | |
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| 0.0044 | 18.81 | 4250 | 4.8119 | |
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| 0.0906 | 19.03 | 4300 | 4.7168 | |
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| 0.0533 | 19.25 | 4350 | 4.7032 | |
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| 0.0496 | 19.47 | 4400 | 4.6918 | |
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| 0.0938 | 19.69 | 4450 | 4.6824 | |
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| 0.0483 | 19.91 | 4500 | 4.6788 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.2.1 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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