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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: 4.3701 |
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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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| 5.3439 | 0.22 | 50 | 4.6661 | |
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| 4.4287 | 0.44 | 100 | 4.2125 | |
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| 4.0781 | 0.66 | 150 | 3.7145 | |
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| 3.8419 | 0.88 | 200 | 3.5926 | |
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| 3.633 | 1.11 | 250 | 3.4266 | |
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| 3.1492 | 1.33 | 300 | 3.2833 | |
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| 3.2018 | 1.55 | 350 | 3.0237 | |
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| 2.8891 | 1.77 | 400 | 2.9976 | |
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| 2.6695 | 1.99 | 450 | 3.0654 | |
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| 2.211 | 2.21 | 500 | 2.7658 | |
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| 2.2555 | 2.43 | 550 | 2.5009 | |
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| 2.0293 | 2.65 | 600 | 2.3515 | |
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| 1.8663 | 2.88 | 650 | 2.1264 | |
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| 1.6332 | 3.1 | 700 | 2.3934 | |
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| 1.5298 | 3.32 | 750 | 2.6686 | |
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| 1.3594 | 3.54 | 800 | 2.0781 | |
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| 1.3923 | 3.76 | 850 | 2.2174 | |
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| 1.26 | 3.98 | 900 | 2.5728 | |
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| 0.9371 | 4.2 | 950 | 2.7164 | |
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| 0.9891 | 4.42 | 1000 | 2.8637 | |
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| 1.0822 | 4.65 | 1050 | 2.5435 | |
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| 0.9355 | 4.87 | 1100 | 2.7256 | |
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| 0.9527 | 5.09 | 1150 | 2.8934 | |
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| 0.9454 | 5.31 | 1200 | 3.0235 | |
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| 0.6458 | 5.53 | 1250 | 3.2280 | |
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| 0.8697 | 5.75 | 1300 | 2.8636 | |
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| 0.9365 | 5.97 | 1350 | 2.8955 | |
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| 0.4425 | 6.19 | 1400 | 3.0859 | |
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| 0.6329 | 6.42 | 1450 | 3.0695 | |
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| 0.7564 | 6.64 | 1500 | 2.5050 | |
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| 0.5747 | 6.86 | 1550 | 3.2825 | |
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| 0.5451 | 7.08 | 1600 | 3.4123 | |
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| 0.5432 | 7.3 | 1650 | 3.1163 | |
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| 0.3738 | 7.52 | 1700 | 2.8969 | |
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| 0.5026 | 7.74 | 1750 | 2.8579 | |
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| 0.4245 | 7.96 | 1800 | 3.2212 | |
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| 0.3145 | 8.19 | 1850 | 3.4482 | |
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| 0.516 | 8.41 | 1900 | 2.9995 | |
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| 0.2816 | 8.63 | 1950 | 2.9903 | |
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| 0.3946 | 8.85 | 2000 | 3.3378 | |
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| 0.3854 | 9.07 | 2050 | 3.4644 | |
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| 0.2191 | 9.29 | 2100 | 3.5034 | |
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| 0.3854 | 9.51 | 2150 | 3.4320 | |
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| 0.2207 | 9.73 | 2200 | 3.6972 | |
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| 0.2779 | 9.96 | 2250 | 3.6866 | |
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| 0.2837 | 10.18 | 2300 | 3.8988 | |
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| 0.1613 | 10.4 | 2350 | 3.8722 | |
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| 0.1069 | 10.62 | 2400 | 3.9079 | |
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| 0.4031 | 10.84 | 2450 | 3.5352 | |
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| 0.2129 | 11.06 | 2500 | 3.6764 | |
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| 0.1166 | 11.28 | 2550 | 4.1964 | |
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| 0.1599 | 11.5 | 2600 | 4.2577 | |
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| 0.2108 | 11.73 | 2650 | 3.7519 | |
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| 0.3207 | 11.95 | 2700 | 3.6609 | |
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| 0.2291 | 12.17 | 2750 | 3.5265 | |
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| 0.1609 | 12.39 | 2800 | 3.8727 | |
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| 0.2308 | 12.61 | 2850 | 3.9877 | |
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| 0.1461 | 12.83 | 2900 | 4.0395 | |
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| 0.1353 | 13.05 | 2950 | 3.8678 | |
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| 0.0735 | 13.27 | 3000 | 3.9054 | |
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| 0.1695 | 13.5 | 3050 | 3.5661 | |
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| 0.0129 | 13.72 | 3100 | 3.9625 | |
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| 0.1691 | 13.94 | 3150 | 3.7996 | |
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| 0.066 | 14.16 | 3200 | 4.2540 | |
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| 0.0484 | 14.38 | 3250 | 4.0625 | |
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| 0.099 | 14.6 | 3300 | 4.4666 | |
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| 0.127 | 14.82 | 3350 | 4.0762 | |
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| 0.046 | 15.04 | 3400 | 4.1859 | |
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| 0.0608 | 15.27 | 3450 | 4.4004 | |
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| 0.1002 | 15.49 | 3500 | 4.3228 | |
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| 0.0394 | 15.71 | 3550 | 4.4576 | |
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| 0.0863 | 15.93 | 3600 | 4.4386 | |
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| 0.0214 | 16.15 | 3650 | 4.5233 | |
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| 0.0661 | 16.37 | 3700 | 4.4493 | |
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| 0.0448 | 16.59 | 3750 | 4.3361 | |
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| 0.0463 | 16.81 | 3800 | 4.4174 | |
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| 0.0456 | 17.04 | 3850 | 4.4851 | |
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| 0.0144 | 17.26 | 3900 | 4.4655 | |
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| 0.0268 | 17.48 | 3950 | 4.4417 | |
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| 0.0529 | 17.7 | 4000 | 4.3580 | |
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| 0.0678 | 17.92 | 4050 | 4.2008 | |
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| 0.0039 | 18.14 | 4100 | 4.2346 | |
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| 0.0481 | 18.36 | 4150 | 4.2652 | |
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| 0.0501 | 18.58 | 4200 | 4.2786 | |
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| 0.0271 | 18.81 | 4250 | 4.2857 | |
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| 0.0322 | 19.03 | 4300 | 4.3047 | |
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| 0.0187 | 19.25 | 4350 | 4.3691 | |
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| 0.0469 | 19.47 | 4400 | 4.3560 | |
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| 0.0056 | 19.69 | 4450 | 4.3626 | |
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| 0.0099 | 19.91 | 4500 | 4.3701 | |
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### Framework versions |
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- Transformers 4.35.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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