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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: layoutlm_qa |
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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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# layoutlm_qa |
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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: 4.7055 |
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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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| 5.2983 | 0.22 | 50 | 4.5220 | |
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| 4.4844 | 0.44 | 100 | 4.1165 | |
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| 4.1775 | 0.66 | 150 | 3.8581 | |
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| 3.8202 | 0.88 | 200 | 3.5512 | |
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| 3.5174 | 1.11 | 250 | 3.9044 | |
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| 3.3304 | 1.33 | 300 | 3.3451 | |
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| 3.1339 | 1.55 | 350 | 3.0255 | |
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| 2.9657 | 1.77 | 400 | 2.9532 | |
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| 2.7647 | 1.99 | 450 | 3.0166 | |
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| 2.3376 | 2.21 | 500 | 2.9174 | |
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| 1.9903 | 2.43 | 550 | 2.7034 | |
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| 1.9975 | 2.65 | 600 | 2.4877 | |
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| 1.8642 | 2.88 | 650 | 2.3439 | |
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| 1.6613 | 3.1 | 700 | 2.3873 | |
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| 1.4884 | 3.32 | 750 | 2.1284 | |
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| 1.3033 | 3.54 | 800 | 2.3192 | |
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| 1.3821 | 3.76 | 850 | 3.0033 | |
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| 1.4121 | 3.98 | 900 | 2.3074 | |
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| 1.0226 | 4.2 | 950 | 2.5772 | |
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| 0.8721 | 4.42 | 1000 | 2.8909 | |
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| 1.1364 | 4.65 | 1050 | 2.6966 | |
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| 1.1504 | 4.87 | 1100 | 2.7247 | |
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| 0.7333 | 5.09 | 1150 | 3.3075 | |
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| 0.7097 | 5.31 | 1200 | 3.2459 | |
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| 0.7138 | 5.53 | 1250 | 3.2652 | |
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| 0.6852 | 5.75 | 1300 | 3.0537 | |
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| 0.6396 | 5.97 | 1350 | 3.1964 | |
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| 0.6756 | 6.19 | 1400 | 3.3380 | |
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| 0.5771 | 6.42 | 1450 | 3.4396 | |
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| 0.6753 | 6.64 | 1500 | 3.0820 | |
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| 0.5361 | 6.86 | 1550 | 3.3736 | |
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| 0.5659 | 7.08 | 1600 | 3.3211 | |
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| 0.6637 | 7.3 | 1650 | 3.2642 | |
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| 0.5321 | 7.52 | 1700 | 3.3275 | |
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| 0.3525 | 7.74 | 1750 | 3.5490 | |
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| 0.4964 | 7.96 | 1800 | 3.5147 | |
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| 0.4882 | 8.19 | 1850 | 3.4210 | |
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| 0.3879 | 8.41 | 1900 | 3.9024 | |
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| 0.4991 | 8.63 | 1950 | 3.5269 | |
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| 0.5084 | 8.85 | 2000 | 3.7400 | |
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| 0.3502 | 9.07 | 2050 | 3.6098 | |
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| 0.2492 | 9.29 | 2100 | 3.8580 | |
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| 0.2889 | 9.51 | 2150 | 3.6365 | |
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| 0.2672 | 9.73 | 2200 | 3.5260 | |
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| 0.4289 | 9.96 | 2250 | 3.1862 | |
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| 0.1803 | 10.18 | 2300 | 3.9092 | |
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| 0.2014 | 10.4 | 2350 | 3.8147 | |
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| 0.3197 | 10.62 | 2400 | 3.7593 | |
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| 0.1503 | 10.84 | 2450 | 3.8731 | |
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| 0.1766 | 11.06 | 2500 | 3.6034 | |
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| 0.3074 | 11.28 | 2550 | 3.6639 | |
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| 0.1637 | 11.5 | 2600 | 3.9461 | |
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| 0.2674 | 11.73 | 2650 | 3.6418 | |
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| 0.2074 | 11.95 | 2700 | 3.7350 | |
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| 0.1034 | 12.17 | 2750 | 4.0971 | |
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| 0.1438 | 12.39 | 2800 | 3.8840 | |
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| 0.0739 | 12.61 | 2850 | 3.9797 | |
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| 0.2329 | 12.83 | 2900 | 4.0602 | |
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| 0.2348 | 13.05 | 2950 | 3.9343 | |
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| 0.1119 | 13.27 | 3000 | 4.2030 | |
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| 0.0955 | 13.5 | 3050 | 4.3291 | |
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| 0.0787 | 13.72 | 3100 | 4.1507 | |
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| 0.1446 | 13.94 | 3150 | 4.1370 | |
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| 0.0202 | 14.16 | 3200 | 4.2964 | |
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| 0.1201 | 14.38 | 3250 | 4.3851 | |
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| 0.0783 | 14.6 | 3300 | 4.2924 | |
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| 0.0536 | 14.82 | 3350 | 4.2803 | |
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| 0.1042 | 15.04 | 3400 | 4.2722 | |
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| 0.1374 | 15.27 | 3450 | 4.3609 | |
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| 0.096 | 15.49 | 3500 | 4.3868 | |
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| 0.0223 | 15.71 | 3550 | 4.3771 | |
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| 0.0573 | 15.93 | 3600 | 4.4002 | |
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| 0.0688 | 16.15 | 3650 | 4.4771 | |
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| 0.0052 | 16.37 | 3700 | 4.5400 | |
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| 0.0128 | 16.59 | 3750 | 4.5740 | |
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| 0.0913 | 16.81 | 3800 | 4.6113 | |
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| 0.0783 | 17.04 | 3850 | 4.2686 | |
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| 0.0344 | 17.26 | 3900 | 4.3120 | |
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| 0.0064 | 17.48 | 3950 | 4.4239 | |
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| 0.1358 | 17.7 | 4000 | 4.5027 | |
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| 0.0299 | 17.92 | 4050 | 4.5290 | |
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| 0.0157 | 18.14 | 4100 | 4.6270 | |
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| 0.0141 | 18.36 | 4150 | 4.6847 | |
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| 0.0382 | 18.58 | 4200 | 4.6527 | |
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| 0.0069 | 18.81 | 4250 | 4.5969 | |
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| 0.0698 | 19.03 | 4300 | 4.6249 | |
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| 0.0303 | 19.25 | 4350 | 4.6679 | |
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| 0.0076 | 19.47 | 4400 | 4.7096 | |
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| 0.0161 | 19.69 | 4450 | 4.7129 | |
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| 0.0572 | 19.91 | 4500 | 4.7055 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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