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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: 5.1691 |
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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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| 5.2266 | 0.22 | 50 | 4.7202 | |
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| 4.4028 | 0.44 | 100 | 4.1366 | |
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| 4.0483 | 0.66 | 150 | 3.8471 | |
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| 3.7553 | 0.88 | 200 | 3.5072 | |
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| 3.4046 | 1.11 | 250 | 3.5053 | |
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| 3.1543 | 1.33 | 300 | 3.1483 | |
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| 3.0577 | 1.55 | 350 | 3.0745 | |
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| 2.8076 | 1.77 | 400 | 2.8592 | |
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| 2.456 | 1.99 | 450 | 2.7019 | |
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| 1.9787 | 2.21 | 500 | 2.7553 | |
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| 1.9308 | 2.43 | 550 | 2.3374 | |
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| 1.7637 | 2.65 | 600 | 2.2109 | |
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| 1.7719 | 2.88 | 650 | 2.9137 | |
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| 1.6661 | 3.1 | 700 | 2.7946 | |
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| 1.3154 | 3.32 | 750 | 2.5750 | |
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| 1.3015 | 3.54 | 800 | 2.4883 | |
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| 1.2136 | 3.76 | 850 | 2.1466 | |
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| 1.253 | 3.98 | 900 | 2.2343 | |
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| 0.96 | 4.2 | 950 | 2.6481 | |
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| 0.9083 | 4.42 | 1000 | 2.2891 | |
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| 0.9441 | 4.65 | 1050 | 2.8459 | |
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| 0.9041 | 4.87 | 1100 | 3.0106 | |
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| 0.8727 | 5.09 | 1150 | 2.7765 | |
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| 0.6496 | 5.31 | 1200 | 3.0633 | |
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| 0.7388 | 5.53 | 1250 | 2.7464 | |
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| 0.5012 | 5.75 | 1300 | 3.3843 | |
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| 0.6762 | 5.97 | 1350 | 3.6035 | |
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| 0.4907 | 6.19 | 1400 | 3.4269 | |
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| 0.5893 | 6.42 | 1450 | 3.2352 | |
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| 0.4987 | 6.64 | 1500 | 3.2802 | |
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| 0.3867 | 6.86 | 1550 | 3.8191 | |
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| 0.6091 | 7.08 | 1600 | 3.4476 | |
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| 0.4088 | 7.3 | 1650 | 3.5099 | |
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| 0.4135 | 7.52 | 1700 | 3.4519 | |
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| 0.3859 | 7.74 | 1750 | 3.4147 | |
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| 0.335 | 7.96 | 1800 | 3.8082 | |
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| 0.2068 | 8.19 | 1850 | 4.3927 | |
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| 0.3149 | 8.41 | 1900 | 3.7065 | |
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| 0.2526 | 8.63 | 1950 | 3.6056 | |
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| 0.451 | 8.85 | 2000 | 3.7065 | |
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| 0.3792 | 9.07 | 2050 | 3.8738 | |
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| 0.2299 | 9.29 | 2100 | 3.8282 | |
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| 0.3064 | 9.51 | 2150 | 3.6586 | |
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| 0.26 | 9.73 | 2200 | 3.9155 | |
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| 0.3218 | 9.96 | 2250 | 3.5863 | |
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| 0.2826 | 10.18 | 2300 | 3.5095 | |
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| 0.149 | 10.4 | 2350 | 3.4537 | |
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| 0.1213 | 10.62 | 2400 | 3.8778 | |
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| 0.2157 | 10.84 | 2450 | 3.8106 | |
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| 0.2149 | 11.06 | 2500 | 4.2672 | |
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| 0.1212 | 11.28 | 2550 | 4.2534 | |
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| 0.1664 | 11.5 | 2600 | 4.3033 | |
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| 0.1487 | 11.73 | 2650 | 3.9483 | |
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| 0.1088 | 11.95 | 2700 | 3.9682 | |
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| 0.0791 | 12.17 | 2750 | 4.2143 | |
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| 0.0734 | 12.39 | 2800 | 4.2175 | |
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| 0.128 | 12.61 | 2850 | 4.2613 | |
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| 0.1851 | 12.83 | 2900 | 3.9094 | |
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| 0.1215 | 13.05 | 2950 | 4.2045 | |
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| 0.0438 | 13.27 | 3000 | 4.5802 | |
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| 0.0107 | 13.5 | 3050 | 4.7988 | |
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| 0.0606 | 13.72 | 3100 | 5.0228 | |
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| 0.0819 | 13.94 | 3150 | 4.9309 | |
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| 0.1375 | 14.16 | 3200 | 4.8995 | |
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| 0.0729 | 14.38 | 3250 | 4.7900 | |
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| 0.0832 | 14.6 | 3300 | 4.6417 | |
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| 0.0687 | 14.82 | 3350 | 4.8781 | |
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| 0.0516 | 15.04 | 3400 | 4.9231 | |
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| 0.056 | 15.27 | 3450 | 5.1059 | |
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| 0.0672 | 15.49 | 3500 | 5.0563 | |
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| 0.1036 | 15.71 | 3550 | 4.5889 | |
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| 0.1551 | 15.93 | 3600 | 4.4488 | |
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| 0.0509 | 16.15 | 3650 | 4.8964 | |
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| 0.0505 | 16.37 | 3700 | 4.9259 | |
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| 0.0295 | 16.59 | 3750 | 4.8617 | |
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| 0.0766 | 16.81 | 3800 | 4.7973 | |
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| 0.0103 | 17.04 | 3850 | 4.9249 | |
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| 0.0148 | 17.26 | 3900 | 4.9319 | |
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| 0.0105 | 17.48 | 3950 | 5.1000 | |
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| 0.0341 | 17.7 | 4000 | 4.9627 | |
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| 0.0547 | 17.92 | 4050 | 5.0149 | |
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| 0.0106 | 18.14 | 4100 | 5.0924 | |
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| 0.0045 | 18.36 | 4150 | 5.1550 | |
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| 0.0072 | 18.58 | 4200 | 5.1620 | |
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| 0.0428 | 18.81 | 4250 | 5.1546 | |
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| 0.0443 | 19.03 | 4300 | 5.1506 | |
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| 0.0244 | 19.25 | 4350 | 5.1720 | |
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| 0.0096 | 19.47 | 4400 | 5.1640 | |
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| 0.0265 | 19.69 | 4450 | 5.1647 | |
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| 0.0057 | 19.91 | 4500 | 5.1691 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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