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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: 3.8273 |
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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: 8 |
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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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| 2.0156 | 0.44 | 50 | 2.4679 | |
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| 1.8368 | 0.88 | 100 | 2.2079 | |
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| 1.5567 | 1.33 | 150 | 2.3312 | |
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| 1.3487 | 1.77 | 200 | 2.8410 | |
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| 1.2254 | 2.21 | 250 | 2.6996 | |
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| 1.1201 | 2.65 | 300 | 2.2915 | |
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| 0.8816 | 3.1 | 350 | 2.3419 | |
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| 0.7885 | 3.54 | 400 | 2.6410 | |
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| 0.7532 | 3.98 | 450 | 2.7539 | |
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| 0.5822 | 4.42 | 500 | 2.7213 | |
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| 0.5801 | 4.87 | 550 | 2.7429 | |
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| 0.5043 | 5.31 | 600 | 2.8523 | |
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| 0.4545 | 5.75 | 650 | 2.8666 | |
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| 0.4029 | 6.19 | 700 | 3.4559 | |
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| 0.3568 | 6.64 | 750 | 3.1760 | |
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| 0.3962 | 7.08 | 800 | 3.0625 | |
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| 0.2381 | 7.52 | 850 | 3.3868 | |
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| 0.2492 | 7.96 | 900 | 3.7453 | |
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| 0.3813 | 8.41 | 950 | 3.2516 | |
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| 0.2477 | 8.85 | 1000 | 3.4677 | |
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| 0.1834 | 9.29 | 1050 | 3.2748 | |
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| 0.2067 | 9.73 | 1100 | 3.7590 | |
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| 0.2062 | 10.18 | 1150 | 3.5956 | |
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| 0.1337 | 10.62 | 1200 | 3.8232 | |
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| 0.1785 | 11.06 | 1250 | 3.5264 | |
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| 0.0906 | 11.5 | 1300 | 3.6157 | |
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| 0.1649 | 11.95 | 1350 | 3.4667 | |
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| 0.1306 | 12.39 | 1400 | 3.7029 | |
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| 0.0529 | 12.83 | 1450 | 3.6307 | |
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| 0.0628 | 13.27 | 1500 | 3.5905 | |
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| 0.1015 | 13.72 | 1550 | 3.4659 | |
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| 0.0693 | 14.16 | 1600 | 3.7713 | |
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| 0.1111 | 14.6 | 1650 | 3.7680 | |
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| 0.0414 | 15.04 | 1700 | 3.8956 | |
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| 0.0256 | 15.49 | 1750 | 3.9021 | |
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| 0.0737 | 15.93 | 1800 | 3.9392 | |
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| 0.0577 | 16.37 | 1850 | 3.8129 | |
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| 0.0744 | 16.81 | 1900 | 3.8356 | |
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| 0.0698 | 17.26 | 1950 | 3.8406 | |
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| 0.0173 | 17.7 | 2000 | 3.8611 | |
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| 0.0667 | 18.14 | 2050 | 3.7995 | |
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| 0.0482 | 18.58 | 2100 | 3.8132 | |
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| 0.0458 | 19.03 | 2150 | 3.8335 | |
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| 0.0415 | 19.47 | 2200 | 3.8475 | |
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| 0.0236 | 19.91 | 2250 | 3.8273 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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