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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: 5.3353 |
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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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| 0.153 | 0.22 | 50 | 5.3909 | |
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| 0.2793 | 0.44 | 100 | 5.0150 | |
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| 0.2634 | 0.66 | 150 | 4.6620 | |
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| 0.5192 | 0.88 | 200 | 4.7826 | |
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| 0.3096 | 1.11 | 250 | 4.9532 | |
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| 0.2638 | 1.33 | 300 | 5.2584 | |
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| 0.4727 | 1.55 | 350 | 4.0943 | |
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| 0.2763 | 1.77 | 400 | 4.8408 | |
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| 1.0425 | 1.99 | 450 | 5.0344 | |
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| 0.4477 | 2.21 | 500 | 4.9084 | |
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| 0.3266 | 2.43 | 550 | 5.0996 | |
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| 0.3085 | 2.65 | 600 | 4.4858 | |
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| 0.4648 | 2.88 | 650 | 4.0630 | |
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| 0.1845 | 3.1 | 700 | 5.3969 | |
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| 0.1616 | 3.32 | 750 | 4.8225 | |
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| 0.1752 | 3.54 | 800 | 5.2945 | |
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| 0.1877 | 3.76 | 850 | 5.2358 | |
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| 0.3172 | 3.98 | 900 | 5.2205 | |
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| 0.1627 | 4.2 | 950 | 4.9991 | |
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| 0.2548 | 4.42 | 1000 | 4.6917 | |
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| 0.1566 | 4.65 | 1050 | 5.1266 | |
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| 0.2616 | 4.87 | 1100 | 4.3241 | |
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| 0.1199 | 5.09 | 1150 | 4.9821 | |
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| 0.1372 | 5.31 | 1200 | 5.0838 | |
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| 0.1198 | 5.53 | 1250 | 5.0156 | |
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| 0.0558 | 5.75 | 1300 | 4.8638 | |
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| 0.1331 | 5.97 | 1350 | 4.9492 | |
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| 0.0689 | 6.19 | 1400 | 4.6926 | |
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| 0.0912 | 6.42 | 1450 | 4.5153 | |
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| 0.0495 | 6.64 | 1500 | 4.6969 | |
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| 0.0853 | 6.86 | 1550 | 4.7690 | |
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| 0.1072 | 7.08 | 1600 | 4.6783 | |
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| 0.034 | 7.3 | 1650 | 4.7351 | |
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| 0.2999 | 7.52 | 1700 | 4.5185 | |
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| 0.0763 | 7.74 | 1750 | 4.5825 | |
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| 0.0799 | 7.96 | 1800 | 4.7218 | |
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| 0.0343 | 8.19 | 1850 | 5.1508 | |
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| 0.0396 | 8.41 | 1900 | 5.4893 | |
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| 0.033 | 8.63 | 1950 | 5.5167 | |
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| 0.0295 | 8.85 | 2000 | 5.6252 | |
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| 0.2303 | 9.07 | 2050 | 4.7031 | |
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| 0.088 | 9.29 | 2100 | 4.7323 | |
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| 0.0666 | 9.51 | 2150 | 4.8688 | |
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| 0.0597 | 9.73 | 2200 | 5.6007 | |
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| 0.0615 | 9.96 | 2250 | 5.5403 | |
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| 0.1003 | 10.18 | 2300 | 5.3198 | |
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| 0.0457 | 10.4 | 2350 | 5.4828 | |
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| 0.0391 | 10.62 | 2400 | 5.5312 | |
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| 0.0325 | 10.84 | 2450 | 5.7410 | |
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| 0.0147 | 11.06 | 2500 | 5.8749 | |
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| 0.1013 | 11.28 | 2550 | 5.6522 | |
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| 0.001 | 11.5 | 2600 | 5.7776 | |
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| 0.0002 | 11.73 | 2650 | 5.8431 | |
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| 0.03 | 11.95 | 2700 | 5.9751 | |
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| 0.0452 | 12.17 | 2750 | 5.6928 | |
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| 0.0002 | 12.39 | 2800 | 5.6264 | |
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| 0.0109 | 12.61 | 2850 | 5.2688 | |
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| 0.0801 | 12.83 | 2900 | 5.2780 | |
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| 0.0216 | 13.05 | 2950 | 5.3691 | |
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| 0.0002 | 13.27 | 3000 | 5.5237 | |
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| 0.0092 | 13.5 | 3050 | 5.3662 | |
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| 0.0124 | 13.72 | 3100 | 5.4474 | |
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| 0.0515 | 13.94 | 3150 | 5.3623 | |
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| 0.0032 | 14.16 | 3200 | 5.4168 | |
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| 0.0051 | 14.38 | 3250 | 5.2897 | |
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| 0.0002 | 14.6 | 3300 | 5.3205 | |
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| 0.014 | 14.82 | 3350 | 5.2114 | |
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| 0.0004 | 15.04 | 3400 | 5.2342 | |
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| 0.0104 | 15.27 | 3450 | 5.2562 | |
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| 0.0107 | 15.49 | 3500 | 5.1112 | |
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| 0.0002 | 15.71 | 3550 | 5.1515 | |
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| 0.0002 | 15.93 | 3600 | 5.2054 | |
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| 0.0002 | 16.15 | 3650 | 5.1968 | |
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| 0.0003 | 16.37 | 3700 | 5.3196 | |
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| 0.0246 | 16.59 | 3750 | 5.3111 | |
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| 0.0054 | 16.81 | 3800 | 5.3335 | |
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| 0.0001 | 17.04 | 3850 | 5.3488 | |
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| 0.0243 | 17.26 | 3900 | 5.2597 | |
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| 0.0217 | 17.48 | 3950 | 5.2834 | |
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| 0.0002 | 17.7 | 4000 | 5.2947 | |
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| 0.0002 | 17.92 | 4050 | 5.3131 | |
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| 0.0001 | 18.14 | 4100 | 5.3240 | |
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| 0.0016 | 18.36 | 4150 | 5.3129 | |
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| 0.0133 | 18.58 | 4200 | 5.3241 | |
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| 0.0002 | 18.81 | 4250 | 5.3382 | |
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| 0.0159 | 19.03 | 4300 | 5.3764 | |
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| 0.003 | 19.25 | 4350 | 5.3776 | |
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| 0.0516 | 19.47 | 4400 | 5.3389 | |
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| 0.016 | 19.69 | 4450 | 5.3275 | |
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| 0.0105 | 19.91 | 4500 | 5.3353 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cpu |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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