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--- |
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library_name: transformers |
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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: tmp |
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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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# tmp |
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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: 5.1124 |
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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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| 5.2734 | 0.2212 | 50 | 4.4270 | |
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| 4.3976 | 0.4425 | 100 | 4.0382 | |
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| 4.0042 | 0.6637 | 150 | 3.8146 | |
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| 3.7912 | 0.8850 | 200 | 3.5961 | |
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| 3.4488 | 1.1062 | 250 | 3.7510 | |
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| 3.1503 | 1.3274 | 300 | 3.1755 | |
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| 3.1023 | 1.5487 | 350 | 2.8744 | |
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| 2.7424 | 1.7699 | 400 | 2.7684 | |
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| 2.3707 | 1.9912 | 450 | 2.7751 | |
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| 2.0726 | 2.2124 | 500 | 2.8069 | |
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| 1.7808 | 2.4336 | 550 | 2.4706 | |
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| 1.9086 | 2.6549 | 600 | 2.3128 | |
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| 1.8711 | 2.8761 | 650 | 2.2711 | |
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| 1.5378 | 3.0973 | 700 | 2.7780 | |
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| 1.4234 | 3.3186 | 750 | 2.3195 | |
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| 1.3624 | 3.5398 | 800 | 2.8083 | |
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| 1.5029 | 3.7611 | 850 | 2.3164 | |
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| 1.4002 | 3.9823 | 900 | 2.2043 | |
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| 0.993 | 4.2035 | 950 | 2.3923 | |
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| 1.1307 | 4.4248 | 1000 | 2.6620 | |
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| 1.0207 | 4.6460 | 1050 | 3.0029 | |
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| 0.9392 | 4.8673 | 1100 | 2.7303 | |
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| 0.8404 | 5.0885 | 1150 | 2.9590 | |
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| 0.7301 | 5.3097 | 1200 | 3.0281 | |
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| 0.723 | 5.5310 | 1250 | 2.8981 | |
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| 0.5396 | 5.7522 | 1300 | 3.2900 | |
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| 0.8811 | 5.9735 | 1350 | 2.8048 | |
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| 0.5488 | 6.1947 | 1400 | 3.0010 | |
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| 0.5603 | 6.4159 | 1450 | 3.3632 | |
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| 0.6611 | 6.6372 | 1500 | 3.1133 | |
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| 0.589 | 6.8584 | 1550 | 2.9019 | |
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| 0.5597 | 7.0796 | 1600 | 3.5935 | |
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| 0.2414 | 7.3009 | 1650 | 3.6715 | |
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| 0.5152 | 7.5221 | 1700 | 3.3859 | |
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| 0.3482 | 7.7434 | 1750 | 3.4798 | |
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| 0.4217 | 7.9646 | 1800 | 3.6040 | |
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| 0.3183 | 8.1858 | 1850 | 3.9913 | |
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| 0.1838 | 8.4071 | 1900 | 4.0946 | |
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| 0.2845 | 8.6283 | 1950 | 3.8923 | |
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| 0.3402 | 8.8496 | 2000 | 3.6999 | |
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| 0.3264 | 9.0708 | 2050 | 3.7774 | |
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| 0.205 | 9.2920 | 2100 | 3.9310 | |
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| 0.2841 | 9.5133 | 2150 | 4.1358 | |
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| 0.4066 | 9.7345 | 2200 | 3.8157 | |
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| 0.2587 | 9.9558 | 2250 | 3.8218 | |
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| 0.3097 | 10.1770 | 2300 | 3.3976 | |
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| 0.1278 | 10.3982 | 2350 | 3.8840 | |
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| 0.2826 | 10.6195 | 2400 | 4.1218 | |
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| 0.3355 | 10.8407 | 2450 | 4.1840 | |
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| 0.0822 | 11.0619 | 2500 | 4.3269 | |
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| 0.0617 | 11.2832 | 2550 | 4.2505 | |
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| 0.2015 | 11.5044 | 2600 | 4.3315 | |
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| 0.1249 | 11.7257 | 2650 | 4.3413 | |
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| 0.118 | 11.9469 | 2700 | 4.4579 | |
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| 0.1772 | 12.1681 | 2750 | 4.2534 | |
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| 0.0556 | 12.3894 | 2800 | 4.4677 | |
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| 0.1161 | 12.6106 | 2850 | 4.3609 | |
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| 0.13 | 12.8319 | 2900 | 4.2524 | |
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| 0.1565 | 13.0531 | 2950 | 4.1582 | |
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| 0.1165 | 13.2743 | 3000 | 4.5896 | |
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| 0.0341 | 13.4956 | 3050 | 4.7110 | |
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| 0.0532 | 13.7168 | 3100 | 4.6562 | |
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| 0.1283 | 13.9381 | 3150 | 4.8117 | |
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| 0.0744 | 14.1593 | 3200 | 4.6408 | |
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| 0.0289 | 14.3805 | 3250 | 4.8391 | |
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| 0.0293 | 14.6018 | 3300 | 4.9042 | |
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| 0.1226 | 14.8230 | 3350 | 4.8181 | |
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| 0.0453 | 15.0442 | 3400 | 4.8071 | |
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| 0.0229 | 15.2655 | 3450 | 4.8802 | |
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| 0.0077 | 15.4867 | 3500 | 4.8759 | |
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| 0.0439 | 15.7080 | 3550 | 4.9694 | |
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| 0.0754 | 15.9292 | 3600 | 4.9196 | |
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| 0.0608 | 16.1504 | 3650 | 4.7920 | |
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| 0.0292 | 16.3717 | 3700 | 4.9271 | |
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| 0.0059 | 16.5929 | 3750 | 4.9988 | |
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| 0.0286 | 16.8142 | 3800 | 4.9258 | |
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| 0.0047 | 17.0354 | 3850 | 4.9470 | |
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| 0.0231 | 17.2566 | 3900 | 4.9583 | |
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| 0.0254 | 17.4779 | 3950 | 4.9438 | |
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| 0.023 | 17.6991 | 4000 | 4.9529 | |
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| 0.016 | 17.9204 | 4050 | 5.0210 | |
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| 0.0039 | 18.1416 | 4100 | 5.0263 | |
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| 0.0039 | 18.3628 | 4150 | 5.0436 | |
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| 0.0103 | 18.5841 | 4200 | 5.0655 | |
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| 0.0084 | 18.8053 | 4250 | 5.0971 | |
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| 0.0681 | 19.0265 | 4300 | 5.0795 | |
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| 0.0157 | 19.2478 | 4350 | 5.0929 | |
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| 0.0039 | 19.4690 | 4400 | 5.1009 | |
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| 0.0089 | 19.6903 | 4450 | 5.1096 | |
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| 0.0086 | 19.9115 | 4500 | 5.1124 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.5.0+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.19.1 |
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