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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: 5.2024 |
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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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| 5.2725 | 0.22 | 50 | 4.6295 | |
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| 4.532 | 0.44 | 100 | 4.2254 | |
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| 4.0834 | 0.66 | 150 | 3.8568 | |
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| 3.9787 | 0.88 | 200 | 3.6523 | |
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| 3.6224 | 1.11 | 250 | 3.8143 | |
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| 3.2397 | 1.33 | 300 | 3.1685 | |
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| 3.0931 | 1.55 | 350 | 3.0822 | |
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| 2.9593 | 1.77 | 400 | 2.9521 | |
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| 2.5904 | 1.99 | 450 | 2.7995 | |
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| 2.1358 | 2.21 | 500 | 2.4827 | |
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| 2.0137 | 2.43 | 550 | 2.3651 | |
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| 1.951 | 2.65 | 600 | 2.2448 | |
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| 1.684 | 2.88 | 650 | 2.3455 | |
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| 1.6708 | 3.1 | 700 | 2.5003 | |
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| 1.3927 | 3.32 | 750 | 2.3116 | |
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| 1.5237 | 3.54 | 800 | 2.6236 | |
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| 1.2826 | 3.76 | 850 | 2.4859 | |
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| 1.5274 | 3.98 | 900 | 2.1857 | |
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| 1.0727 | 4.2 | 950 | 2.5041 | |
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| 0.9465 | 4.42 | 1000 | 2.7958 | |
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| 1.0889 | 4.65 | 1050 | 2.3797 | |
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| 0.9121 | 4.87 | 1100 | 2.7570 | |
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| 0.8847 | 5.09 | 1150 | 3.0968 | |
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| 0.8864 | 5.31 | 1200 | 2.8488 | |
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| 0.8693 | 5.53 | 1250 | 2.6848 | |
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| 0.5451 | 5.75 | 1300 | 3.3272 | |
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| 0.8121 | 5.97 | 1350 | 3.6097 | |
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| 0.6214 | 6.19 | 1400 | 3.1954 | |
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| 0.5576 | 6.42 | 1450 | 3.2427 | |
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| 0.5576 | 6.64 | 1500 | 3.4471 | |
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| 0.4858 | 6.86 | 1550 | 3.2469 | |
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| 0.5947 | 7.08 | 1600 | 3.2522 | |
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| 0.4889 | 7.3 | 1650 | 3.3459 | |
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| 0.3126 | 7.52 | 1700 | 3.9616 | |
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| 0.3291 | 7.74 | 1750 | 3.9943 | |
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| 0.5337 | 7.96 | 1800 | 3.6498 | |
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| 0.2384 | 8.19 | 1850 | 4.2966 | |
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| 0.3566 | 8.41 | 1900 | 4.1365 | |
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| 0.3539 | 8.63 | 1950 | 4.1291 | |
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| 0.3219 | 8.85 | 2000 | 4.3024 | |
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| 0.2307 | 9.07 | 2050 | 4.1780 | |
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| 0.1922 | 9.29 | 2100 | 4.4078 | |
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| 0.1721 | 9.51 | 2150 | 4.2569 | |
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| 0.1541 | 9.73 | 2200 | 4.2138 | |
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| 0.3044 | 9.96 | 2250 | 4.2793 | |
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| 0.2642 | 10.18 | 2300 | 4.2676 | |
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| 0.1725 | 10.4 | 2350 | 4.0887 | |
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| 0.2223 | 10.62 | 2400 | 3.9813 | |
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| 0.2107 | 10.84 | 2450 | 4.1089 | |
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| 0.3262 | 11.06 | 2500 | 3.9025 | |
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| 0.383 | 11.28 | 2550 | 4.1511 | |
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| 0.1437 | 11.5 | 2600 | 4.1774 | |
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| 0.2707 | 11.73 | 2650 | 4.1749 | |
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| 0.1692 | 11.95 | 2700 | 4.3012 | |
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| 0.1651 | 12.17 | 2750 | 4.3723 | |
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| 0.1388 | 12.39 | 2800 | 4.3273 | |
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| 0.1072 | 12.61 | 2850 | 4.7238 | |
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| 0.1748 | 12.83 | 2900 | 4.3425 | |
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| 0.1053 | 13.05 | 2950 | 4.0696 | |
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| 0.1929 | 13.27 | 3000 | 4.6322 | |
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| 0.028 | 13.5 | 3050 | 4.4843 | |
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| 0.0207 | 13.72 | 3100 | 4.9324 | |
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| 0.0662 | 13.94 | 3150 | 4.9421 | |
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| 0.0644 | 14.16 | 3200 | 4.8991 | |
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| 0.0321 | 14.38 | 3250 | 4.7757 | |
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| 0.0567 | 14.6 | 3300 | 4.9158 | |
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| 0.0552 | 14.82 | 3350 | 5.0722 | |
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| 0.0695 | 15.04 | 3400 | 5.0160 | |
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| 0.081 | 15.27 | 3450 | 5.1969 | |
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| 0.084 | 15.49 | 3500 | 5.2285 | |
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| 0.0372 | 15.71 | 3550 | 5.2621 | |
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| 0.1193 | 15.93 | 3600 | 5.1806 | |
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| 0.0166 | 16.15 | 3650 | 5.2799 | |
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| 0.029 | 16.37 | 3700 | 5.2543 | |
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| 0.048 | 16.59 | 3750 | 5.1176 | |
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| 0.143 | 16.81 | 3800 | 5.1800 | |
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| 0.033 | 17.04 | 3850 | 5.1635 | |
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| 0.0424 | 17.26 | 3900 | 5.1982 | |
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| 0.004 | 17.48 | 3950 | 5.2322 | |
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| 0.0143 | 17.7 | 4000 | 5.2242 | |
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| 0.0261 | 17.92 | 4050 | 5.3110 | |
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| 0.0076 | 18.14 | 4100 | 5.3329 | |
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| 0.0036 | 18.36 | 4150 | 5.3355 | |
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| 0.0182 | 18.58 | 4200 | 5.3223 | |
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| 0.0466 | 18.81 | 4250 | 5.2396 | |
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| 0.0036 | 19.03 | 4300 | 5.2409 | |
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| 0.0278 | 19.25 | 4350 | 5.2128 | |
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| 0.015 | 19.47 | 4400 | 5.2227 | |
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| 0.0394 | 19.69 | 4450 | 5.2018 | |
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| 0.0034 | 19.91 | 4500 | 5.2024 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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