|
--- |
|
license: cc-by-nc-sa-4.0 |
|
base_model: microsoft/layoutlmv2-base-uncased |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: layoutlmv2-base-uncased_finetuned_docvqa |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# layoutlmv2-base-uncased_finetuned_docvqa |
|
|
|
This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 4.9097 |
|
|
|
## Model description |
|
|
|
More information needed |
|
|
|
## Intended uses & limitations |
|
|
|
More information needed |
|
|
|
## Training and evaluation data |
|
|
|
More information needed |
|
|
|
## Training procedure |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 5e-05 |
|
- train_batch_size: 4 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 5.3187 | 0.22 | 50 | 4.6843 | |
|
| 4.5031 | 0.44 | 100 | 4.1274 | |
|
| 4.128 | 0.66 | 150 | 3.7921 | |
|
| 3.9091 | 0.88 | 200 | 3.6115 | |
|
| 3.6889 | 1.11 | 250 | 3.5696 | |
|
| 3.1707 | 1.33 | 300 | 3.1811 | |
|
| 3.0354 | 1.55 | 350 | 2.8562 | |
|
| 2.7856 | 1.77 | 400 | 2.7444 | |
|
| 2.4529 | 1.99 | 450 | 2.7386 | |
|
| 1.9655 | 2.21 | 500 | 2.6058 | |
|
| 1.9712 | 2.43 | 550 | 2.3241 | |
|
| 1.9305 | 2.65 | 600 | 2.2414 | |
|
| 1.7701 | 2.88 | 650 | 2.1765 | |
|
| 1.3844 | 3.1 | 700 | 2.7470 | |
|
| 1.4493 | 3.32 | 750 | 2.3821 | |
|
| 1.2487 | 3.54 | 800 | 2.0868 | |
|
| 1.3189 | 3.76 | 850 | 2.5860 | |
|
| 1.3709 | 3.98 | 900 | 2.4280 | |
|
| 1.1087 | 4.2 | 950 | 2.5985 | |
|
| 0.9481 | 4.42 | 1000 | 3.3342 | |
|
| 1.0106 | 4.65 | 1050 | 3.0318 | |
|
| 0.9703 | 4.87 | 1100 | 2.7671 | |
|
| 0.788 | 5.09 | 1150 | 3.0565 | |
|
| 0.6952 | 5.31 | 1200 | 3.3631 | |
|
| 0.8017 | 5.53 | 1250 | 3.2544 | |
|
| 0.6489 | 5.75 | 1300 | 3.0772 | |
|
| 0.7419 | 5.97 | 1350 | 2.6226 | |
|
| 0.558 | 6.19 | 1400 | 3.5186 | |
|
| 0.5727 | 6.42 | 1450 | 3.3600 | |
|
| 0.5322 | 6.64 | 1500 | 3.5181 | |
|
| 0.6472 | 6.86 | 1550 | 3.6967 | |
|
| 0.5805 | 7.08 | 1600 | 3.2425 | |
|
| 0.4877 | 7.3 | 1650 | 3.4871 | |
|
| 0.273 | 7.52 | 1700 | 3.5272 | |
|
| 0.5527 | 7.74 | 1750 | 3.0758 | |
|
| 0.2936 | 7.96 | 1800 | 3.3492 | |
|
| 0.2585 | 8.19 | 1850 | 3.4836 | |
|
| 0.5038 | 8.41 | 1900 | 3.3159 | |
|
| 0.3943 | 8.63 | 1950 | 3.3977 | |
|
| 0.3129 | 8.85 | 2000 | 3.8042 | |
|
| 0.2977 | 9.07 | 2050 | 3.7062 | |
|
| 0.2695 | 9.29 | 2100 | 3.7420 | |
|
| 0.363 | 9.51 | 2150 | 3.6655 | |
|
| 0.1834 | 9.73 | 2200 | 3.7858 | |
|
| 0.3347 | 9.96 | 2250 | 3.9257 | |
|
| 0.2159 | 10.18 | 2300 | 3.9075 | |
|
| 0.2691 | 10.4 | 2350 | 3.8001 | |
|
| 0.2965 | 10.62 | 2400 | 3.6177 | |
|
| 0.3078 | 10.84 | 2450 | 3.8440 | |
|
| 0.1397 | 11.06 | 2500 | 4.0490 | |
|
| 0.052 | 11.28 | 2550 | 4.2137 | |
|
| 0.1741 | 11.5 | 2600 | 4.2273 | |
|
| 0.2956 | 11.73 | 2650 | 3.8075 | |
|
| 0.2098 | 11.95 | 2700 | 4.1653 | |
|
| 0.1466 | 12.17 | 2750 | 4.2080 | |
|
| 0.1378 | 12.39 | 2800 | 4.0473 | |
|
| 0.1864 | 12.61 | 2850 | 4.0665 | |
|
| 0.1938 | 12.83 | 2900 | 4.1019 | |
|
| 0.2332 | 13.05 | 2950 | 3.9249 | |
|
| 0.0486 | 13.27 | 3000 | 4.2374 | |
|
| 0.223 | 13.5 | 3050 | 4.1405 | |
|
| 0.1387 | 13.72 | 3100 | 4.1833 | |
|
| 0.1447 | 13.94 | 3150 | 4.0949 | |
|
| 0.0265 | 14.16 | 3200 | 4.2652 | |
|
| 0.0253 | 14.38 | 3250 | 4.5294 | |
|
| 0.1781 | 14.6 | 3300 | 4.5310 | |
|
| 0.0676 | 14.82 | 3350 | 4.3897 | |
|
| 0.0692 | 15.04 | 3400 | 4.3176 | |
|
| 0.1093 | 15.27 | 3450 | 4.3505 | |
|
| 0.0219 | 15.49 | 3500 | 4.4436 | |
|
| 0.0834 | 15.71 | 3550 | 4.4736 | |
|
| 0.0728 | 15.93 | 3600 | 4.5234 | |
|
| 0.0612 | 16.15 | 3650 | 4.6432 | |
|
| 0.0844 | 16.37 | 3700 | 4.5729 | |
|
| 0.0269 | 16.59 | 3750 | 4.7230 | |
|
| 0.037 | 16.81 | 3800 | 4.7512 | |
|
| 0.0532 | 17.04 | 3850 | 4.8247 | |
|
| 0.0042 | 17.26 | 3900 | 4.8263 | |
|
| 0.0684 | 17.48 | 3950 | 4.7495 | |
|
| 0.0058 | 17.7 | 4000 | 4.7748 | |
|
| 0.0158 | 17.92 | 4050 | 4.8827 | |
|
| 0.0059 | 18.14 | 4100 | 4.8746 | |
|
| 0.0217 | 18.36 | 4150 | 4.8981 | |
|
| 0.0725 | 18.58 | 4200 | 4.9908 | |
|
| 0.0399 | 18.81 | 4250 | 4.8712 | |
|
| 0.0478 | 19.03 | 4300 | 4.9006 | |
|
| 0.0212 | 19.25 | 4350 | 4.9160 | |
|
| 0.0269 | 19.47 | 4400 | 4.9076 | |
|
| 0.0317 | 19.69 | 4450 | 4.9081 | |
|
| 0.0233 | 19.91 | 4500 | 4.9097 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.0 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|