|
--- |
|
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: 4.6126 |
|
|
|
## 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 | |
|
|:-------------:|:-------:|:----:|:---------------:| |
|
| 5.2641 | 0.2212 | 50 | 4.8696 | |
|
| 4.6026 | 0.4425 | 100 | 4.2722 | |
|
| 4.3484 | 0.6637 | 150 | 4.0328 | |
|
| 3.879 | 0.8850 | 200 | 3.6907 | |
|
| 3.5541 | 1.1062 | 250 | 3.3437 | |
|
| 3.3072 | 1.3274 | 300 | 3.1499 | |
|
| 3.1514 | 1.5487 | 350 | 2.9365 | |
|
| 2.9353 | 1.7699 | 400 | 2.7036 | |
|
| 2.4954 | 1.9912 | 450 | 2.7155 | |
|
| 1.9393 | 2.2124 | 500 | 2.8356 | |
|
| 1.8631 | 2.4336 | 550 | 2.4434 | |
|
| 1.9553 | 2.6549 | 600 | 2.5365 | |
|
| 2.0108 | 2.8761 | 650 | 2.5717 | |
|
| 1.8383 | 3.0973 | 700 | 2.5751 | |
|
| 1.3356 | 3.3186 | 750 | 2.5472 | |
|
| 1.3101 | 3.5398 | 800 | 2.6720 | |
|
| 1.3699 | 3.7611 | 850 | 2.4359 | |
|
| 1.421 | 3.9823 | 900 | 2.9012 | |
|
| 1.1819 | 4.2035 | 950 | 2.9297 | |
|
| 0.9407 | 4.4248 | 1000 | 2.7371 | |
|
| 1.0575 | 4.6460 | 1050 | 2.3495 | |
|
| 0.9061 | 4.8673 | 1100 | 2.5941 | |
|
| 0.8149 | 5.0885 | 1150 | 2.7071 | |
|
| 0.7002 | 5.3097 | 1200 | 3.2910 | |
|
| 1.009 | 5.5310 | 1250 | 2.7820 | |
|
| 0.6106 | 5.7522 | 1300 | 2.9551 | |
|
| 0.7998 | 5.9735 | 1350 | 3.0283 | |
|
| 0.5198 | 6.1947 | 1400 | 3.0532 | |
|
| 0.5274 | 6.4159 | 1450 | 3.3331 | |
|
| 0.4868 | 6.6372 | 1500 | 3.0930 | |
|
| 0.4724 | 6.8584 | 1550 | 3.3668 | |
|
| 0.6184 | 7.0796 | 1600 | 3.1645 | |
|
| 0.4337 | 7.3009 | 1650 | 3.3045 | |
|
| 0.4681 | 7.5221 | 1700 | 3.3785 | |
|
| 0.3815 | 7.7434 | 1750 | 3.6287 | |
|
| 0.4704 | 7.9646 | 1800 | 3.6386 | |
|
| 0.2866 | 8.1858 | 1850 | 3.8093 | |
|
| 0.4064 | 8.4071 | 1900 | 3.6475 | |
|
| 0.4187 | 8.6283 | 1950 | 3.4646 | |
|
| 0.4037 | 8.8496 | 2000 | 3.8256 | |
|
| 0.3989 | 9.0708 | 2050 | 3.7898 | |
|
| 0.1772 | 9.2920 | 2100 | 3.9931 | |
|
| 0.2577 | 9.5133 | 2150 | 3.7201 | |
|
| 0.3283 | 9.7345 | 2200 | 3.7783 | |
|
| 0.416 | 9.9558 | 2250 | 3.7312 | |
|
| 0.1935 | 10.1770 | 2300 | 3.8151 | |
|
| 0.1934 | 10.3982 | 2350 | 3.6563 | |
|
| 0.2502 | 10.6195 | 2400 | 3.9194 | |
|
| 0.3274 | 10.8407 | 2450 | 3.6391 | |
|
| 0.0669 | 11.0619 | 2500 | 3.9782 | |
|
| 0.144 | 11.2832 | 2550 | 3.9159 | |
|
| 0.1992 | 11.5044 | 2600 | 4.2785 | |
|
| 0.1433 | 11.7257 | 2650 | 4.3765 | |
|
| 0.204 | 11.9469 | 2700 | 4.1064 | |
|
| 0.094 | 12.1681 | 2750 | 4.0756 | |
|
| 0.0549 | 12.3894 | 2800 | 4.3475 | |
|
| 0.1252 | 12.6106 | 2850 | 4.3339 | |
|
| 0.2964 | 12.8319 | 2900 | 4.0766 | |
|
| 0.0759 | 13.0531 | 2950 | 4.0707 | |
|
| 0.019 | 13.2743 | 3000 | 4.2173 | |
|
| 0.1115 | 13.4956 | 3050 | 4.2590 | |
|
| 0.0624 | 13.7168 | 3100 | 4.1736 | |
|
| 0.1996 | 13.9381 | 3150 | 4.2134 | |
|
| 0.1371 | 14.1593 | 3200 | 4.3083 | |
|
| 0.0826 | 14.3805 | 3250 | 4.3719 | |
|
| 0.0729 | 14.6018 | 3300 | 4.3055 | |
|
| 0.0893 | 14.8230 | 3350 | 4.2607 | |
|
| 0.0209 | 15.0442 | 3400 | 4.3385 | |
|
| 0.0463 | 15.2655 | 3450 | 4.5433 | |
|
| 0.0498 | 15.4867 | 3500 | 4.4161 | |
|
| 0.0544 | 15.7080 | 3550 | 4.5817 | |
|
| 0.1237 | 15.9292 | 3600 | 4.3659 | |
|
| 0.0696 | 16.1504 | 3650 | 4.1952 | |
|
| 0.0654 | 16.3717 | 3700 | 4.2650 | |
|
| 0.1063 | 16.5929 | 3750 | 4.1685 | |
|
| 0.0564 | 16.8142 | 3800 | 4.2705 | |
|
| 0.0212 | 17.0354 | 3850 | 4.3499 | |
|
| 0.0131 | 17.2566 | 3900 | 4.3843 | |
|
| 0.0044 | 17.4779 | 3950 | 4.4541 | |
|
| 0.0719 | 17.6991 | 4000 | 4.4613 | |
|
| 0.0271 | 17.9204 | 4050 | 4.5354 | |
|
| 0.0073 | 18.1416 | 4100 | 4.6207 | |
|
| 0.0037 | 18.3628 | 4150 | 4.6541 | |
|
| 0.0171 | 18.5841 | 4200 | 4.6636 | |
|
| 0.0345 | 18.8053 | 4250 | 4.6466 | |
|
| 0.103 | 19.0265 | 4300 | 4.5768 | |
|
| 0.0232 | 19.2478 | 4350 | 4.6006 | |
|
| 0.0162 | 19.4690 | 4400 | 4.6079 | |
|
| 0.0261 | 19.6903 | 4450 | 4.6057 | |
|
| 0.0083 | 19.9115 | 4500 | 4.6126 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.3.1+cu121 |
|
- Datasets 2.19.2 |
|
- Tokenizers 0.19.1 |
|
|
