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---
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: 3.6446
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 5.1899 | 0.2212 | 50 | 4.5198 |
| 4.3841 | 0.4425 | 100 | 3.9910 |
| 4.0167 | 0.6637 | 150 | 3.9030 |
| 3.7906 | 0.8850 | 200 | 3.4974 |
| 3.426 | 1.1062 | 250 | 3.7834 |
| 3.0774 | 1.3274 | 300 | 3.2013 |
| 2.9541 | 1.5487 | 350 | 3.0711 |
| 2.7072 | 1.7699 | 400 | 2.7067 |
| 2.3127 | 1.9912 | 450 | 2.6800 |
| 2.0786 | 2.2124 | 500 | 2.6677 |
| 1.9055 | 2.4336 | 550 | 2.5482 |
| 2.0272 | 2.6549 | 600 | 2.2344 |
| 1.6753 | 2.8761 | 650 | 2.3265 |
| 1.4848 | 3.0973 | 700 | 2.5170 |
| 1.4359 | 3.3186 | 750 | 2.4527 |
| 1.2884 | 3.5398 | 800 | 2.4033 |
| 1.3217 | 3.7611 | 850 | 2.0981 |
| 1.3359 | 3.9823 | 900 | 2.2481 |
| 0.9068 | 4.2035 | 950 | 2.4053 |
| 1.1537 | 4.4248 | 1000 | 2.5739 |
| 0.8742 | 4.6460 | 1050 | 2.5003 |
| 0.9135 | 4.8673 | 1100 | 2.5511 |
| 0.9073 | 5.0885 | 1150 | 2.6724 |
| 0.6596 | 5.3097 | 1200 | 2.6174 |
| 0.7797 | 5.5310 | 1250 | 2.8350 |
| 0.6031 | 5.7522 | 1300 | 3.1642 |
| 0.7287 | 5.9735 | 1350 | 3.0317 |
| 0.4586 | 6.1947 | 1400 | 3.1821 |
| 0.5755 | 6.4159 | 1450 | 3.1222 |
| 0.4174 | 6.6372 | 1500 | 3.6997 |
| 0.2839 | 6.8584 | 1550 | 3.7044 |
| 0.5378 | 7.0796 | 1600 | 3.4223 |
| 0.3549 | 7.3009 | 1650 | 3.3740 |
| 0.2239 | 7.5221 | 1700 | 3.6018 |
| 0.3209 | 7.7434 | 1750 | 3.3689 |
| 0.2594 | 7.9646 | 1800 | 3.6625 |
| 0.1606 | 8.1858 | 1850 | 3.6916 |
| 0.1525 | 8.4071 | 1900 | 3.6299 |
| 0.1104 | 8.6283 | 1950 | 3.7133 |
| 0.3046 | 8.8496 | 2000 | 3.7701 |
| 0.3161 | 9.0708 | 2050 | 3.6224 |
| 0.1331 | 9.2920 | 2100 | 3.6198 |
| 0.2595 | 9.5133 | 2150 | 3.6251 |
| 0.1928 | 9.7345 | 2200 | 3.6359 |
| 0.1465 | 9.9558 | 2250 | 3.6446 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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