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---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-language-levels-v5-4000
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. -->
# layoutlmv3-finetuned-language-levels-v5-4000
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0913
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 0.9824
## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 4000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 0.2618 | 100 | 0.8184 | 0.9647 | 0.9630 | 0.9639 | 0.6971 |
| No log | 0.5236 | 200 | 0.6254 | 0.9743 | 0.9815 | 0.9779 | 0.7404 |
| No log | 0.7853 | 300 | 0.4760 | 0.9926 | 0.9944 | 0.9935 | 0.7981 |
| No log | 1.0471 | 400 | 0.3675 | 0.9798 | 0.9889 | 0.9843 | 0.8910 |
| 0.6763 | 1.3089 | 500 | 0.0913 | 1.0 | 1.0 | 1.0 | 0.9824 |
| 0.6763 | 1.5707 | 600 | 0.0375 | 1.0 | 1.0 | 1.0 | 0.9904 |
| 0.6763 | 1.8325 | 700 | 0.0149 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.6763 | 2.0942 | 800 | 0.0078 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.6763 | 2.3560 | 900 | 0.0047 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.037 | 2.6178 | 1000 | 0.0037 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.037 | 2.8796 | 1100 | 0.0030 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.037 | 3.1414 | 1200 | 0.0026 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.037 | 3.4031 | 1300 | 0.0022 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.037 | 3.6649 | 1400 | 0.0019 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0046 | 3.9267 | 1500 | 0.0017 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0046 | 4.1885 | 1600 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0046 | 4.4503 | 1700 | 0.0014 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0046 | 4.7120 | 1800 | 0.0013 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0046 | 4.9738 | 1900 | 0.0012 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0025 | 5.2356 | 2000 | 0.0011 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0025 | 5.4974 | 2100 | 0.0010 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0025 | 5.7592 | 2200 | 0.0010 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0025 | 6.0209 | 2300 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0025 | 6.2827 | 2400 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0017 | 6.5445 | 2500 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0017 | 6.8063 | 2600 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0017 | 7.0681 | 2700 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0017 | 7.3298 | 2800 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0017 | 7.5916 | 2900 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0013 | 7.8534 | 3000 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0013 | 8.1152 | 3100 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0013 | 8.3770 | 3200 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0013 | 8.6387 | 3300 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0013 | 8.9005 | 3400 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0011 | 9.1623 | 3500 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0011 | 9.4241 | 3600 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0011 | 9.6859 | 3700 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0011 | 9.9476 | 3800 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0011 | 10.2094 | 3900 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.001 | 10.4712 | 4000 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.43.3
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
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