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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: layoutmlv3_sunday_sep3_v5
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. -->
# layoutmlv3_sunday_sep3_v5
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: 0.1630
- Precision: 0.6867
- Recall: 0.7308
- F1: 0.7081
- Accuracy: 0.9570
## 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: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 8.33 | 100 | 0.5150 | 0.5139 | 0.4744 | 0.4933 | 0.8460 |
| No log | 16.67 | 200 | 0.2462 | 0.5053 | 0.6154 | 0.5549 | 0.9387 |
| No log | 25.0 | 300 | 0.1973 | 0.6471 | 0.7051 | 0.6748 | 0.9536 |
| No log | 33.33 | 400 | 0.1617 | 0.6667 | 0.7179 | 0.6914 | 0.9520 |
| 0.3718 | 41.67 | 500 | 0.1630 | 0.6867 | 0.7308 | 0.7081 | 0.9570 |
| 0.3718 | 50.0 | 600 | 0.2247 | 0.5106 | 0.6154 | 0.5581 | 0.9073 |
| 0.3718 | 58.33 | 700 | 0.3364 | 0.5393 | 0.6154 | 0.5749 | 0.8907 |
| 0.3718 | 66.67 | 800 | 0.1783 | 0.5435 | 0.6410 | 0.5882 | 0.9454 |
| 0.3718 | 75.0 | 900 | 0.2255 | 0.5263 | 0.6410 | 0.5780 | 0.9305 |
| 0.0196 | 83.33 | 1000 | 0.2781 | 0.5158 | 0.6282 | 0.5665 | 0.9123 |
### Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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