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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: test
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. -->
# test
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: 0.2843
- Precision: 0.4118
- Recall: 0.8235
- F1: 0.5490
- Accuracy: 0.9485
## 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 | 0.6271 | 0.1864 | 0.6471 | 0.2895 | 0.8757 |
| No log | 16.67 | 200 | 0.1736 | 0.52 | 0.7647 | 0.6190 | 0.9734 |
| No log | 25.0 | 300 | 0.1302 | 0.5714 | 0.9412 | 0.7111 | 0.9734 |
| No log | 33.33 | 400 | 0.2835 | 0.5333 | 0.9412 | 0.6809 | 0.9556 |
| 0.287 | 41.67 | 500 | 0.0924 | 0.4828 | 0.8235 | 0.6087 | 0.9805 |
| 0.287 | 50.0 | 600 | 0.2594 | 0.4412 | 0.8824 | 0.5882 | 0.9485 |
| 0.287 | 58.33 | 700 | 0.3172 | 0.4412 | 0.8824 | 0.5882 | 0.9467 |
| 0.287 | 66.67 | 800 | 0.2447 | 0.4545 | 0.8824 | 0.6 | 0.9520 |
| 0.287 | 75.0 | 900 | 0.2941 | 0.4118 | 0.8235 | 0.5490 | 0.9485 |
| 0.013 | 83.33 | 1000 | 0.2843 | 0.4118 | 0.8235 | 0.5490 | 0.9485 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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