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---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-Algo_427Images
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-Algo_427Images
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: 0.0013
- Precision: 0.9937
- Recall: 0.9964
- F1: 0.9950
- Accuracy: 0.9999
## 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: 4
- eval_batch_size: 4
- 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 | 1.25 | 100 | 0.0082 | 0.9505 | 0.9367 | 0.9435 | 0.9983 |
| No log | 2.5 | 200 | 0.0024 | 0.9883 | 0.9901 | 0.9892 | 0.9997 |
| No log | 3.75 | 300 | 0.0020 | 0.9883 | 0.9919 | 0.9901 | 0.9997 |
| No log | 5.0 | 400 | 0.0016 | 0.9910 | 0.9928 | 0.9919 | 0.9998 |
| 0.0301 | 6.25 | 500 | 0.0015 | 0.9910 | 0.9928 | 0.9919 | 0.9998 |
| 0.0301 | 7.5 | 600 | 0.0014 | 0.9928 | 0.9946 | 0.9937 | 0.9998 |
| 0.0301 | 8.75 | 700 | 0.0013 | 0.9928 | 0.9946 | 0.9937 | 0.9998 |
| 0.0301 | 10.0 | 800 | 0.0013 | 0.9937 | 0.9964 | 0.9950 | 0.9999 |
| 0.0301 | 11.25 | 900 | 0.0013 | 0.9928 | 0.9946 | 0.9937 | 0.9998 |
| 0.002 | 12.5 | 1000 | 0.0013 | 0.9937 | 0.9964 | 0.9950 | 0.9999 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3
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