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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-testCUSTOMds20_02
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-testCUSTOMds20_02
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: 0.1298
- Precision: 0.8546
- Recall: 0.8362
- F1: 0.8453
- Accuracy: 0.9807
## 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 | 1.25 | 100 | 0.0624 | 0.8578 | 0.8578 | 0.8578 | 0.9837 |
| No log | 2.5 | 200 | 0.0858 | 0.8603 | 0.8491 | 0.8547 | 0.9814 |
| No log | 3.75 | 300 | 0.0826 | 0.9062 | 0.875 | 0.8904 | 0.9859 |
| No log | 5.0 | 400 | 0.0940 | 0.9018 | 0.8707 | 0.8860 | 0.9851 |
| 0.0658 | 6.25 | 500 | 0.1237 | 0.8502 | 0.8319 | 0.8410 | 0.9807 |
| 0.0658 | 7.5 | 600 | 0.1125 | 0.9045 | 0.8578 | 0.8805 | 0.9844 |
| 0.0658 | 8.75 | 700 | 0.1252 | 0.8448 | 0.8448 | 0.8448 | 0.9799 |
| 0.0658 | 10.0 | 800 | 0.1156 | 0.8678 | 0.8491 | 0.8584 | 0.9829 |
| 0.0658 | 11.25 | 900 | 0.1238 | 0.8559 | 0.8448 | 0.8503 | 0.9822 |
| 0.0036 | 12.5 | 1000 | 0.1298 | 0.8546 | 0.8362 | 0.8453 | 0.9807 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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