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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_thursday_sep7_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_thursday_sep7_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: 0.1416
- Precision: 0.5517
- Recall: 0.9412
- F1: 0.6957
- Accuracy: 0.9822
## 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 | 0.3243 | 0.5556 | 0.8824 | 0.6818 | 0.9485 |
| No log | 16.67 | 200 | 0.1584 | 0.6087 | 0.8235 | 0.7 | 0.9734 |
| No log | 25.0 | 300 | 0.1682 | 0.5517 | 0.9412 | 0.6957 | 0.9769 |
| No log | 33.33 | 400 | 0.1773 | 0.4545 | 0.8824 | 0.6 | 0.9734 |
| 0.2633 | 41.67 | 500 | 0.1631 | 0.4375 | 0.8235 | 0.5714 | 0.9751 |
| 0.2633 | 50.0 | 600 | 0.1526 | 0.5517 | 0.9412 | 0.6957 | 0.9769 |
| 0.2633 | 58.33 | 700 | 0.1430 | 0.5517 | 0.9412 | 0.6957 | 0.9840 |
| 0.2633 | 66.67 | 800 | 0.1497 | 0.5517 | 0.9412 | 0.6957 | 0.9822 |
| 0.2633 | 75.0 | 900 | 0.1418 | 0.5517 | 0.9412 | 0.6957 | 0.9805 |
| 0.0111 | 83.33 | 1000 | 0.1416 | 0.5517 | 0.9412 | 0.6957 | 0.9822 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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