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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-funsd
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-funsd
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: 0.5469
- Precision: 0.8633
- Recall: 0.903
- F1: 0.8827
- Accuracy: 0.8435
## 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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 300
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.67 | 25 | 1.2106 | 0.4708 | 0.5275 | 0.4975 | 0.6554 |
| No log | 3.33 | 50 | 0.7854 | 0.7498 | 0.8075 | 0.7776 | 0.7687 |
| No log | 5.0 | 75 | 0.6002 | 0.7932 | 0.8455 | 0.8185 | 0.8142 |
| No log | 6.67 | 100 | 0.6523 | 0.7849 | 0.876 | 0.8280 | 0.7781 |
| No log | 8.33 | 125 | 0.5190 | 0.8152 | 0.8755 | 0.8443 | 0.8354 |
| No log | 10.0 | 150 | 0.5064 | 0.8315 | 0.888 | 0.8588 | 0.8338 |
| No log | 11.67 | 175 | 0.5342 | 0.8482 | 0.8915 | 0.8693 | 0.8344 |
| No log | 13.33 | 200 | 0.5538 | 0.8492 | 0.8925 | 0.8703 | 0.8201 |
| No log | 15.0 | 225 | 0.5336 | 0.8557 | 0.901 | 0.8777 | 0.8349 |
| No log | 16.67 | 250 | 0.5465 | 0.8564 | 0.8975 | 0.8765 | 0.8385 |
| No log | 18.33 | 275 | 0.5403 | 0.8580 | 0.9005 | 0.8788 | 0.8439 |
| No log | 20.0 | 300 | 0.5469 | 0.8633 | 0.903 | 0.8827 | 0.8435 |
### Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu111
- Datasets 2.13.2
- Tokenizers 0.10.1
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