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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-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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6088
- Precision: 0.9024
- Recall: 0.9190
- F1: 0.9107
- Accuracy: 0.8544
## 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 | 1.33 | 100 | 0.6659 | 0.7835 | 0.8217 | 0.8021 | 0.7825 |
| No log | 2.67 | 200 | 0.5631 | 0.8229 | 0.8912 | 0.8557 | 0.7903 |
| No log | 4.0 | 300 | 0.4653 | 0.8470 | 0.8992 | 0.8723 | 0.8389 |
| No log | 5.33 | 400 | 0.5080 | 0.8526 | 0.9081 | 0.8795 | 0.8324 |
| 0.5612 | 6.67 | 500 | 0.5200 | 0.8733 | 0.9036 | 0.8882 | 0.8429 |
| 0.5612 | 8.0 | 600 | 0.5480 | 0.8878 | 0.9160 | 0.9017 | 0.8531 |
| 0.5612 | 9.33 | 700 | 0.5655 | 0.8894 | 0.9146 | 0.9018 | 0.8521 |
| 0.5612 | 10.67 | 800 | 0.5971 | 0.8943 | 0.9160 | 0.9050 | 0.8514 |
| 0.5612 | 12.0 | 900 | 0.5873 | 0.9022 | 0.9215 | 0.9118 | 0.8583 |
| 0.1425 | 13.33 | 1000 | 0.6088 | 0.9024 | 0.9190 | 0.9107 | 0.8544 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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