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---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
datasets:
- funsd-layoutlmv3
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: test
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: funsd-layoutlmv3
type: funsd-layoutlmv3
config: funsd
split: test
args: funsd
metrics:
- name: Precision
type: precision
value: 0.9002457002457003
- name: Recall
type: recall
value: 0.9100844510680576
- name: F1
type: f1
value: 0.9051383399209486
- name: Accuracy
type: accuracy
value: 0.8547486033519553
---
<!-- 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. -->
# test
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the funsd-layoutlmv3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6194
- Precision: 0.9002
- Recall: 0.9101
- F1: 0.9051
- Accuracy: 0.8547
## 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 | 0.6953 | 0.7761 | 0.8058 | 0.7906 | 0.7680 |
| No log | 2.67 | 200 | 0.5117 | 0.8250 | 0.8808 | 0.8520 | 0.8290 |
| No log | 4.0 | 300 | 0.5177 | 0.8397 | 0.8897 | 0.8640 | 0.8337 |
| No log | 5.33 | 400 | 0.5165 | 0.8642 | 0.9106 | 0.8868 | 0.8509 |
| 0.5653 | 6.67 | 500 | 0.5378 | 0.8735 | 0.9091 | 0.8909 | 0.8458 |
| 0.5653 | 8.0 | 600 | 0.5698 | 0.8733 | 0.9111 | 0.8918 | 0.8482 |
| 0.5653 | 9.33 | 700 | 0.5773 | 0.8934 | 0.9076 | 0.9004 | 0.8557 |
| 0.5653 | 10.67 | 800 | 0.6073 | 0.8905 | 0.9006 | 0.8955 | 0.8520 |
| 0.5653 | 12.0 | 900 | 0.6090 | 0.8940 | 0.9091 | 0.9015 | 0.8513 |
| 0.1357 | 13.33 | 1000 | 0.6194 | 0.9002 | 0.9101 | 0.9051 | 0.8547 |
### Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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