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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: 0.8808265257087938
- name: Recall
type: recall
value: 0.910581222056632
- name: F1
type: f1
value: 0.895456765999023
- name: Accuracy
type: accuracy
value: 0.8507072387970998
---
<!-- 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: 0.5799
- Precision: 0.8808
- Recall: 0.9106
- F1: 0.8955
- Accuracy: 0.8507
## 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 | 1.3333 | 100 | 0.6686 | 0.7452 | 0.8251 | 0.7831 | 0.7535 |
| No log | 2.6667 | 200 | 0.4724 | 0.8064 | 0.8713 | 0.8376 | 0.8389 |
| No log | 4.0 | 300 | 0.4922 | 0.8612 | 0.8942 | 0.8774 | 0.8481 |
| No log | 5.3333 | 400 | 0.4632 | 0.8587 | 0.8997 | 0.8787 | 0.8521 |
| 0.544 | 6.6667 | 500 | 0.4850 | 0.8632 | 0.9031 | 0.8827 | 0.8474 |
| 0.544 | 8.0 | 600 | 0.5024 | 0.8744 | 0.8992 | 0.8866 | 0.8451 |
| 0.544 | 9.3333 | 700 | 0.5394 | 0.8768 | 0.9155 | 0.8957 | 0.8565 |
| 0.544 | 10.6667 | 800 | 0.5647 | 0.8800 | 0.9146 | 0.8970 | 0.8550 |
| 0.544 | 12.0 | 900 | 0.5798 | 0.8847 | 0.9106 | 0.8974 | 0.8545 |
| 0.1288 | 13.3333 | 1000 | 0.5799 | 0.8808 | 0.9106 | 0.8955 | 0.8507 |
### Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.1.1+cu118
- Datasets 2.15.0
- Tokenizers 0.19.1
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