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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: 0.8925979680696662
- name: Recall
type: recall
value: 0.9165424739195231
- name: F1
type: f1
value: 0.9044117647058824
- name: Accuracy
type: accuracy
value: 0.86009746820397
---
<!-- 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: 0.6509
- Precision: 0.8926
- Recall: 0.9165
- F1: 0.9044
- Accuracy: 0.8601
## 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 | 0.7445 | 0.7475 | 0.7869 | 0.7667 | 0.7630 |
| No log | 2.67 | 200 | 0.5447 | 0.8075 | 0.8793 | 0.8419 | 0.8194 |
| No log | 4.0 | 300 | 0.5183 | 0.8425 | 0.8957 | 0.8683 | 0.8418 |
| No log | 5.33 | 400 | 0.5603 | 0.8281 | 0.8952 | 0.8603 | 0.8307 |
| 0.5735 | 6.67 | 500 | 0.5571 | 0.8535 | 0.9001 | 0.8762 | 0.8376 |
| 0.5735 | 8.0 | 600 | 0.5647 | 0.8824 | 0.9096 | 0.8958 | 0.8536 |
| 0.5735 | 9.33 | 700 | 0.5896 | 0.8802 | 0.9121 | 0.8958 | 0.8547 |
| 0.5735 | 10.67 | 800 | 0.6298 | 0.8935 | 0.9165 | 0.9049 | 0.8587 |
| 0.5735 | 12.0 | 900 | 0.6280 | 0.8965 | 0.9210 | 0.9086 | 0.8615 |
| 0.1395 | 13.33 | 1000 | 0.6509 | 0.8926 | 0.9165 | 0.9044 | 0.8601 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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