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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: 0.8876459143968871
- name: Recall
type: recall
value: 0.9066070541480378
- name: F1
type: f1
value: 0.8970262963873188
- 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: 0.6568
- Precision: 0.8876
- Recall: 0.9066
- F1: 0.8970
- 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 | 0.6157 | 0.7621 | 0.8400 | 0.7991 | 0.8051 |
| No log | 2.67 | 200 | 0.4834 | 0.7915 | 0.8902 | 0.8380 | 0.8334 |
| No log | 4.0 | 300 | 0.4929 | 0.8484 | 0.8922 | 0.8697 | 0.8493 |
| No log | 5.33 | 400 | 0.5191 | 0.8746 | 0.9006 | 0.8874 | 0.8556 |
| 0.5561 | 6.67 | 500 | 0.5553 | 0.8671 | 0.9041 | 0.8852 | 0.8487 |
| 0.5561 | 8.0 | 600 | 0.5766 | 0.8723 | 0.9091 | 0.8903 | 0.8388 |
| 0.5561 | 9.33 | 700 | 0.6486 | 0.8816 | 0.8917 | 0.8866 | 0.8511 |
| 0.5561 | 10.67 | 800 | 0.6188 | 0.8861 | 0.9086 | 0.8972 | 0.8608 |
| 0.5561 | 12.0 | 900 | 0.6317 | 0.8890 | 0.9071 | 0.8980 | 0.8630 |
| 0.1298 | 13.33 | 1000 | 0.6568 | 0.8876 | 0.9066 | 0.8970 | 0.8601 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cpu
- Datasets 2.12.0
- Tokenizers 0.13.3
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