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---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
datasets:
- funsd
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-funsd
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: funsd
type: funsd
config: funsd
split: test
args: funsd
metrics:
- name: Precision
type: precision
value: 0.7467652495378928
- name: Recall
type: recall
value: 0.8027819175360159
- name: F1
type: f1
value: 0.7737610725401005
- name: Accuracy
type: accuracy
value: 0.8188517770117675
---
<!-- 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 the funsd dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5984
- Precision: 0.7468
- Recall: 0.8028
- F1: 0.7738
- Accuracy: 0.8189
## 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: 1
- eval_batch_size: 1
- 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 | 0.67 | 100 | 1.0197 | 0.5025 | 0.5981 | 0.5462 | 0.6622 |
| No log | 1.34 | 200 | 0.6833 | 0.6203 | 0.7238 | 0.6680 | 0.7608 |
| No log | 2.01 | 300 | 0.6237 | 0.6401 | 0.7794 | 0.7030 | 0.7846 |
| No log | 2.68 | 400 | 0.6028 | 0.6892 | 0.7392 | 0.7133 | 0.7771 |
| 0.8343 | 3.36 | 500 | 0.5948 | 0.7175 | 0.7884 | 0.7512 | 0.7991 |
| 0.8343 | 4.03 | 600 | 0.5953 | 0.7135 | 0.8028 | 0.7555 | 0.7961 |
| 0.8343 | 4.7 | 700 | 0.5925 | 0.7354 | 0.7953 | 0.7642 | 0.8174 |
| 0.8343 | 5.37 | 800 | 0.6055 | 0.7397 | 0.7933 | 0.7656 | 0.8134 |
| 0.8343 | 6.04 | 900 | 0.5940 | 0.7535 | 0.8077 | 0.7797 | 0.8199 |
| 0.3468 | 6.71 | 1000 | 0.5984 | 0.7468 | 0.8028 | 0.7738 | 0.8189 |
### Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
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