---
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