---
library_name: transformers
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
datasets:
- layoutlmv3
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: test
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: layoutlmv3
      type: layoutlmv3
      config: InvoiceExtraction
      split: test
      args: InvoiceExtraction
    metrics:
    - name: Precision
      type: precision
      value: 0.0
    - name: Recall
      type: recall
      value: 0.0
    - name: F1
      type: f1
      value: 0.0
    - name: Accuracy
      type: accuracy
      value: 0.6923076923076923
---

<!-- 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 layoutlmv3 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1824
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.6923

## 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: 0.00011
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 400

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log        | 5.0   | 20   | 3.5946          | 0.0       | 0.0    | 0.0 | 0.5641   |
| No log        | 10.0  | 40   | 4.0548          | 0.0       | 0.0    | 0.0 | 0.5897   |
| No log        | 15.0  | 60   | 3.0002          | 0.0       | 0.0    | 0.0 | 0.5897   |
| No log        | 20.0  | 80   | 2.1386          | 0.0       | 0.0    | 0.0 | 0.6667   |
| No log        | 25.0  | 100  | 2.3658          | 0.0       | 0.0    | 0.0 | 0.6667   |
| No log        | 30.0  | 120  | 2.8136          | 0.0       | 0.0    | 0.0 | 0.6410   |
| No log        | 35.0  | 140  | 3.3828          | 0.0       | 0.0    | 0.0 | 0.5897   |
| No log        | 40.0  | 160  | 2.6686          | 0.0       | 0.0    | 0.0 | 0.6923   |
| No log        | 45.0  | 180  | 2.9943          | 0.0       | 0.0    | 0.0 | 0.6667   |
| No log        | 50.0  | 200  | 2.9472          | 0.0       | 0.0    | 0.0 | 0.6923   |
| No log        | 55.0  | 220  | 3.0009          | 0.0       | 0.0    | 0.0 | 0.6923   |
| No log        | 60.0  | 240  | 3.0470          | 0.0       | 0.0    | 0.0 | 0.6923   |
| No log        | 65.0  | 260  | 3.0742          | 0.0       | 0.0    | 0.0 | 0.6923   |
| No log        | 70.0  | 280  | 3.3041          | 0.0       | 0.0    | 0.0 | 0.6667   |
| No log        | 75.0  | 300  | 3.1925          | 0.0       | 0.0    | 0.0 | 0.6923   |
| No log        | 80.0  | 320  | 3.1618          | 0.0       | 0.0    | 0.0 | 0.6923   |
| No log        | 85.0  | 340  | 3.1684          | 0.0       | 0.0    | 0.0 | 0.6923   |
| No log        | 90.0  | 360  | 3.1765          | 0.0       | 0.0    | 0.0 | 0.6923   |
| No log        | 95.0  | 380  | 3.1813          | 0.0       | 0.0    | 0.0 | 0.6923   |
| No log        | 100.0 | 400  | 3.1824          | 0.0       | 0.0    | 0.0 | 0.6923   |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1