---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
datasets:
- drug_bill_layoutv3
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutlmv3-finetuned-cord_100
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: drug_bill_layoutv3
      type: drug_bill_layoutv3
      config: Vin_Drug_Bill
      split: train
      args: Vin_Drug_Bill
    metrics:
    - name: Precision
      type: precision
      value: 1.0
    - name: Recall
      type: recall
      value: 1.0
    - name: F1
      type: f1
      value: 1.0
    - name: Accuracy
      type: accuracy
      value: 1.0
---

<!-- 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-cord_100

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the drug_bill_layoutv3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0003
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0

## 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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log        | 1.33  | 250  | 0.0010          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0648        | 2.66  | 500  | 0.0003          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0648        | 3.99  | 750  | 0.0004          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0115        | 5.32  | 1000 | 0.0002          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0115        | 6.65  | 1250 | 0.0002          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0134        | 7.98  | 1500 | 0.0001          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0134        | 9.31  | 1750 | 0.0001          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0045        | 10.64 | 2000 | 0.0001          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0045        | 11.97 | 2250 | 0.0001          | 1.0       | 1.0    | 1.0 | 1.0      |
| 0.0004        | 13.3  | 2500 | 0.0001          | 1.0       | 1.0    | 1.0 | 1.0      |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2