---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: EElayoutlmv3_jordyvl_rvl_cdip_easyocr_2023-07-09_weighted
  results: []
---

<!-- 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. -->

# EElayoutlmv3_jordyvl_rvl_cdip_easyocr_2023-07-09_weighted

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2223
- Accuracy: 0.9400
- Exit 0 Accuracy: 0.2580
- Exit 1 Accuracy: 0.5214
- Exit 2 Accuracy: 0.7781
- Exit 3 Accuracy: 0.8564
- Exit 4 Accuracy: 0.9330

## 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: 2e-05
- train_batch_size: 6
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 24
- total_train_batch_size: 144
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Exit 0 Accuracy | Exit 1 Accuracy | Exit 2 Accuracy | Exit 3 Accuracy | Exit 4 Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------------:|:---------------:|:---------------:|:---------------:|:---------------:|
| 2.4115        | 1.0   | 2222  | 0.2907          | 0.9172   | 0.209           | 0.3731          | 0.645           | 0.7651          | 0.9109          |
| 2.0272        | 2.0   | 4444  | 0.2444          | 0.9310   | 0.2243          | 0.4579          | 0.7297          | 0.8172          | 0.9234          |
| 1.8196        | 3.0   | 6666  | 0.2268          | 0.9350   | 0.2383          | 0.4979          | 0.7589          | 0.8439          | 0.9285          |
| 1.7287        | 4.0   | 8888  | 0.2216          | 0.9387   | 0.2438          | 0.5163          | 0.7728          | 0.8533          | 0.9315          |
| 1.6664        | 5.0   | 11110 | 0.2223          | 0.9400   | 0.2580          | 0.5214          | 0.7781          | 0.8564          | 0.9330          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1.post200
- Datasets 2.9.0
- Tokenizers 0.13.2