---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: track_traininglogs2
  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. -->

# track_traininglogs2

This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3388
- Precision: 0.8871
- Recall: 0.8800
- F1: 0.8835
- Accuracy: 0.9465

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.6119        | 1.0   | 684  | 0.2890          | 0.8515    | 0.7911 | 0.8202 | 0.9172   |
| 0.2969        | 2.0   | 1368 | 0.2478          | 0.8720    | 0.8279 | 0.8494 | 0.9302   |
| 0.1876        | 3.0   | 2052 | 0.2418          | 0.8354    | 0.8737 | 0.8541 | 0.9332   |
| 0.1476        | 4.0   | 2736 | 0.2480          | 0.8697    | 0.8620 | 0.8658 | 0.9378   |
| 0.1302        | 5.0   | 3420 | 0.2707          | 0.8692    | 0.8697 | 0.8694 | 0.9405   |
| 0.0798        | 6.0   | 4104 | 0.2641          | 0.8755    | 0.8798 | 0.8776 | 0.9434   |
| 0.0642        | 7.0   | 4788 | 0.2694          | 0.8897    | 0.8661 | 0.8777 | 0.9449   |
| 0.0502        | 8.0   | 5472 | 0.3050          | 0.8878    | 0.8741 | 0.8809 | 0.9462   |
| 0.0267        | 9.0   | 6156 | 0.3379          | 0.8888    | 0.8750 | 0.8818 | 0.9453   |
| 0.0273        | 10.0  | 6840 | 0.3388          | 0.8871    | 0.8800 | 0.8835 | 0.9465   |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3