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---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
datasets:
- data_loader
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: models
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: data_loader
type: data_loader
config: default
split: test
args: default
metrics:
- name: Precision
type: precision
value: 0.8940149625935162
- name: Recall
type: recall
value: 0.9168797953964194
- name: F1
type: f1
value: 0.9053030303030304
- name: Accuracy
type: accuracy
value: 0.9743718592964824
---
<!-- 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. -->
# models
This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the data_loader dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1595
- Precision: 0.8940
- Recall: 0.9169
- F1: 0.9053
- Accuracy: 0.9744
## 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: 2
- eval_batch_size: 2
- 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 | 2.5 | 100 | 0.1926 | 0.7730 | 0.8274 | 0.7993 | 0.9452 |
| No log | 5.0 | 200 | 0.1342 | 0.8285 | 0.8708 | 0.8491 | 0.9583 |
| No log | 7.5 | 300 | 0.1217 | 0.8758 | 0.9015 | 0.8885 | 0.9693 |
| No log | 10.0 | 400 | 0.1157 | 0.9082 | 0.9233 | 0.9157 | 0.9769 |
| 0.15 | 12.5 | 500 | 0.1310 | 0.9011 | 0.9092 | 0.9052 | 0.9744 |
| 0.15 | 15.0 | 600 | 0.1583 | 0.8682 | 0.9015 | 0.8846 | 0.9693 |
| 0.15 | 17.5 | 700 | 0.1628 | 0.8867 | 0.9105 | 0.8984 | 0.9724 |
| 0.15 | 20.0 | 800 | 0.1594 | 0.8945 | 0.9220 | 0.9081 | 0.9749 |
| 0.15 | 22.5 | 900 | 0.1579 | 0.8940 | 0.9169 | 0.9053 | 0.9744 |
| 0.0047 | 25.0 | 1000 | 0.1595 | 0.8940 | 0.9169 | 0.9053 | 0.9744 |
### Framework versions
- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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