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---
license: cc-by-nc-sa-4.0
base_model: microsoft/layoutlmv3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: layoutmlv3_thursday_oct4_v7
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. -->
# layoutmlv3_thursday_oct4_v7
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: 0.2861
- Precision: 0.8352
- Recall: 0.7894
- F1: 0.8116
- Accuracy: 0.9586
## 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 | 1.12 | 100 | 0.2568 | 0.8574 | 0.7770 | 0.8152 | 0.9586 |
| No log | 2.25 | 200 | 0.2653 | 0.8268 | 0.7858 | 0.8058 | 0.9581 |
| No log | 3.37 | 300 | 0.2728 | 0.7982 | 0.7770 | 0.7874 | 0.9565 |
| No log | 4.49 | 400 | 0.2626 | 0.8569 | 0.7735 | 0.8130 | 0.9589 |
| 0.114 | 5.62 | 500 | 0.2861 | 0.8352 | 0.7894 | 0.8116 | 0.9586 |
| 0.114 | 6.74 | 600 | 0.2978 | 0.8205 | 0.7929 | 0.8065 | 0.9582 |
| 0.114 | 7.87 | 700 | 0.2942 | 0.8256 | 0.7876 | 0.8062 | 0.9584 |
| 0.114 | 8.99 | 800 | 0.2910 | 0.8420 | 0.7735 | 0.8063 | 0.9579 |
| 0.114 | 10.11 | 900 | 0.3028 | 0.8346 | 0.7770 | 0.8048 | 0.9574 |
| 0.0846 | 11.24 | 1000 | 0.2989 | 0.8318 | 0.7876 | 0.8091 | 0.9581 |
### Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
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