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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: layout3
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. -->
# layout3
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: 0.6334
- Precision: 0.8935
- Recall: 0.9131
- F1: 0.9032
- Accuracy: 0.8586
## 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 | 1.33 | 100 | 0.6874 | 0.7820 | 0.8073 | 0.7944 | 0.7841 |
| No log | 2.67 | 200 | 0.4485 | 0.8321 | 0.8838 | 0.8571 | 0.8474 |
| No log | 4.0 | 300 | 0.4403 | 0.8579 | 0.9086 | 0.8825 | 0.8414 |
| No log | 5.33 | 400 | 0.4593 | 0.8452 | 0.9056 | 0.8743 | 0.8341 |
| 0.5531 | 6.67 | 500 | 0.4881 | 0.8732 | 0.9170 | 0.8946 | 0.8575 |
| 0.5531 | 8.0 | 600 | 0.5332 | 0.8761 | 0.9101 | 0.8928 | 0.8547 |
| 0.5531 | 9.33 | 700 | 0.5910 | 0.8894 | 0.9106 | 0.8999 | 0.8517 |
| 0.5531 | 10.67 | 800 | 0.5914 | 0.8909 | 0.9131 | 0.9019 | 0.8557 |
| 0.5531 | 12.0 | 900 | 0.6127 | 0.9001 | 0.9180 | 0.9090 | 0.8614 |
| 0.1245 | 13.33 | 1000 | 0.6334 | 0.8935 | 0.9131 | 0.9032 | 0.8586 |
### Framework versions
- Transformers 4.32.0
- Pytorch 2.0.0+cu118
- Datasets 2.17.1
- Tokenizers 0.13.2
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