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license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: LayoutLM_4
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. -->
# LayoutLM_4
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: 0.6673
- Precision: 0.675
- Recall: 0.3576
- F1: 0.4675
- Accuracy: 0.8559
## 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-06
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 7.14 | 100 | 1.2248 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 14.29 | 200 | 0.9800 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 21.43 | 300 | 0.8988 | 0.0 | 0.0 | 0.0 | 0.7818 |
| No log | 28.57 | 400 | 0.8416 | 0.0 | 0.0 | 0.0 | 0.7818 |
| 1.0601 | 35.71 | 500 | 0.8025 | 0.0 | 0.0 | 0.0 | 0.7818 |
| 1.0601 | 42.86 | 600 | 0.7719 | 0.0 | 0.0 | 0.0 | 0.7818 |
| 1.0601 | 50.0 | 700 | 0.7428 | 0.75 | 0.0397 | 0.0755 | 0.7902 |
| 1.0601 | 57.14 | 800 | 0.7225 | 0.5714 | 0.0530 | 0.0970 | 0.7972 |
| 1.0601 | 64.29 | 900 | 0.7107 | 0.6923 | 0.1192 | 0.2034 | 0.8140 |
| 0.6088 | 71.43 | 1000 | 0.6954 | 0.6444 | 0.1921 | 0.2959 | 0.8308 |
| 0.6088 | 78.57 | 1100 | 0.6861 | 0.6727 | 0.2450 | 0.3592 | 0.8392 |
| 0.6088 | 85.71 | 1200 | 0.6800 | 0.6719 | 0.2848 | 0.4 | 0.8462 |
| 0.6088 | 92.86 | 1300 | 0.6694 | 0.6901 | 0.3245 | 0.4414 | 0.8517 |
| 0.6088 | 100.0 | 1400 | 0.6684 | 0.675 | 0.3576 | 0.4675 | 0.8573 |
| 0.5237 | 107.14 | 1500 | 0.6673 | 0.675 | 0.3576 | 0.4675 | 0.8559 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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