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--- |
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license: cc-by-nc-sa-4.0 |
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tags: |
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- generated_from_trainer |
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- layoutlmv3 |
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- token_classifier |
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- layout_analysis |
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datasets: |
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- pierreguillou/DocLayNet-small |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: layoutlmv3-finetuned-DocLayNet |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: doc_lay_net-small |
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type: doc_lay_net-small |
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config: DocLayNet_2022.08_processed_on_2023.01 |
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split: test |
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args: DocLayNet_2022.08_processed_on_2023.01 |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.6178861788617886 |
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- name: Recall |
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type: recall |
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value: 0.7238095238095238 |
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- name: F1 |
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type: f1 |
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value: 0.6666666666666667 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8719611021069692 |
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language: |
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- en |
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pipeline_tag: token-classification |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# layoutlmv3-finetuned-DocLayNet |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the doc_lay_net-small dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5644 |
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- Precision: 0.6179 |
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- Recall: 0.7238 |
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- F1: 0.6667 |
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- Accuracy: 0.8720 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- training_steps: 1000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 1.3383 | 0.58 | 200 | 0.8358 | 0.3007 | 0.4381 | 0.3566 | 0.7724 | |
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| 0.8308 | 1.16 | 400 | 0.6735 | 0.4634 | 0.5429 | 0.5 | 0.8084 | |
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| 0.518 | 1.74 | 600 | 0.5706 | 0.5373 | 0.6857 | 0.6025 | 0.8399 | |
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| 0.3856 | 2.33 | 800 | 0.6303 | 0.6032 | 0.7238 | 0.6580 | 0.8648 | |
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| 0.2558 | 2.91 | 1000 | 0.5644 | 0.6179 | 0.7238 | 0.6667 | 0.8720 | |
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### Framework versions |
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- Transformers 4.27.3 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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### How to Train & Inference: |
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Check this out this repo: https://github.com/mit1280/Document-AI |
