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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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datasets: |
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- cord-layoutlmv3 |
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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: project-ocr |
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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: cord-layoutlmv3 |
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type: cord-layoutlmv3 |
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config: cord |
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split: test |
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args: cord |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.7515745276417075 |
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- name: Recall |
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type: recall |
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value: 0.8038922155688623 |
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- name: F1 |
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type: f1 |
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value: 0.7768535262206148 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8102716468590832 |
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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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# project-ocr |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the cord-layoutlmv3 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9877 |
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- Precision: 0.7516 |
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- Recall: 0.8039 |
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- F1: 0.7769 |
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- Accuracy: 0.8103 |
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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: 5 |
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- eval_batch_size: 5 |
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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: 500 |
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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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| No log | 0.83 | 50 | 2.6184 | 0.4355 | 0.5404 | 0.4823 | 0.4338 | |
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| No log | 1.67 | 100 | 1.8766 | 0.5912 | 0.6018 | 0.5964 | 0.5620 | |
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| No log | 2.5 | 150 | 1.6165 | 0.5737 | 0.6347 | 0.6027 | 0.6150 | |
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| No log | 3.33 | 200 | 1.4317 | 0.5732 | 0.6737 | 0.6194 | 0.6944 | |
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| No log | 4.17 | 250 | 1.2787 | 0.6190 | 0.7126 | 0.6625 | 0.7347 | |
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| No log | 5.0 | 300 | 1.1632 | 0.6729 | 0.7560 | 0.7120 | 0.7759 | |
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| No log | 5.83 | 350 | 1.0990 | 0.6980 | 0.7665 | 0.7306 | 0.7857 | |
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| No log | 6.67 | 400 | 1.0327 | 0.7125 | 0.7792 | 0.7444 | 0.7946 | |
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| No log | 7.5 | 450 | 0.9994 | 0.7526 | 0.8016 | 0.7764 | 0.8065 | |
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| 1.6589 | 8.33 | 500 | 0.9877 | 0.7516 | 0.8039 | 0.7769 | 0.8103 | |
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### Framework versions |
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- Transformers 4.27.1 |
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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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