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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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- nielsr/funsd-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: pasha |
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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: nielsr/funsd-layoutlmv3 |
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type: nielsr/funsd-layoutlmv3 |
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config: pasha |
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split: test |
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args: pasha |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.986704994610133 |
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- name: Recall |
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type: recall |
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value: 0.989193083573487 |
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- name: F1 |
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type: f1 |
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value: 0.9879474725670084 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9905978784956606 |
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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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# pasha |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the nielsr/funsd-layoutlmv3 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0585 |
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- Precision: 0.9867 |
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- Recall: 0.9892 |
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- F1: 0.9879 |
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- Accuracy: 0.9906 |
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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: 16 |
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- eval_batch_size: 16 |
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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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| No log | 2.13 | 100 | 0.2664 | 0.9534 | 0.9438 | 0.9486 | 0.9571 | |
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| No log | 4.26 | 200 | 0.1044 | 0.9756 | 0.9802 | 0.9779 | 0.9838 | |
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| No log | 6.38 | 300 | 0.0672 | 0.9853 | 0.9899 | 0.9876 | 0.9904 | |
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| No log | 8.51 | 400 | 0.0634 | 0.9824 | 0.9860 | 0.9842 | 0.9884 | |
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| 0.2958 | 10.64 | 500 | 0.0585 | 0.9867 | 0.9892 | 0.9879 | 0.9906 | |
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| 0.2958 | 12.77 | 600 | 0.0511 | 0.9889 | 0.9928 | 0.9908 | 0.9928 | |
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| 0.2958 | 14.89 | 700 | 0.0503 | 0.9871 | 0.9921 | 0.9896 | 0.9925 | |
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| 0.2958 | 17.02 | 800 | 0.0529 | 0.9860 | 0.9903 | 0.9881 | 0.9913 | |
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| 0.2958 | 19.15 | 900 | 0.0581 | 0.9842 | 0.9892 | 0.9867 | 0.9904 | |
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| 0.0256 | 21.28 | 1000 | 0.0571 | 0.9849 | 0.9888 | 0.9869 | 0.9901 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.12.1 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.2 |
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